If I reopened the 2026 folder in 2030, I would check one thing first: did the work completed with AI change a real problem and leave evidence that others could verify and build upon?
AI benchmarks are now appearing faster than any researcher can evaluate them, so I built a radar that makes discovery daily, transparent, and auditable.
When someone publicly told Steve Jobs that he did not understand technology, Jobs paused, conceded part of the criticism, and asked a more consequential question: what will the customer ultimately gain?
The thing that almost stranded me on this international trip was not a typhoon, but several unrelated systems deciding at the same time that they did not trust me.
Does building a benchmark count as research, or is it “crowdfunding a paper”? Does it create public value or consume public resources? Can it build lasting capabilities, or is it useful only for a startup team trying to show investors its potential?
The most dangerous failure mode of an AI science benchmark is not that it is too hard, it is that it quietly becomes either a coding trick or a guessing game.
I spent the last couple of days checking a tempting claim: that Microsoft Flight Simulator is secretly the foundation for a broader Earth digital twin story.
I was in the middle of setting up a second Cloudflare backup, verifying one dataset and configuring another, when the AI agent helping me flagged something unrelated: while listing what had access to my GitHub account, one authorization stood out as unusually broad. That single flag turned into an hour of reviewing GitHub’s installed-apps list, and it was worth every minute.
I ran a health check on my Claude Code setup this week and found 174 custom skills, 124 of which I had never invoked once. They were not failures. Most of them were scaffolding I built for a model that needed it, and then kept long after the model stopped needing it.
The most dangerous failure mode of an AI science benchmark is not that it is too hard, it is that it quietly becomes either a coding trick or a guessing game.
When someone publicly told Steve Jobs that he did not understand technology, Jobs paused, conceded part of the criticism, and asked a more consequential question: what will the customer ultimately gain?
Does building a benchmark count as research, or is it “crowdfunding a paper”? Does it create public value or consume public resources? Can it build lasting capabilities, or is it useful only for a startup team trying to show investors its potential?
The most dangerous failure mode of an AI science benchmark is not that it is too hard, it is that it quietly becomes either a coding trick or a guessing game.
AI benchmarks are now appearing faster than any researcher can evaluate them, so I built a radar that makes discovery daily, transparent, and auditable.
A junior colleague asked me recently if there is a magical brokerage that does it all, from stock trading to high-yield savings, which reminded me of my own naive expectations when I first started investing.
Does building a benchmark count as research, or is it “crowdfunding a paper”? Does it create public value or consume public resources? Can it build lasting capabilities, or is it useful only for a startup team trying to show investors its potential?
I ran a health check on my Claude Code setup this week and found 174 custom skills, 124 of which I had never invoked once. They were not failures. Most of them were scaffolding I built for a model that needed it, and then kept long after the model stopped needing it.
I was in the middle of setting up a second Cloudflare backup, verifying one dataset and configuring another, when the AI agent helping me flagged something unrelated: while listing what had access to my GitHub account, one authorization stood out as unusually broad. That single flag turned into an hour of reviewing GitHub’s installed-apps list, and it was worth every minute.
Most of biology is averages. You measure a million cells, you get a mean. Eric Greene’s lab figured out how to actually watch one DNA molecule at a time, repair itself, in real time, and that changes what kind of questions biology can ask.
I ran a health check on my Claude Code setup this week and found 174 custom skills, 124 of which I had never invoked once. They were not failures. Most of them were scaffolding I built for a model that needed it, and then kept long after the model stopped needing it.
Some books leave behind a few ideas. The Mom Test gave me a method I continue to use: do not ask whether someone likes your idea. Ask what they have already done, how often the problem occurs, what it has cost them, and whether they will commit to a next step.
Most of biology is averages. You measure a million cells, you get a mean. Eric Greene’s lab figured out how to actually watch one DNA molecule at a time, repair itself, in real time, and that changes what kind of questions biology can ask.
AI benchmarks are now appearing faster than any researcher can evaluate them, so I built a radar that makes discovery daily, transparent, and auditable.
I ran a health check on my Claude Code setup this week and found 174 custom skills, 124 of which I had never invoked once. They were not failures. Most of them were scaffolding I built for a model that needed it, and then kept long after the model stopped needing it.
I spent the last couple of days checking a tempting claim: that Microsoft Flight Simulator is secretly the foundation for a broader Earth digital twin story.
Most VCs and accelerators talk about supporting founders. Kehan Dong specifically supports the kind of founder who started building at 16, when nobody told them they were allowed to, and it turns out that population is dramatically underserved.
A widely shared post describes a brainstorming meeting at a robotics startup in Boston. A slide said “No stupid questions.” A Chinese employee interpreted it as “Do not ask stupid questions,” while American colleagues explained it as “Ask freely; no question will be judged stupid.” A related post claims that “Say it again?” is neutral when someone is not heard, whereas “What did you say?” is hostile.
一张流传截图讲了这样一件事:一家波士顿机器人创业公司开头脑风暴会,幻灯片写着 “No stupid questions.” 一位中国员工把它理解为“不要问蠢问题”,美国同事却说它的意思是“什么都可以问,没有问题会被当成蠢问题”。另一组讨论又声称:没听清时说 “Say it again?” 很中性,而 “What did you say?” 很不友好。
AI benchmarks are now appearing faster than any researcher can evaluate them, so I built a radar that makes discovery daily, transparent, and auditable.
The most dangerous failure mode of an AI science benchmark is not that it is too hard, it is that it quietly becomes either a coding trick or a guessing game.
A junior colleague asked me recently if there is a magical brokerage that does it all, from stock trading to high-yield savings, which reminded me of my own naive expectations when I first started investing.
A receipt in Singapore showed S$5.50, while a U.S. credit-card account displayed only US$4.27. Another purchase of about S$48 appeared as roughly US$38. A bank-card transit ride also failed to appear immediately as pending.
The same way text foundation models ate NLP and image models ate computer vision, someone is going to build the foundation model that eats spatial reasoning. Gengchen Mai is one of the people taking that bet seriously, and his SEAI Lab at UT Austin is one of the places it is being built.
I was in the middle of setting up a second Cloudflare backup, verifying one dataset and configuring another, when the AI agent helping me flagged something unrelated: while listing what had access to my GitHub account, one authorization stood out as unusually broad. That single flag turned into an hour of reviewing GitHub’s installed-apps list, and it was worth every minute.
The story goes like this: I’ve been pondering a question lately—given how insanely advanced technology is today, why do we still have to spend so much time dressing up and managing our personal image?
A new paper looked at 739 science Nobel laureates from 1901 to 2023, and the headline number that came out is brutal, at the current rate of progress it would take roughly 600 years before a kid born into a poor country has the same shot at a Nobel as a kid born into a rich one.
A junior colleague asked me recently if there is a magical brokerage that does it all, from stock trading to high-yield savings, which reminded me of my own naive expectations when I first started investing.
Most academic climate scientists will tell you they care about policy and then publish a paper that no policymaker is ever going to read. Geeta Persad spent four years working at the Union of Concerned Scientists translating climate models for water managers, and she came back to academia knowing exactly what the gap looks like.
When someone publicly told Steve Jobs that he did not understand technology, Jobs paused, conceded part of the criticism, and asked a more consequential question: what will the customer ultimately gain?
I spent the last couple of days checking a tempting claim: that Microsoft Flight Simulator is secretly the foundation for a broader Earth digital twin story.
I ended up in the wrong NEXUS line at Vancouver International Airport. By the rules, the mistake was mine. By design, it was an almost predictable wrong turn.
When you join a lab, you do not just get a research direction. You inherit a 30-year codebase that is currently running inside the U.S. National Water Model and was on the critical path forecasting Hurricane Harvey. That is what working with Zong-Liang Yang at the Jackson School of Geosciences actually looks like.
Most land surface models treat a tree like a passive straw. Water comes in at the roots, water leaves at the leaves, end of story. Ashley Matheny’s research basically says no, a tree is an active hydraulic system with storage, capacitance, and a strategy, and if you do not model it that way you are going to be wrong about drought.
Most physics undergraduates know Chen Ning Yang as a Nobel laureate and the Y in Yang-Mills. Building him a chronicle made me see something the textbooks gloss over: the most consequential single fact about his life is who his father was, and what that father had set up for him before he was born.
A 1957 Nobel prize cheque, a father who was the first Chinese PhD in number theory, three different monetary regimes, and seventy years of compounding, so how do you put a number on Chen Ning Yang’s family wealth in 2026 without making it up?
A new paper looked at 739 science Nobel laureates from 1901 to 2023, and the headline number that came out is brutal, at the current rate of progress it would take roughly 600 years before a kid born into a poor country has the same shot at a Nobel as a kid born into a rich one.
A new paper looked at 739 science Nobel laureates from 1901 to 2023, and the headline number that came out is brutal, at the current rate of progress it would take roughly 600 years before a kid born into a poor country has the same shot at a Nobel as a kid born into a rich one.
You can study fluid mechanics in five different countries before you turn 30, work on petroleum reservoirs and tectonophysics and planetary ice on the same week, and somehow end up at a Centennial Chair in Geophysics. Marc Hesse did exactly that, and the through-line is more interesting than any of the individual stops.
AI benchmarks are now appearing faster than any researcher can evaluate them, so I built a radar that makes discovery daily, transparent, and auditable.
When you join a lab, you do not just get a research direction. You inherit a 30-year codebase that is currently running inside the U.S. National Water Model and was on the critical path forecasting Hurricane Harvey. That is what working with Zong-Liang Yang at the Jackson School of Geosciences actually looks like.
You can study fluid mechanics in five different countries before you turn 30, work on petroleum reservoirs and tectonophysics and planetary ice on the same week, and somehow end up at a Centennial Chair in Geophysics. Marc Hesse did exactly that, and the through-line is more interesting than any of the individual stops.
If you ask most people where trees in California get their water in a drought, they will say “the soil.” It turns out a huge fraction of it comes from cracks in the bedrock underneath the soil, and Daniella Rempe is the person who put numbers on it.
Most land surface models treat a tree like a passive straw. Water comes in at the roots, water leaves at the leaves, end of story. Ashley Matheny’s research basically says no, a tree is an active hydraulic system with storage, capacitance, and a strategy, and if you do not model it that way you are going to be wrong about drought.
In a field where everyone gets pulled toward the next hot thing, Juan Santiago joined Stanford Mechanical Engineering in 1998 and has been there ever since, building one of the most consequential microfluidics labs on the planet. Long-term focus is its own competitive advantage.
Some books leave behind a few ideas. The Mom Test gave me a method I continue to use: do not ask whether someone likes your idea. Ask what they have already done, how often the problem occurs, what it has cost them, and whether they will commit to a next step.
When someone publicly told Steve Jobs that he did not understand technology, Jobs paused, conceded part of the criticism, and asked a more consequential question: what will the customer ultimately gain?
The story goes like this: I’ve been pondering a question lately—given how insanely advanced technology is today, why do we still have to spend so much time dressing up and managing our personal image?
Does building a benchmark count as research, or is it “crowdfunding a paper”? Does it create public value or consume public resources? Can it build lasting capabilities, or is it useful only for a startup team trying to show investors its potential?
The most dangerous failure mode of an AI science benchmark is not that it is too hard, it is that it quietly becomes either a coding trick or a guessing game.
When someone publicly told Steve Jobs that he did not understand technology, Jobs paused, conceded part of the criticism, and asked a more consequential question: what will the customer ultimately gain?
Does building a benchmark count as research, or is it “crowdfunding a paper”? Does it create public value or consume public resources? Can it build lasting capabilities, or is it useful only for a startup team trying to show investors its potential?
A new paper looked at 739 science Nobel laureates from 1901 to 2023, and the headline number that came out is brutal, at the current rate of progress it would take roughly 600 years before a kid born into a poor country has the same shot at a Nobel as a kid born into a rich one.
A 1957 Nobel prize cheque, a father who was the first Chinese PhD in number theory, three different monetary regimes, and seventy years of compounding, so how do you put a number on Chen Ning Yang’s family wealth in 2026 without making it up?
Does building a benchmark count as research, or is it “crowdfunding a paper”? Does it create public value or consume public resources? Can it build lasting capabilities, or is it useful only for a startup team trying to show investors its potential?
The most dangerous failure mode of an AI science benchmark is not that it is too hard, it is that it quietly becomes either a coding trick or a guessing game.
A 1957 Nobel prize cheque, a father who was the first Chinese PhD in number theory, three different monetary regimes, and seventy years of compounding, so how do you put a number on Chen Ning Yang’s family wealth in 2026 without making it up?
A new paper looked at 739 science Nobel laureates from 1901 to 2023, and the headline number that came out is brutal, at the current rate of progress it would take roughly 600 years before a kid born into a poor country has the same shot at a Nobel as a kid born into a rich one.
I was in the middle of setting up a second Cloudflare backup, verifying one dataset and configuring another, when the AI agent helping me flagged something unrelated: while listing what had access to my GitHub account, one authorization stood out as unusually broad. That single flag turned into an hour of reviewing GitHub’s installed-apps list, and it was worth every minute.
A receipt in Singapore showed S$5.50, while a U.S. credit-card account displayed only US$4.27. Another purchase of about S$48 appeared as roughly US$38. A bank-card transit ride also failed to appear immediately as pending.
A 1957 Nobel prize cheque, a father who was the first Chinese PhD in number theory, three different monetary regimes, and seventy years of compounding, so how do you put a number on Chen Ning Yang’s family wealth in 2026 without making it up?
In a field where everyone gets pulled toward the next hot thing, Juan Santiago joined Stanford Mechanical Engineering in 1998 and has been there ever since, building one of the most consequential microfluidics labs on the planet. Long-term focus is its own competitive advantage.
Some books leave behind a few ideas. The Mom Test gave me a method I continue to use: do not ask whether someone likes your idea. Ask what they have already done, how often the problem occurs, what it has cost them, and whether they will commit to a next step.
When someone publicly told Steve Jobs that he did not understand technology, Jobs paused, conceded part of the criticism, and asked a more consequential question: what will the customer ultimately gain?
Some books leave behind a few ideas. The Mom Test gave me a method I continue to use: do not ask whether someone likes your idea. Ask what they have already done, how often the problem occurs, what it has cost them, and whether they will commit to a next step.
I spent the last couple of days checking a tempting claim: that Microsoft Flight Simulator is secretly the foundation for a broader Earth digital twin story.
Some books leave behind a few ideas. The Mom Test gave me a method I continue to use: do not ask whether someone likes your idea. Ask what they have already done, how often the problem occurs, what it has cost them, and whether they will commit to a next step.
The story goes like this: I’ve been pondering a question lately—given how insanely advanced technology is today, why do we still have to spend so much time dressing up and managing our personal image?
I ran a health check on my Claude Code setup this week and found 174 custom skills, 124 of which I had never invoked once. They were not failures. Most of them were scaffolding I built for a model that needed it, and then kept long after the model stopped needing it.
Most physics undergraduates know Chen Ning Yang as a Nobel laureate and the Y in Yang-Mills. Building him a chronicle made me see something the textbooks gloss over: the most consequential single fact about his life is who his father was, and what that father had set up for him before he was born.
Most physics undergraduates know Chen Ning Yang as a Nobel laureate and the Y in Yang-Mills. Building him a chronicle made me see something the textbooks gloss over: the most consequential single fact about his life is who his father was, and what that father had set up for him before he was born.
When you join a lab, you do not just get a research direction. You inherit a 30-year codebase that is currently running inside the U.S. National Water Model and was on the critical path forecasting Hurricane Harvey. That is what working with Zong-Liang Yang at the Jackson School of Geosciences actually looks like.
You can study fluid mechanics in five different countries before you turn 30, work on petroleum reservoirs and tectonophysics and planetary ice on the same week, and somehow end up at a Centennial Chair in Geophysics. Marc Hesse did exactly that, and the through-line is more interesting than any of the individual stops.
The same way text foundation models ate NLP and image models ate computer vision, someone is going to build the foundation model that eats spatial reasoning. Gengchen Mai is one of the people taking that bet seriously, and his SEAI Lab at UT Austin is one of the places it is being built.
Most academic climate scientists will tell you they care about policy and then publish a paper that no policymaker is ever going to read. Geeta Persad spent four years working at the Union of Concerned Scientists translating climate models for water managers, and she came back to academia knowing exactly what the gap looks like.
If you ask most people where trees in California get their water in a drought, they will say “the soil.” It turns out a huge fraction of it comes from cracks in the bedrock underneath the soil, and Daniella Rempe is the person who put numbers on it.
Most land surface models treat a tree like a passive straw. Water comes in at the roots, water leaves at the leaves, end of story. Ashley Matheny’s research basically says no, a tree is an active hydraulic system with storage, capacitance, and a strategy, and if you do not model it that way you are going to be wrong about drought.
A 1957 Nobel prize cheque, a father who was the first Chinese PhD in number theory, three different monetary regimes, and seventy years of compounding, so how do you put a number on Chen Ning Yang’s family wealth in 2026 without making it up?
A new paper looked at 739 science Nobel laureates from 1901 to 2023, and the headline number that came out is brutal, at the current rate of progress it would take roughly 600 years before a kid born into a poor country has the same shot at a Nobel as a kid born into a rich one.
Most enterprise security companies show up, ride one trend, and disappear in the next infrastructure cycle. Sean Xiang has been building Bloombase since January 2012, and the company has somehow been on the right side of every major infrastructure shift since, including the current AI accelerator era. That is not luck. That is a thesis.
Most VCs and accelerators talk about supporting founders. Kehan Dong specifically supports the kind of founder who started building at 16, when nobody told them they were allowed to, and it turns out that population is dramatically underserved.
I ended up in the wrong NEXUS line at Vancouver International Airport. By the rules, the mistake was mine. By design, it was an almost predictable wrong turn.
Beyond the wayfinding problem that led me into the wrong NEXUS line, my connection at Vancouver International Airport left me with several observations unrelated to signs. I noticed an older-looking mix of people, a departures area that offered almost nowhere to work, and a visible contrast between people in Vancouver and Texas. This post records those observations. The full account of the NEXUS incident is in How I “Reasonably” Ended Up in the Wrong NEXUS Line at YVR.
A 1957 Nobel prize cheque, a father who was the first Chinese PhD in number theory, three different monetary regimes, and seventy years of compounding, so how do you put a number on Chen Ning Yang’s family wealth in 2026 without making it up?
Most physics undergraduates know Chen Ning Yang as a Nobel laureate and the Y in Yang-Mills. Building him a chronicle made me see something the textbooks gloss over: the most consequential single fact about his life is who his father was, and what that father had set up for him before he was born.
Most physics undergraduates know Chen Ning Yang as a Nobel laureate and the Y in Yang-Mills. Building him a chronicle made me see something the textbooks gloss over: the most consequential single fact about his life is who his father was, and what that father had set up for him before he was born.
Today I had an interesting experience collaborating with Claude Code to completely overhaul my personal academic website. As a PhD student in Geological and Earth Sciences at UT Austin, I needed to update my GitHub Pages site with real professional information instead of the placeholder content that had been sitting there.
Most academic climate scientists will tell you they care about policy and then publish a paper that no policymaker is ever going to read. Geeta Persad spent four years working at the Union of Concerned Scientists translating climate models for water managers, and she came back to academia knowing exactly what the gap looks like.
I asked Claude Code a narrow question: can I protect this machine from Codex accidentally deleting files forever, just by aliasing rm to trash? The honest answer turned out to be no, for a reason that is not obvious until you actually test it, and the fix ended up being a five-layer setup rather than a one-liner.
Parameterizing a large Fortran climate model by hand is slow, error-prone, and hard to validate. Noah-Agent asks whether a team of specialized AI agents can do it instead.
The Tmux Orchestrator enables Claude agents to work autonomously, schedule their own check-ins, and coordinate across multiple projects without human intervention - a project I explored and learned a lot from.
If I reopened the 2026 folder in 2030, I would check one thing first: did the work completed with AI change a real problem and leave evidence that others could verify and build upon?
I am deeply honored to join my colleagues in contributing to the newly published paper, “On the Ethics of Generative GeoAI: Explainability, Bias, Hallucination, Accountability, Privacy, and Trust,” specifically focusing on the section regarding GeoAI Trust (Section 8).
Earlier today I published a piece called “Four Ego Mistakes I Made as a 22-Year-Old Founder.” Then I ran it through Gemini 2.5 Pro as an independent reviewer. Gemini’s verdict was that the essay is itself an ego move. I think Gemini is mostly right.
Call it a (10^5) gap if you like, once you put semantic entropy and effective training samples on the board, the difference between internet-scale text and embodied robotics data stops sounding like rhetorical inflation and starts sounding almost conservative. You just have to separate raw physics bits from semantics a learner can actually use.
Ask which campus actually sits on the best multimodal feedstock for GPT-4V-class perception, Sora-class video, Gemini-scale bundles, and Meta Emu-style image stacks, and the short answer is almost vulgar in how cleanly it splits three big piles. Meta still pulls ahead by a chasm on stills, ByteDance owns the high-velocity short-video river that is really motion plus audio, and X ships the smallest absolute media volume yet the weirdest leverage on tight text-image coupling and live-event semantics.
Top physics researchers aren’t blind to what AI is doing in the application layer. They’re locked by their own evaluation system and can’t afford to look.
A PhD is hard. A PhD in 2026 — with the field moving faster than your committee can read — is a different kind of hard. AI PhD Survival Guide is a handbook for surviving and finishing an AI or ML PhD without burning out and without falling behind.
Virtual cell models powered by neuromorphic computing and gene language models represent one of the most capital-intensive and scientifically ambitious convergences in biotech AI. If you’re evaluating this space as a VC intern, you need to understand three core components: what these systems actually do, why the market is moving now, and where the investable opportunities lie.
Research, stock trading, and startups all share a common pattern: success comes from combining a defensible core competency with the ability to ride trending waves. You don’t need exhaustive preparation anymore. You need methodology and the ability to produce content when it matters. When the right moment arrives, you strike.
When Large Language Models (LLMs) hallucinate, we often treat it as an engineering bug to be fixed. But what if hallucinations are not a flaw, but a mathematical inevitability? A recent interdisciplinary discussion revealed a profound connection between the Gibbs phenomenon in Fourier analysis and the fundamental limitations of neural networks.
How photographing a black hole and training GPT-4 are fundamentally the same process: extracting coherent structure from impossibly sparse frequency-domain measurements.
The promise of AI-automated science is intoxicating: imagine machines that can generate hypotheses, design experiments, and publish papers while we sleep.
Every knowledge worker is now competing with an LLM for some part of their job. AI Survival Guide is a handbook for figuring out which parts, what to do about it, and how to come out the other side better at your craft instead of replaced by it.
Sometimes a piece of old science fiction stays in your head not because of the gadgets, but because it got the emotional structure of the future right.
Every generation has its own way of managing work: paper notebooks, SaaS task managers, and now programmable agentic workflows powered by tools like OpenClaw heartbeat.
Lay out every hyped multiAgent product on a table in front of Steve Jobs and he would probably squint, frown, and ask one question, why on earth are you showing the user any of this.
To be totally honest with you, you don’t need to understand the underlying architecture of large language models to get your name on a top-tier AI paper right now, you just need to be a true expert in your own field.
If you’re serious about understanding LLMs and AI engineering, Simon Willison’s Newsletter is one of the best resources out there. With over 38,000 subscribers, it provides detailed analysis on AI, LLMs, web engineering, open source, data science, and Python.
Parameterizing a large Fortran climate model by hand is slow, error-prone, and hard to validate. Noah-Agent asks whether a team of specialized AI agents can do it instead.
A hand-controlled 3D visualization of your AI conversation history - fly through ChatGPT conversations and explore artificial intelligence concepts. Try Live Demo
Most crypto dashboards either drown you in numbers or hide the signal behind a paywall. Crypto Dashboard is my attempt at a clean, AI-augmented view of the market that runs entirely in your browser. Try Live Demo
AlphaEarthHack is the project our team built for the UT Austin Geoscience Hackathon. The goal: see how far we could push AI on Earth system data inside a single weekend. Try Live Demo
The Tmux Orchestrator enables Claude agents to work autonomously, schedule their own check-ins, and coordinate across multiple projects without human intervention - a project I explored and learned a lot from.
Yuxuan and I have been discussing AI agent ideas for a while. Yesterday, we finally decided: we’re building Atomize, a task-breaking agent system evolved from Goblin Tools.
Decades of Earth-system modeling judgment live in PDFs, mailing lists, and senior researchers’ heads, and none of it is loadable by an AI coding agent. earth-space-ai.org is an attempt to fix that.
Earth system models are some of the most complex scientific software ever written, and they are also some of the worst-documented for newcomers. I have been building a series of “skill packages” — structured, progressive-disclosure knowledge bundles — for the major Earth system and land surface models, designed to be used by both new graduate students and AI coding agents.
Port Aransas South Jetty published an Institute Insights feature on May 28, 2026 about how our University of Texas team is using satellite remote sensing and AI to monitor Texas coastal water quality.
Today I had an interesting experience collaborating with Claude Code to completely overhaul my personal academic website. As a PhD student in Geological and Earth Sciences at UT Austin, I needed to update my GitHub Pages site with real professional information instead of the placeholder content that had been sitting there.
The promise of AI-automated science is intoxicating: imagine machines that can generate hypotheses, design experiments, and publish papers while we sleep.
Call it a (10^5) gap if you like, once you put semantic entropy and effective training samples on the board, the difference between internet-scale text and embodied robotics data stops sounding like rhetorical inflation and starts sounding almost conservative. You just have to separate raw physics bits from semantics a learner can actually use.
Exchanging money for time is a privilege I rarely indulge in, but a surprise membership benefit that cleared airport security in ten minutes changed my perspective on friction and market regulation. While a Clear Plus membership normally costs over a hundred dollars annually, obtaining it for free through an Uber membership allowed me to experience a level of efficiency that money can’t always buy—at least not without a well-regulated system behind it.
I ended up in the wrong NEXUS line at Vancouver International Airport. By the rules, the mistake was mine. By design, it was an almost predictable wrong turn.
Beyond the wayfinding problem that led me into the wrong NEXUS line, my connection at Vancouver International Airport left me with several observations unrelated to signs. I noticed an older-looking mix of people, a departures area that offered almost nowhere to work, and a visible contrast between people in Vancouver and Texas. This post records those observations. The full account of the NEXUS incident is in How I “Reasonably” Ended Up in the Wrong NEXUS Line at YVR.
Every indie developer who has ever burned through a free API tier knows the feeling: you build something cool, and then your OPENAI_API_KEY runs out at the worst possible moment. hao-tokens is a curated list of the legitimate ways to get free or low-cost LLM tokens so you can keep building.
Every indie developer who has ever burned through a free API tier knows the feeling: you build something cool, and then your OPENAI_API_KEY runs out at the worst possible moment. hao-tokens is a curated list of the legitimate ways to get free or low-cost LLM tokens so you can keep building.
The thing that almost stranded me on this international trip was not a typhoon, but several unrelated systems deciding at the same time that they did not trust me.
NASA’s Future Investigators in NASA Earth and Space Science and Technology (FINESST) is one of the most underused fellowships among US graduate students. Most PhD students have never heard of it, and the ones who have often miss the deadline because the proposal expectations aren’t obvious from the call alone. This repo is a curated guide of links, tips, and examples to help you write a competitive FINESST proposal.
The thing that almost stranded me on this international trip was not a typhoon, but several unrelated systems deciding at the same time that they did not trust me.
Today I had an interesting experience collaborating with Claude Code to completely overhaul my personal academic website. As a PhD student in Geological and Earth Sciences at UT Austin, I needed to update my GitHub Pages site with real professional information instead of the placeholder content that had been sitting there.
The Tmux Orchestrator enables Claude agents to work autonomously, schedule their own check-ins, and coordinate across multiple projects without human intervention - a project I explored and learned a lot from.
If you ask most people where trees in California get their water in a drought, they will say “the soil.” It turns out a huge fraction of it comes from cracks in the bedrock underneath the soil, and Daniella Rempe is the person who put numbers on it.
Most of biology is averages. You measure a million cells, you get a mean. Eric Greene’s lab figured out how to actually watch one DNA molecule at a time, repair itself, in real time, and that changes what kind of questions biology can ask.
Virtual cell models powered by neuromorphic computing and gene language models represent one of the most capital-intensive and scientifically ambitious convergences in biotech AI. If you’re evaluating this space as a VC intern, you need to understand three core components: what these systems actually do, why the market is moving now, and where the investable opportunities lie.
Most crypto dashboards either drown you in numbers or hide the signal behind a paywall. Crypto Dashboard is my attempt at a clean, AI-augmented view of the market that runs entirely in your browser. Try Live Demo
Sometimes a piece of old science fiction stays in your head not because of the gadgets, but because it got the emotional structure of the future right.
Ask which campus actually sits on the best multimodal feedstock for GPT-4V-class perception, Sora-class video, Gemini-scale bundles, and Meta Emu-style image stacks, and the short answer is almost vulgar in how cleanly it splits three big piles. Meta still pulls ahead by a chasm on stills, ByteDance owns the high-velocity short-video river that is really motion plus audio, and X ships the smallest absolute media volume yet the weirdest leverage on tight text-image coupling and live-event semantics.
Most people think of summer vacation as time off. I started wondering whether that framing undersells it. Summer Calculator is a small web tool that estimates the full value of your summer — money, learning, relationships, health — not just the days you didn’t work. Try Live Demo
School rankings are a single number standing in for a multi-dimensional decision. School Evaluator is a small web tool that lets you score a school across the dimensions that actually shape your life there. Try Live Demo
Earth system models are some of the most complex scientific software ever written, and they are also some of the worst-documented for newcomers. I have been building a series of “skill packages” — structured, progressive-disclosure knowledge bundles — for the major Earth system and land surface models, designed to be used by both new graduate students and AI coding agents.
Top physics researchers aren’t blind to what AI is doing in the application layer. They’re locked by their own evaluation system and can’t afford to look.
Research, stock trading, and startups all share a common pattern: success comes from combining a defensible core competency with the ability to ride trending waves. You don’t need exhaustive preparation anymore. You need methodology and the ability to produce content when it matters. When the right moment arrives, you strike.
Every knowledge worker is now competing with an LLM for some part of their job. AI Survival Guide is a handbook for figuring out which parts, what to do about it, and how to come out the other side better at your craft instead of replaced by it.
Every generation has its own way of managing work: paper notebooks, SaaS task managers, and now programmable agentic workflows powered by tools like OpenClaw heartbeat.
To be totally honest with you, you don’t need to understand the underlying architecture of large language models to get your name on a top-tier AI paper right now, you just need to be a true expert in your own field.
In October 2023 I asked ChatGPT an over-engineered question: how do you fry rice so that every grain of rice ends up bonded to egg, with no bare rice grains and no isolated clumps of egg sitting off on their own? I saved that conversation as an HTML file, dropped it in my Downloads folder, and did not look at it again for almost three years. Last week I finally turned it into an actual open-source repo, and going back through the original conversation to build it was more interesting than I expected.
“这b人生过的值不值” — roughly, “was this damn life worth it?” — is a phrase that does a lot of emotional work on the Chinese internet. ZuoGuoHuaDiao (做过划掉) is a small web tool that takes the phrase seriously and tries to answer it with numbers. Try Live Demo
The US is full of small traps that nobody warns you about until after you’ve fallen into one. US Survival Guide is a handbook for Chinese students and newcomers on identifying risk early, knowing your rights, and building a financial defense before you need it. Read the Guide
Most physics undergraduates know Chen Ning Yang as a Nobel laureate and the Y in Yang-Mills. Building him a chronicle made me see something the textbooks gloss over: the most consequential single fact about his life is who his father was, and what that father had set up for him before he was born.
Every indie developer who has ever burned through a free API tier knows the feeling: you build something cool, and then your OPENAI_API_KEY runs out at the worst possible moment. hao-tokens is a curated list of the legitimate ways to get free or low-cost LLM tokens so you can keep building.
I asked Claude Code a narrow question: can I protect this machine from Codex accidentally deleting files forever, just by aliasing rm to trash? The honest answer turned out to be no, for a reason that is not obvious until you actually test it, and the fix ended up being a five-layer setup rather than a one-liner.
When you join a lab, you do not just get a research direction. You inherit a 30-year codebase that is currently running inside the U.S. National Water Model and was on the critical path forecasting Hurricane Harvey. That is what working with Zong-Liang Yang at the Jackson School of Geosciences actually looks like.
AlphaEarthHack is the project our team built for the UT Austin Geoscience Hackathon. The goal: see how far we could push AI on Earth system data inside a single weekend. Try Live Demo
Dr. Zong-Liang Yang’s Land Environment and Atmospheric Dynamics (LEAD) Group at UT-Austin employs satellite remote sensing, earth system modeling, and high-performance computing to advance understanding of Earth system sciences.
Most academic climate scientists will tell you they care about policy and then publish a paper that no policymaker is ever going to read. Geeta Persad spent four years working at the Union of Concerned Scientists translating climate models for water managers, and she came back to academia knowing exactly what the gap looks like.
Most academic climate scientists will tell you they care about policy and then publish a paper that no policymaker is ever going to read. Geeta Persad spent four years working at the Union of Concerned Scientists translating climate models for water managers, and she came back to academia knowing exactly what the gap looks like.
Decades of Earth-system modeling judgment live in PDFs, mailing lists, and senior researchers’ heads, and none of it is loadable by an AI coding agent. earth-space-ai.org is an attempt to fix that.
Earth system models are some of the most complex scientific software ever written, and they are also some of the worst-documented for newcomers. I have been building a series of “skill packages” — structured, progressive-disclosure knowledge bundles — for the major Earth system and land surface models, designed to be used by both new graduate students and AI coding agents.
Parameterizing a large Fortran climate model by hand is slow, error-prone, and hard to validate. Noah-Agent asks whether a team of specialized AI agents can do it instead.
The roar of cooling systems in the Texas Advanced Computing Center (TACC) isn’t just noise—it’s the power of supercomputers translating the overwhelming dimensionality of climate data into something students can finally see and understand.
Earth system models are some of the most complex scientific software ever written, and they are also some of the worst-documented for newcomers. I have been building a series of “skill packages” — structured, progressive-disclosure knowledge bundles — for the major Earth system and land surface models, designed to be used by both new graduate students and AI coding agents.
I asked Claude Code a narrow question: can I protect this machine from Codex accidentally deleting files forever, just by aliasing rm to trash? The honest answer turned out to be no, for a reason that is not obvious until you actually test it, and the fix ended up being a five-layer setup rather than a one-liner.
School rankings are a single number standing in for a multi-dimensional decision. School Evaluator is a small web tool that lets you score a school across the dimensions that actually shape your life there. Try Live Demo
A widely shared post describes a brainstorming meeting at a robotics startup in Boston. A slide said “No stupid questions.” A Chinese employee interpreted it as “Do not ask stupid questions,” while American colleagues explained it as “Ask freely; no question will be judged stupid.” A related post claims that “Say it again?” is neutral when someone is not heard, whereas “What did you say?” is hostile.
一张流传截图讲了这样一件事:一家波士顿机器人创业公司开头脑风暴会,幻灯片写着 “No stupid questions.” 一位中国员工把它理解为“不要问蠢问题”,美国同事却说它的意思是“什么都可以问,没有问题会被当成蠢问题”。另一组讨论又声称:没听清时说 “Say it again?” 很中性,而 “What did you say?” 很不友好。
People love saying that ten years to a billion-dollar valuation is the normal pace for a unicorn, neither fast nor slow. But once you actually crunch the compound numbers, you realize what hides behind that word “normal” is a beast that doubles in value every single year.
In my first post on this I described sending a patch through GitGitGadget and watching it land on the mailing list as v1. That post ended with the patch waiting for review. It has since merged. Now that I have seen the full lifecycle, from typo to master, here is what actually mattered.
A long time ago, I came across a book called Chase, Chance, and Creativity: The Lucky Art of Novelty(《追逐、机遇和创造力:新奇的幸运艺术》). I no longer remember everything in it, but its central idea stayed somewhere in the back of my mind: luck and creativity are not entirely random. Chance may arrive unexpectedly, but we can still choose how often we encounter it and whether we are ready to recognize it.
很久以前,我偶然看到一本书,叫 Chase, Chance, and Creativity: The Lucky Art of Novelty(《追逐、机遇和创造力:新奇的幸运艺术》)。我已经不记得书里的全部内容了,但它的核心想法一直留在我脑海中的某个角落:运气和创造力并不完全是随机的。机遇也许会意外到来,但我们仍然可以选择自己遇见它的频率,以及当它出现时,我们是否已经准备好认出它。
A receipt in Singapore showed S$5.50, while a U.S. credit-card account displayed only US$4.27. Another purchase of about S$48 appeared as roughly US$38. A bank-card transit ride also failed to appear immediately as pending.
If you ask most people where trees in California get their water in a drought, they will say “the soil.” It turns out a huge fraction of it comes from cracks in the bedrock underneath the soil, and Daniella Rempe is the person who put numbers on it.
The US is full of small traps that nobody warns you about until after you’ve fallen into one. US Survival Guide is a handbook for Chinese students and newcomers on identifying risk early, knowing your rights, and building a financial defense before you need it. Read the Guide
Most crypto dashboards either drown you in numbers or hide the signal behind a paywall. Crypto Dashboard is my attempt at a clean, AI-augmented view of the market that runs entirely in your browser. Try Live Demo
Most enterprise security companies show up, ride one trend, and disappear in the next infrastructure cycle. Sean Xiang has been building Bloombase since January 2012, and the company has somehow been on the right side of every major infrastructure shift since, including the current AI accelerator era. That is not luck. That is a thesis.
A widely shared post describes a brainstorming meeting at a robotics startup in Boston. A slide said “No stupid questions.” A Chinese employee interpreted it as “Do not ask stupid questions,” while American colleagues explained it as “Ask freely; no question will be judged stupid.” A related post claims that “Say it again?” is neutral when someone is not heard, whereas “What did you say?” is hostile.
一张流传截图讲了这样一件事:一家波士顿机器人创业公司开头脑风暴会,幻灯片写着 “No stupid questions.” 一位中国员工把它理解为“不要问蠢问题”,美国同事却说它的意思是“什么都可以问,没有问题会被当成蠢问题”。另一组讨论又声称:没听清时说 “Say it again?” 很中性,而 “What did you say?” 很不友好。
The silence surrounding the Alamo chapel in San Antonio belies the brutal, thirteen-day siege that transformed this former Spanish mission into the ultimate symbol of Texan independence. Standing before its weathered facade today, one can almost hear the echoes of a conflict that remains one of the most legendary chapters in American history.
Most crypto dashboards either drown you in numbers or hide the signal behind a paywall. Crypto Dashboard is my attempt at a clean, AI-augmented view of the market that runs entirely in your browser. Try Live Demo
If I reopened the 2026 folder in 2030, I would check one thing first: did the work completed with AI change a real problem and leave evidence that others could verify and build upon?
Every indie developer who has ever burned through a free API tier knows the feeling: you build something cool, and then your OPENAI_API_KEY runs out at the worst possible moment. hao-tokens is a curated list of the legitimate ways to get free or low-cost LLM tokens so you can keep building.
Earth system models are some of the most complex scientific software ever written, and they are also some of the worst-documented for newcomers. I have been building a series of “skill packages” — structured, progressive-disclosure knowledge bundles — for the major Earth system and land surface models, designed to be used by both new graduate students and AI coding agents.
Most VCs and accelerators talk about supporting founders. Kehan Dong specifically supports the kind of founder who started building at 16, when nobody told them they were allowed to, and it turns out that population is dramatically underserved.
When you join a lab, you do not just get a research direction. You inherit a 30-year codebase that is currently running inside the U.S. National Water Model and was on the critical path forecasting Hurricane Harvey. That is what working with Zong-Liang Yang at the Jackson School of Geosciences actually looks like.
NASA’s Future Investigators in NASA Earth and Space Science and Technology (FINESST) is one of the most underused fellowships among US graduate students. Most PhD students have never heard of it, and the ones who have often miss the deadline because the proposal expectations aren’t obvious from the call alone. This repo is a curated guide of links, tips, and examples to help you write a competitive FINESST proposal.
Dr. Zong-Liang Yang’s Land Environment and Atmospheric Dynamics (LEAD) Group at UT-Austin employs satellite remote sensing, earth system modeling, and high-performance computing to advance understanding of Earth system sciences.
AlphaEarthHack is the project our team built for the UT Austin Geoscience Hackathon. The goal: see how far we could push AI on Earth system data inside a single weekend. Try Live Demo
Call it a (10^5) gap if you like, once you put semantic entropy and effective training samples on the board, the difference between internet-scale text and embodied robotics data stops sounding like rhetorical inflation and starts sounding almost conservative. You just have to separate raw physics bits from semantics a learner can actually use.
Decades of Earth-system modeling judgment live in PDFs, mailing lists, and senior researchers’ heads, and none of it is loadable by an AI coding agent. earth-space-ai.org is an attempt to fix that.
Earth system models are some of the most complex scientific software ever written, and they are also some of the worst-documented for newcomers. I have been building a series of “skill packages” — structured, progressive-disclosure knowledge bundles — for the major Earth system and land surface models, designed to be used by both new graduate students and AI coding agents.
The roar of cooling systems in the Texas Advanced Computing Center (TACC) isn’t just noise—it’s the power of supercomputers translating the overwhelming dimensionality of climate data into something students can finally see and understand.
Most land surface models treat a tree like a passive straw. Water comes in at the roots, water leaves at the leaves, end of story. Ashley Matheny’s research basically says no, a tree is an active hydraulic system with storage, capacitance, and a strategy, and if you do not model it that way you are going to be wrong about drought.
School rankings are a single number standing in for a multi-dimensional decision. School Evaluator is a small web tool that lets you score a school across the dimensions that actually shape your life there. Try Live Demo
Earlier today I published a piece called “Four Ego Mistakes I Made as a 22-Year-Old Founder.” Then I ran it through Gemini 2.5 Pro as an independent reviewer. Gemini’s verdict was that the essay is itself an ego move. I think Gemini is mostly right.
Call it a (10^5) gap if you like, once you put semantic entropy and effective training samples on the board, the difference between internet-scale text and embodied robotics data stops sounding like rhetorical inflation and starts sounding almost conservative. You just have to separate raw physics bits from semantics a learner can actually use.
Most enterprise security companies show up, ride one trend, and disappear in the next infrastructure cycle. Sean Xiang has been building Bloombase since January 2012, and the company has somehow been on the right side of every major infrastructure shift since, including the current AI accelerator era. That is not luck. That is a thesis.
Most VCs and accelerators talk about supporting founders. Kehan Dong specifically supports the kind of founder who started building at 16, when nobody told them they were allowed to, and it turns out that population is dramatically underserved.
Research, stock trading, and startups all share a common pattern: success comes from combining a defensible core competency with the ability to ride trending waves. You don’t need exhaustive preparation anymore. You need methodology and the ability to produce content when it matters. When the right moment arrives, you strike.
Most crypto dashboards either drown you in numbers or hide the signal behind a paywall. Crypto Dashboard is my attempt at a clean, AI-augmented view of the market that runs entirely in your browser. Try Live Demo
I spent a whole evening with Gemini taking apart the Buy Borrow Die playbook that American billionaires run, expecting that with a little scaling down I could just copy the moves, and what I found instead was that almost every single move has an F-1 trapdoor underneath it, and the list of things I can actually do fits on one page.
The roar of cooling systems in the Texas Advanced Computing Center (TACC) isn’t just noise—it’s the power of supercomputers translating the overwhelming dimensionality of climate data into something students can finally see and understand.
I plugged a Western Digital external drive full of data into a MacBook Air, tried to copy a file onto it, and nothing happened. No error dialog, no progress bar, just a drive that would let me read everything and write nothing. My first instinct was that something was broken, or that I needed to fix permissions. Both were wrong, and chasing the wrong explanation almost led me to permanently downgrade the security of the whole laptop.
我把一块装满数据的西部数据(WD)移动硬盘插到 MacBook Air 上,想往里拷一个文件,结果什么都没发生。没有报错弹窗,没有进度条,就是一块能读出所有东西、却一个字节都写不进去的硬盘。我的第一反应是它坏了,或者是我得去修一下权限。这两个判断都是错的,而且顺着错误的解释找下去,差点让我把整台笔记本的安全性永久降级。
finance
Warren Buffett: The “Open Source” Leader Half a Century Before GitHub
巴菲特:比GitHub早了半个世纪的“开源”运动领袖
3 minute read
Published:
In an era driven by code, collaboration, and transparency, GitHub has become synonymous with the “open source” spirit. But if we turn our gaze to the world of finance, we find a pioneer of “open source” who predates the birth of GitHub by a full half-century. His name is Warren Buffett.
People love saying that ten years to a billion-dollar valuation is the normal pace for a unicorn, neither fast nor slow. But once you actually crunch the compound numbers, you realize what hides behind that word “normal” is a beast that doubles in value every single year.
The US is full of small traps that nobody warns you about until after you’ve fallen into one. US Survival Guide is a handbook for Chinese students and newcomers on identifying risk early, knowing your rights, and building a financial defense before you need it. Read the Guide
NASA’s Future Investigators in NASA Earth and Space Science and Technology (FINESST) is one of the most underused fellowships among US graduate students. Most PhD students have never heard of it, and the ones who have often miss the deadline because the proposal expectations aren’t obvious from the call alone. This repo is a curated guide of links, tips, and examples to help you write a competitive FINESST proposal.
Call it a (10^5) gap if you like, once you put semantic entropy and effective training samples on the board, the difference between internet-scale text and embodied robotics data stops sounding like rhetorical inflation and starts sounding almost conservative. You just have to separate raw physics bits from semantics a learner can actually use.
You can study fluid mechanics in five different countries before you turn 30, work on petroleum reservoirs and tectonophysics and planetary ice on the same week, and somehow end up at a Centennial Chair in Geophysics. Marc Hesse did exactly that, and the through-line is more interesting than any of the individual stops.
In October 2023 I asked ChatGPT an over-engineered question: how do you fry rice so that every grain of rice ends up bonded to egg, with no bare rice grains and no isolated clumps of egg sitting off on their own? I saved that conversation as an HTML file, dropped it in my Downloads folder, and did not look at it again for almost three years. Last week I finally turned it into an actual open-source repo, and going back through the original conversation to build it was more interesting than I expected.
I’ve been playing with mixed-language builds (Fortran calling into C++ and C via iso_c_binding) and wanted a demo that was more interesting than “add two numbers across languages.” So I built fortran-zip-bomb: a small program that generates a genuine ZIP bomb — a small archive that expands into a much larger file on decompression.
The same way text foundation models ate NLP and image models ate computer vision, someone is going to build the foundation model that eats spatial reasoning. Gengchen Mai is one of the people taking that bet seriously, and his SEAI Lab at UT Austin is one of the places it is being built.
Most enterprise security companies show up, ride one trend, and disappear in the next infrastructure cycle. Sean Xiang has been building Bloombase since January 2012, and the company has somehow been on the right side of every major infrastructure shift since, including the current AI accelerator era. That is not luck. That is a thesis.
Earlier today I published a piece called “Four Ego Mistakes I Made as a 22-Year-Old Founder.” Then I ran it through Gemini 2.5 Pro as an independent reviewer. Gemini’s verdict was that the essay is itself an ego move. I think Gemini is mostly right.
When Large Language Models (LLMs) hallucinate, we often treat it as an engineering bug to be fixed. But what if hallucinations are not a flaw, but a mathematical inevitability? A recent interdisciplinary discussion revealed a profound connection between the Gibbs phenomenon in Fourier analysis and the fundamental limitations of neural networks.
Every indie developer who has ever burned through a free API tier knows the feeling: you build something cool, and then your OPENAI_API_KEY runs out at the worst possible moment. hao-tokens is a curated list of the legitimate ways to get free or low-cost LLM tokens so you can keep building.
Securing up to $150,000 in research funding over three years can define a graduate career, and NASA’s FINESST program is the primary vehicle for that transformation. This guide distills the complex application process into actionable strategies for Earth and Space Science researchers seeking to join the next generation of Future Investigators.
If I reopened the 2026 folder in 2030, I would check one thing first: did the work completed with AI change a real problem and leave evidence that others could verify and build upon?
Sometimes a piece of old science fiction stays in your head not because of the gadgets, but because it got the emotional structure of the future right.
Every knowledge worker is now competing with an LLM for some part of their job. AI Survival Guide is a handbook for figuring out which parts, what to do about it, and how to come out the other side better at your craft instead of replaced by it.
Virtual cell models powered by neuromorphic computing and gene language models represent one of the most capital-intensive and scientifically ambitious convergences in biotech AI. If you’re evaluating this space as a VC intern, you need to understand three core components: what these systems actually do, why the market is moving now, and where the investable opportunities lie.
I am deeply honored to join my colleagues in contributing to the newly published paper, “On the Ethics of Generative GeoAI: Explainability, Bias, Hallucination, Accountability, Privacy, and Trust,” specifically focusing on the section regarding GeoAI Trust (Section 8).
The same way text foundation models ate NLP and image models ate computer vision, someone is going to build the foundation model that eats spatial reasoning. Gengchen Mai is one of the people taking that bet seriously, and his SEAI Lab at UT Austin is one of the places it is being built.
AlphaEarthHack is the project our team built for the UT Austin Geoscience Hackathon. The goal: see how far we could push AI on Earth system data inside a single weekend. Try Live Demo
You can study fluid mechanics in five different countries before you turn 30, work on petroleum reservoirs and tectonophysics and planetary ice on the same week, and somehow end up at a Centennial Chair in Geophysics. Marc Hesse did exactly that, and the through-line is more interesting than any of the individual stops.
In my first post on this I described sending a patch through GitGitGadget and watching it land on the mailing list as v1. That post ended with the patch waiting for review. It has since merged. Now that I have seen the full lifecycle, from typo to master, here is what actually mattered.
In my first post on this I described sending a patch through GitGitGadget and watching it land on the mailing list as v1. That post ended with the patch waiting for review. It has since merged. Now that I have seen the full lifecycle, from typo to master, here is what actually mattered.
对技术人来说,在一个高速增长的开源仓库里做出高质量 PR,往往比再发一篇泛泛而谈的 AI 观点帖更像真正有效的 inbound marketing。
Warren Buffett: The “Open Source” Leader Half a Century Before GitHub
巴菲特:比GitHub早了半个世纪的“开源”运动领袖
3 minute read
Published:
In an era driven by code, collaboration, and transparency, GitHub has become synonymous with the “open source” spirit. But if we turn our gaze to the world of finance, we find a pioneer of “open source” who predates the birth of GitHub by a full half-century. His name is Warren Buffett.
When gold gets too expensive relative to silver, you sell your gold and buy silver. When silver catches up, you swap back. This sounds like folk wisdom, but it’s one of the most time-tested strategies in precious metals.
Every indie developer who has ever burned through a free API tier knows the feeling: you build something cool, and then your OPENAI_API_KEY runs out at the worst possible moment. hao-tokens is a curated list of the legitimate ways to get free or low-cost LLM tokens so you can keep building.
NASA’s Future Investigators in NASA Earth and Space Science and Technology (FINESST) is one of the most underused fellowships among US graduate students. Most PhD students have never heard of it, and the ones who have often miss the deadline because the proposal expectations aren’t obvious from the call alone. This repo is a curated guide of links, tips, and examples to help you write a competitive FINESST proposal.
Securing up to $150,000 in research funding over three years can define a graduate career, and NASA’s FINESST program is the primary vehicle for that transformation. This guide distills the complex application process into actionable strategies for Earth and Space Science researchers seeking to join the next generation of Future Investigators.
A PhD is hard. A PhD in 2026 — with the field moving faster than your committee can read — is a different kind of hard. AI PhD Survival Guide is a handbook for surviving and finishing an AI or ML PhD without burning out and without falling behind.
School rankings are a single number standing in for a multi-dimensional decision. School Evaluator is a small web tool that lets you score a school across the dimensions that actually shape your life there. Try Live Demo
Dr. Zong-Liang Yang’s Land Environment and Atmospheric Dynamics (LEAD) Group at UT-Austin employs satellite remote sensing, earth system modeling, and high-performance computing to advance understanding of Earth system sciences.
AlphaEarthHack is the project our team built for the UT Austin Geoscience Hackathon. The goal: see how far we could push AI on Earth system data inside a single weekend. Try Live Demo
I plugged a Western Digital external drive full of data into a MacBook Air, tried to copy a file onto it, and nothing happened. No error dialog, no progress bar, just a drive that would let me read everything and write nothing. My first instinct was that something was broken, or that I needed to fix permissions. Both were wrong, and chasing the wrong explanation almost led me to permanently downgrade the security of the whole laptop.
我把一块装满数据的西部数据(WD)移动硬盘插到 MacBook Air 上,想往里拷一个文件,结果什么都没发生。没有报错弹窗,没有进度条,就是一块能读出所有东西、却一个字节都写不进去的硬盘。我的第一反应是它坏了,或者是我得去修一下权限。这两个判断都是错的,而且顺着错误的解释找下去,差点让我把整台笔记本的安全性永久降级。
Decades of Earth-system modeling judgment live in PDFs, mailing lists, and senior researchers’ heads, and none of it is loadable by an AI coding agent. earth-space-ai.org is an attempt to fix that.
A PhD system built on a 19th-century apprenticeship model is failing by nearly every empirical measure — ~40–50% attrition, depression rates six times the general population, and tenure-track placement below 15% in many fields — while venture capital has spent four decades perfecting bilateral contracts that manage exactly the risks PhD programs ignore: information asymmetry, moral hazard, hold-up, and misaligned incentives. The literature across economics, education policy, signaling theory, and AI research converges on a striking conclusion: the structural tools to fix the PhD already exist in VC contract design, but academia has never imported them. This research compendium maps the evidentiary landscape across six domains to ground the argument.
The silence surrounding the Alamo chapel in San Antonio belies the brutal, thirteen-day siege that transformed this former Spanish mission into the ultimate symbol of Texan independence. Standing before its weathered facade today, one can almost hear the echoes of a conflict that remains one of the most legendary chapters in American history.
I ended up in the wrong NEXUS line at Vancouver International Airport. By the rules, the mistake was mine. By design, it was an almost predictable wrong turn.
If you ask most people where trees in California get their water in a drought, they will say “the soil.” It turns out a huge fraction of it comes from cracks in the bedrock underneath the soil, and Daniella Rempe is the person who put numbers on it.
I spent a whole evening with Gemini taking apart the Buy Borrow Die playbook that American billionaires run, expecting that with a little scaling down I could just copy the moves, and what I found instead was that almost every single move has an F-1 trapdoor underneath it, and the list of things I can actually do fits on one page.
A long time ago, I came across a book called Chase, Chance, and Creativity: The Lucky Art of Novelty(《追逐、机遇和创造力:新奇的幸运艺术》). I no longer remember everything in it, but its central idea stayed somewhere in the back of my mind: luck and creativity are not entirely random. Chance may arrive unexpectedly, but we can still choose how often we encounter it and whether we are ready to recognize it.
很久以前,我偶然看到一本书,叫 Chase, Chance, and Creativity: The Lucky Art of Novelty(《追逐、机遇和创造力:新奇的幸运艺术》)。我已经不记得书里的全部内容了,但它的核心想法一直留在我脑海中的某个角落:运气和创造力并不完全是随机的。机遇也许会意外到来,但我们仍然可以选择自己遇见它的频率,以及当它出现时,我们是否已经准备好认出它。
Call it a (10^5) gap if you like, once you put semantic entropy and effective training samples on the board, the difference between internet-scale text and embodied robotics data stops sounding like rhetorical inflation and starts sounding almost conservative. You just have to separate raw physics bits from semantics a learner can actually use.
The promise of AI-automated science is intoxicating: imagine machines that can generate hypotheses, design experiments, and publish papers while we sleep.
Most enterprise security companies show up, ride one trend, and disappear in the next infrastructure cycle. Sean Xiang has been building Bloombase since January 2012, and the company has somehow been on the right side of every major infrastructure shift since, including the current AI accelerator era. That is not luck. That is a thesis.
Most VCs and accelerators talk about supporting founders. Kehan Dong specifically supports the kind of founder who started building at 16, when nobody told them they were allowed to, and it turns out that population is dramatically underserved.
A handcrafted website universe where every webpage, balloon, click, and line of code says “I love you” - designed exclusively for Momo. Visit Live Site
How photographing a black hole and training GPT-4 are fundamentally the same process: extracting coherent structure from impossibly sparse frequency-domain measurements.
I ended up in the wrong NEXUS line at Vancouver International Airport. By the rules, the mistake was mine. By design, it was an almost predictable wrong turn.
Beyond the wayfinding problem that led me into the wrong NEXUS line, my connection at Vancouver International Airport left me with several observations unrelated to signs. I noticed an older-looking mix of people, a departures area that offered almost nowhere to work, and a visible contrast between people in Vancouver and Texas. This post records those observations. The full account of the NEXUS incident is in How I “Reasonably” Ended Up in the Wrong NEXUS Line at YVR.
I spent a whole evening with Gemini taking apart the Buy Borrow Die playbook that American billionaires run, expecting that with a little scaling down I could just copy the moves, and what I found instead was that almost every single move has an F-1 trapdoor underneath it, and the list of things I can actually do fits on one page.
The US is full of small traps that nobody warns you about until after you’ve fallen into one. US Survival Guide is a handbook for Chinese students and newcomers on identifying risk early, knowing your rights, and building a financial defense before you need it. Read the Guide
From the vast datasets of Earth System Models to the specialized niches of high-performance computing, this space documents my journey as a PhD student at UT Austin pushing the boundaries of Geological and Earth Sciences. This website is more than just a portfolio—it’s a hub where data-driven climate science meets the practical challenges of modern research.
I spent a whole evening with Gemini taking apart the Buy Borrow Die playbook that American billionaires run, expecting that with a little scaling down I could just copy the moves, and what I found instead was that almost every single move has an F-1 trapdoor underneath it, and the list of things I can actually do fits on one page.
When gold gets too expensive relative to silver, you sell your gold and buy silver. When silver catches up, you swap back. This sounds like folk wisdom, but it’s one of the most time-tested strategies in precious metals.
“这b人生过的值不值” — roughly, “was this damn life worth it?” — is a phrase that does a lot of emotional work on the Chinese internet. ZuoGuoHuaDiao (做过划掉) is a small web tool that takes the phrase seriously and tries to answer it with numbers. Try Live Demo
Most people think of summer vacation as time off. I started wondering whether that framing undersells it. Summer Calculator is a small web tool that estimates the full value of your summer — money, learning, relationships, health — not just the days you didn’t work. Try Live Demo
A handcrafted website universe where every webpage, balloon, click, and line of code says “I love you” - designed exclusively for Momo. Visit Live Site
Lay out every hyped multiAgent product on a table in front of Steve Jobs and he would probably squint, frown, and ask one question, why on earth are you showing the user any of this.
Earth system models are some of the most complex scientific software ever written, and they are also some of the worst-documented for newcomers. I have been building a series of “skill packages” — structured, progressive-disclosure knowledge bundles — for the major Earth system and land surface models, designed to be used by both new graduate students and AI coding agents.
AlphaEarthHack is the project our team built for the UT Austin Geoscience Hackathon. The goal: see how far we could push AI on Earth system data inside a single weekend. Try Live Demo
The same way text foundation models ate NLP and image models ate computer vision, someone is going to build the foundation model that eats spatial reasoning. Gengchen Mai is one of the people taking that bet seriously, and his SEAI Lab at UT Austin is one of the places it is being built.
Lay out every hyped multiAgent product on a table in front of Steve Jobs and he would probably squint, frown, and ask one question, why on earth are you showing the user any of this.
Every knowledge worker is now competing with an LLM for some part of their job. AI Survival Guide is a handbook for figuring out which parts, what to do about it, and how to come out the other side better at your craft instead of replaced by it.
A widely shared post describes a brainstorming meeting at a robotics startup in Boston. A slide said “No stupid questions.” A Chinese employee interpreted it as “Do not ask stupid questions,” while American colleagues explained it as “Ask freely; no question will be judged stupid.” A related post claims that “Say it again?” is neutral when someone is not heard, whereas “What did you say?” is hostile.
一张流传截图讲了这样一件事:一家波士顿机器人创业公司开头脑风暴会,幻灯片写着 “No stupid questions.” 一位中国员工把它理解为“不要问蠢问题”,美国同事却说它的意思是“什么都可以问,没有问题会被当成蠢问题”。另一组讨论又声称:没听清时说 “Say it again?” 很中性,而 “What did you say?” 很不友好。
The US is full of small traps that nobody warns you about until after you’ve fallen into one. US Survival Guide is a handbook for Chinese students and newcomers on identifying risk early, knowing your rights, and building a financial defense before you need it. Read the Guide
TQQQ is the 3x-leveraged Nasdaq-100 ETF. It is also one of the most asymmetric instruments retail investors touch — the upside is real, the drawdowns are brutal, and the daily-rebalance math means buy-and-hold doesn’t behave the way most people assume. TQQQ ML Trend is an experiment in using machine learning to predict the trend regime, not the price.
“这b人生过的值不值” — roughly, “was this damn life worth it?” — is a phrase that does a lot of emotional work on the Chinese internet. ZuoGuoHuaDiao (做过划掉) is a small web tool that takes the phrase seriously and tries to answer it with numbers. Try Live Demo
Most people think of summer vacation as time off. I started wondering whether that framing undersells it. Summer Calculator is a small web tool that estimates the full value of your summer — money, learning, relationships, health — not just the days you didn’t work. Try Live Demo
School rankings are a single number standing in for a multi-dimensional decision. School Evaluator is a small web tool that lets you score a school across the dimensions that actually shape your life there. Try Live Demo
Sometimes a piece of old science fiction stays in your head not because of the gadgets, but because it got the emotional structure of the future right.
Call it a (10^5) gap if you like, once you put semantic entropy and effective training samples on the board, the difference between internet-scale text and embodied robotics data stops sounding like rhetorical inflation and starts sounding almost conservative. You just have to separate raw physics bits from semantics a learner can actually use.
Ask which campus actually sits on the best multimodal feedstock for GPT-4V-class perception, Sora-class video, Gemini-scale bundles, and Meta Emu-style image stacks, and the short answer is almost vulgar in how cleanly it splits three big piles. Meta still pulls ahead by a chasm on stills, ByteDance owns the high-velocity short-video river that is really motion plus audio, and X ships the smallest absolute media volume yet the weirdest leverage on tight text-image coupling and live-event semantics.
Earth system models are some of the most complex scientific software ever written, and they are also some of the worst-documented for newcomers. I have been building a series of “skill packages” — structured, progressive-disclosure knowledge bundles — for the major Earth system and land surface models, designed to be used by both new graduate students and AI coding agents.
A PhD is hard. A PhD in 2026 — with the field moving faster than your committee can read — is a different kind of hard. AI PhD Survival Guide is a handbook for surviving and finishing an AI or ML PhD without burning out and without falling behind.
Every indie developer who has ever burned through a free API tier knows the feeling: you build something cool, and then your OPENAI_API_KEY runs out at the worst possible moment. hao-tokens is a curated list of the legitimate ways to get free or low-cost LLM tokens so you can keep building.
When Large Language Models (LLMs) hallucinate, we often treat it as an engineering bug to be fixed. But what if hallucinations are not a flaw, but a mathematical inevitability? A recent interdisciplinary discussion revealed a profound connection between the Gibbs phenomenon in Fourier analysis and the fundamental limitations of neural networks.
How photographing a black hole and training GPT-4 are fundamentally the same process: extracting coherent structure from impossibly sparse frequency-domain measurements.
Every knowledge worker is now competing with an LLM for some part of their job. AI Survival Guide is a handbook for figuring out which parts, what to do about it, and how to come out the other side better at your craft instead of replaced by it.
Yuxuan and I have been discussing AI agent ideas for a while. Yesterday, we finally decided: we’re building Atomize, a task-breaking agent system evolved from Goblin Tools.
If you’re serious about understanding LLMs and AI engineering, Simon Willison’s Newsletter is one of the best resources out there. With over 38,000 subscribers, it provides detailed analysis on AI, LLMs, web engineering, open source, data science, and Python.
Most enterprise security companies show up, ride one trend, and disappear in the next infrastructure cycle. Sean Xiang has been building Bloombase since January 2012, and the company has somehow been on the right side of every major infrastructure shift since, including the current AI accelerator era. That is not luck. That is a thesis.
In a field where everyone gets pulled toward the next hot thing, Juan Santiago joined Stanford Mechanical Engineering in 1998 and has been there ever since, building one of the most consequential microfluidics labs on the planet. Long-term focus is its own competitive advantage.
A long time ago, I came across a book called Chase, Chance, and Creativity: The Lucky Art of Novelty(《追逐、机遇和创造力:新奇的幸运艺术》). I no longer remember everything in it, but its central idea stayed somewhere in the back of my mind: luck and creativity are not entirely random. Chance may arrive unexpectedly, but we can still choose how often we encounter it and whether we are ready to recognize it.
很久以前,我偶然看到一本书,叫 Chase, Chance, and Creativity: The Lucky Art of Novelty(《追逐、机遇和创造力:新奇的幸运艺术》)。我已经不记得书里的全部内容了,但它的核心想法一直留在我脑海中的某个角落:运气和创造力并不完全是随机的。机遇也许会意外到来,但我们仍然可以选择自己遇见它的频率,以及当它出现时,我们是否已经准备好认出它。
A PhD is hard. A PhD in 2026 — with the field moving faster than your committee can read — is a different kind of hard. AI PhD Survival Guide is a handbook for surviving and finishing an AI or ML PhD without burning out and without falling behind.
How photographing a black hole and training GPT-4 are fundamentally the same process: extracting coherent structure from impossibly sparse frequency-domain measurements.
TQQQ is the 3x-leveraged Nasdaq-100 ETF. It is also one of the most asymmetric instruments retail investors touch — the upside is real, the drawdowns are brutal, and the daily-rebalance math means buy-and-hold doesn’t behave the way most people assume. TQQQ ML Trend is an experiment in using machine learning to predict the trend regime, not the price.
AlphaEarthHack is the project our team built for the UT Austin Geoscience Hackathon. The goal: see how far we could push AI on Earth system data inside a single weekend. Try Live Demo
I plugged a Western Digital external drive full of data into a MacBook Air, tried to copy a file onto it, and nothing happened. No error dialog, no progress bar, just a drive that would let me read everything and write nothing. My first instinct was that something was broken, or that I needed to fix permissions. Both were wrong, and chasing the wrong explanation almost led me to permanently downgrade the security of the whole laptop.
我把一块装满数据的西部数据(WD)移动硬盘插到 MacBook Air 上,想往里拷一个文件,结果什么都没发生。没有报错弹窗,没有进度条,就是一块能读出所有东西、却一个字节都写不进去的硬盘。我的第一反应是它坏了,或者是我得去修一下权限。这两个判断都是错的,而且顺着错误的解释找下去,差点让我把整台笔记本的安全性永久降级。
Most crypto dashboards either drown you in numbers or hide the signal behind a paywall. Crypto Dashboard is my attempt at a clean, AI-augmented view of the market that runs entirely in your browser. Try Live Demo
When Large Language Models (LLMs) hallucinate, we often treat it as an engineering bug to be fixed. But what if hallucinations are not a flaw, but a mathematical inevitability? A recent interdisciplinary discussion revealed a profound connection between the Gibbs phenomenon in Fourier analysis and the fundamental limitations of neural networks.
In a field where everyone gets pulled toward the next hot thing, Juan Santiago joined Stanford Mechanical Engineering in 1998 and has been there ever since, building one of the most consequential microfluidics labs on the planet. Long-term focus is its own competitive advantage.
Port Aransas South Jetty published an Institute Insights feature on May 28, 2026 about how our University of Texas team is using satellite remote sensing and AI to monitor Texas coastal water quality.
When you join a lab, you do not just get a research direction. You inherit a 30-year codebase that is currently running inside the U.S. National Water Model and was on the critical path forecasting Hurricane Harvey. That is what working with Zong-Liang Yang at the Jackson School of Geosciences actually looks like.
Most VCs and accelerators talk about supporting founders. Kehan Dong specifically supports the kind of founder who started building at 16, when nobody told them they were allowed to, and it turns out that population is dramatically underserved.
Ask which campus actually sits on the best multimodal feedstock for GPT-4V-class perception, Sora-class video, Gemini-scale bundles, and Meta Emu-style image stacks, and the short answer is almost vulgar in how cleanly it splits three big piles. Meta still pulls ahead by a chasm on stills, ByteDance owns the high-velocity short-video river that is really motion plus audio, and X ships the smallest absolute media volume yet the weirdest leverage on tight text-image coupling and live-event semantics.
Most of biology is averages. You measure a million cells, you get a mean. Eric Greene’s lab figured out how to actually watch one DNA molecule at a time, repair itself, in real time, and that changes what kind of questions biology can ask.
Goal: Use a 4x3 grid to place every relevant person “by position, with a matching strategy,” then review it regularly to maximize resource use and manage risk.
To be totally honest with you, you don’t need to understand the underlying architecture of large language models to get your name on a top-tier AI paper right now, you just need to be a true expert in your own field.
In a field where everyone gets pulled toward the next hot thing, Juan Santiago joined Stanford Mechanical Engineering in 1998 and has been there ever since, building one of the most consequential microfluidics labs on the planet. Long-term focus is its own competitive advantage.
In October 2023 I asked ChatGPT an over-engineered question: how do you fry rice so that every grain of rice ends up bonded to egg, with no bare rice grains and no isolated clumps of egg sitting off on their own? I saved that conversation as an HTML file, dropped it in my Downloads folder, and did not look at it again for almost three years. Last week I finally turned it into an actual open-source repo, and going back through the original conversation to build it was more interesting than I expected.
Earth system models are some of the most complex scientific software ever written, and they are also some of the worst-documented for newcomers. I have been building a series of “skill packages” — structured, progressive-disclosure knowledge bundles — for the major Earth system and land surface models, designed to be used by both new graduate students and AI coding agents.
Lay out every hyped multiAgent product on a table in front of Steve Jobs and he would probably squint, frown, and ask one question, why on earth are you showing the user any of this.
Ask which campus actually sits on the best multimodal feedstock for GPT-4V-class perception, Sora-class video, Gemini-scale bundles, and Meta Emu-style image stacks, and the short answer is almost vulgar in how cleanly it splits three big piles. Meta still pulls ahead by a chasm on stills, ByteDance owns the high-velocity short-video river that is really motion plus audio, and X ships the smallest absolute media volume yet the weirdest leverage on tight text-image coupling and live-event semantics.
NASA’s Future Investigators in NASA Earth and Space Science and Technology (FINESST) is one of the most underused fellowships among US graduate students. Most PhD students have never heard of it, and the ones who have often miss the deadline because the proposal expectations aren’t obvious from the call alone. This repo is a curated guide of links, tips, and examples to help you write a competitive FINESST proposal.
Securing up to $150,000 in research funding over three years can define a graduate career, and NASA’s FINESST program is the primary vehicle for that transformation. This guide distills the complex application process into actionable strategies for Earth and Space Science researchers seeking to join the next generation of Future Investigators.
A student-built navigation homepage that consolidates all essential UT Austin links in one place, solving the frustration of navigating deep university website hierarchies. Visit ut01.github.io
Virtual cell models powered by neuromorphic computing and gene language models represent one of the most capital-intensive and scientifically ambitious convergences in biotech AI. If you’re evaluating this space as a VC intern, you need to understand three core components: what these systems actually do, why the market is moving now, and where the investable opportunities lie.
If you’re serious about understanding LLMs and AI engineering, Simon Willison’s Newsletter is one of the best resources out there. With over 38,000 subscribers, it provides detailed analysis on AI, LLMs, web engineering, open source, data science, and Python.
Earth system models are some of the most complex scientific software ever written, and they are also some of the worst-documented for newcomers. I have been building a series of “skill packages” — structured, progressive-disclosure knowledge bundles — for the major Earth system and land surface models, designed to be used by both new graduate students and AI coding agents.
Decades of Earth-system modeling judgment live in PDFs, mailing lists, and senior researchers’ heads, and none of it is loadable by an AI coding agent. earth-space-ai.org is an attempt to fix that.
In October 2023 I asked ChatGPT an over-engineered question: how do you fry rice so that every grain of rice ends up bonded to egg, with no bare rice grains and no isolated clumps of egg sitting off on their own? I saved that conversation as an HTML file, dropped it in my Downloads folder, and did not look at it again for almost three years. Last week I finally turned it into an actual open-source repo, and going back through the original conversation to build it was more interesting than I expected.
In my first post on this I described sending a patch through GitGitGadget and watching it land on the mailing list as v1. That post ended with the patch waiting for review. It has since merged. Now that I have seen the full lifecycle, from typo to master, here is what actually mattered.
Yuxuan and I have been discussing AI agent ideas for a while. Yesterday, we finally decided: we’re building Atomize, a task-breaking agent system evolved from Goblin Tools.
If you’re serious about understanding LLMs and AI engineering, Simon Willison’s Newsletter is one of the best resources out there. With over 38,000 subscribers, it provides detailed analysis on AI, LLMs, web engineering, open source, data science, and Python.
Every indie developer who has ever burned through a free API tier knows the feeling: you build something cool, and then your OPENAI_API_KEY runs out at the worst possible moment. hao-tokens is a curated list of the legitimate ways to get free or low-cost LLM tokens so you can keep building.
Every generation has its own way of managing work: paper notebooks, SaaS task managers, and now programmable agentic workflows powered by tools like OpenClaw heartbeat.
Warren Buffett: The “Open Source” Leader Half a Century Before GitHub
巴菲特:比GitHub早了半个世纪的“开源”运动领袖
3 minute read
Published:
In an era driven by code, collaboration, and transparency, GitHub has become synonymous with the “open source” spirit. But if we turn our gaze to the world of finance, we find a pioneer of “open source” who predates the birth of GitHub by a full half-century. His name is Warren Buffett.
When gold gets too expensive relative to silver, you sell your gold and buy silver. When silver catches up, you swap back. This sounds like folk wisdom, but it’s one of the most time-tested strategies in precious metals.
Earth system models are some of the most complex scientific software ever written, and they are also some of the worst-documented for newcomers. I have been building a series of “skill packages” — structured, progressive-disclosure knowledge bundles — for the major Earth system and land surface models, designed to be used by both new graduate students and AI coding agents.
In a field where everyone gets pulled toward the next hot thing, Juan Santiago joined Stanford Mechanical Engineering in 1998 and has been there ever since, building one of the most consequential microfluidics labs on the planet. Long-term focus is its own competitive advantage.
A receipt in Singapore showed S$5.50, while a U.S. credit-card account displayed only US$4.27. Another purchase of about S$48 appeared as roughly US$38. A bank-card transit ride also failed to appear immediately as pending.
A handcrafted website universe where every webpage, balloon, click, and line of code says “I love you” - designed exclusively for Momo. Visit Live Site
I spent a whole evening with Gemini taking apart the Buy Borrow Die playbook that American billionaires run, expecting that with a little scaling down I could just copy the moves, and what I found instead was that almost every single move has an F-1 trapdoor underneath it, and the list of things I can actually do fits on one page.
A PhD is hard. A PhD in 2026 — with the field moving faster than your committee can read — is a different kind of hard. AI PhD Survival Guide is a handbook for surviving and finishing an AI or ML PhD without burning out and without falling behind.
A PhD system built on a 19th-century apprenticeship model is failing by nearly every empirical measure — ~40–50% attrition, depression rates six times the general population, and tenure-track placement below 15% in many fields — while venture capital has spent four decades perfecting bilateral contracts that manage exactly the risks PhD programs ignore: information asymmetry, moral hazard, hold-up, and misaligned incentives. The literature across economics, education policy, signaling theory, and AI research converges on a striking conclusion: the structural tools to fix the PhD already exist in VC contract design, but academia has never imported them. This research compendium maps the evidentiary landscape across six domains to ground the argument.
NASA’s Future Investigators in NASA Earth and Space Science and Technology (FINESST) is one of the most underused fellowships among US graduate students. Most PhD students have never heard of it, and the ones who have often miss the deadline because the proposal expectations aren’t obvious from the call alone. This repo is a curated guide of links, tips, and examples to help you write a competitive FINESST proposal.
The promise of AI-automated science is intoxicating: imagine machines that can generate hypotheses, design experiments, and publish papers while we sleep.
In October 2023 I asked ChatGPT an over-engineered question: how do you fry rice so that every grain of rice ends up bonded to egg, with no bare rice grains and no isolated clumps of egg sitting off on their own? I saved that conversation as an HTML file, dropped it in my Downloads folder, and did not look at it again for almost three years. Last week I finally turned it into an actual open-source repo, and going back through the original conversation to build it was more interesting than I expected.
Top physics researchers aren’t blind to what AI is doing in the application layer. They’re locked by their own evaluation system and can’t afford to look.
How photographing a black hole and training GPT-4 are fundamentally the same process: extracting coherent structure from impossibly sparse frequency-domain measurements.
You can study fluid mechanics in five different countries before you turn 30, work on petroleum reservoirs and tectonophysics and planetary ice on the same week, and somehow end up at a Centennial Chair in Geophysics. Marc Hesse did exactly that, and the through-line is more interesting than any of the individual stops.
NASA’s Future Investigators in NASA Earth and Space Science and Technology (FINESST) is one of the most underused fellowships among US graduate students. Most PhD students have never heard of it, and the ones who have often miss the deadline because the proposal expectations aren’t obvious from the call alone. This repo is a curated guide of links, tips, and examples to help you write a competitive FINESST proposal.
Most land surface models treat a tree like a passive straw. Water comes in at the roots, water leaves at the leaves, end of story. Ashley Matheny’s research basically says no, a tree is an active hydraulic system with storage, capacitance, and a strategy, and if you do not model it that way you are going to be wrong about drought.
If you ask most people where trees in California get their water in a drought, they will say “the soil.” It turns out a huge fraction of it comes from cracks in the bedrock underneath the soil, and Daniella Rempe is the person who put numbers on it.
Most academic climate scientists will tell you they care about policy and then publish a paper that no policymaker is ever going to read. Geeta Persad spent four years working at the Union of Concerned Scientists translating climate models for water managers, and she came back to academia knowing exactly what the gap looks like.
Top physics researchers aren’t blind to what AI is doing in the application layer. They’re locked by their own evaluation system and can’t afford to look.
When gold gets too expensive relative to silver, you sell your gold and buy silver. When silver catches up, you swap back. This sounds like folk wisdom, but it’s one of the most time-tested strategies in precious metals.
A PhD system built on a 19th-century apprenticeship model is failing by nearly every empirical measure — ~40–50% attrition, depression rates six times the general population, and tenure-track placement below 15% in many fields — while venture capital has spent four decades perfecting bilateral contracts that manage exactly the risks PhD programs ignore: information asymmetry, moral hazard, hold-up, and misaligned incentives. The literature across economics, education policy, signaling theory, and AI research converges on a striking conclusion: the structural tools to fix the PhD already exist in VC contract design, but academia has never imported them. This research compendium maps the evidentiary landscape across six domains to ground the argument.
Parameterizing a large Fortran climate model by hand is slow, error-prone, and hard to validate. Noah-Agent asks whether a team of specialized AI agents can do it instead.
Exchanging money for time is a privilege I rarely indulge in, but a surprise membership benefit that cleared airport security in ten minutes changed my perspective on friction and market regulation. While a Clear Plus membership normally costs over a hundred dollars annually, obtaining it for free through an Uber membership allowed me to experience a level of efficiency that money can’t always buy—at least not without a well-regulated system behind it.
Lay out every hyped multiAgent product on a table in front of Steve Jobs and he would probably squint, frown, and ask one question, why on earth are you showing the user any of this.
Yuxuan and I have been discussing AI agent ideas for a while. Yesterday, we finally decided: we’re building Atomize, a task-breaking agent system evolved from Goblin Tools.
Goal: Use a 4x3 grid to place every relevant person “by position, with a matching strategy,” then review it regularly to maximize resource use and manage risk.
Every knowledge worker is now competing with an LLM for some part of their job. AI Survival Guide is a handbook for figuring out which parts, what to do about it, and how to come out the other side better at your craft instead of replaced by it.
Every generation has its own way of managing work: paper notebooks, SaaS task managers, and now programmable agentic workflows powered by tools like OpenClaw heartbeat.
Yuxuan and I have been discussing AI agent ideas for a while. Yesterday, we finally decided: we’re building Atomize, a task-breaking agent system evolved from Goblin Tools.
“这b人生过的值不值” — roughly, “was this damn life worth it?” — is a phrase that does a lot of emotional work on the Chinese internet. ZuoGuoHuaDiao (做过划掉) is a small web tool that takes the phrase seriously and tries to answer it with numbers. Try Live Demo
Most people think of summer vacation as time off. I started wondering whether that framing undersells it. Summer Calculator is a small web tool that estimates the full value of your summer — money, learning, relationships, health — not just the days you didn’t work. Try Live Demo
NASA’s Future Investigators in NASA Earth and Space Science and Technology (FINESST) is one of the most underused fellowships among US graduate students. Most PhD students have never heard of it, and the ones who have often miss the deadline because the proposal expectations aren’t obvious from the call alone. This repo is a curated guide of links, tips, and examples to help you write a competitive FINESST proposal.
I am deeply honored to join my colleagues in contributing to the newly published paper, “On the Ethics of Generative GeoAI: Explainability, Bias, Hallucination, Accountability, Privacy, and Trust,” specifically focusing on the section regarding GeoAI Trust (Section 8).
If you’re serious about understanding LLMs and AI engineering, Simon Willison’s Newsletter is one of the best resources out there. With over 38,000 subscribers, it provides detailed analysis on AI, LLMs, web engineering, open source, data science, and Python.
TQQQ is the 3x-leveraged Nasdaq-100 ETF. It is also one of the most asymmetric instruments retail investors touch — the upside is real, the drawdowns are brutal, and the daily-rebalance math means buy-and-hold doesn’t behave the way most people assume. TQQQ ML Trend is an experiment in using machine learning to predict the trend regime, not the price.
TQQQ is the 3x-leveraged Nasdaq-100 ETF. It is also one of the most asymmetric instruments retail investors touch — the upside is real, the drawdowns are brutal, and the daily-rebalance math means buy-and-hold doesn’t behave the way most people assume. TQQQ ML Trend is an experiment in using machine learning to predict the trend regime, not the price.
A hand-controlled 3D visualization of your AI conversation history - fly through ChatGPT conversations and explore artificial intelligence concepts. Try Live Demo
Most crypto dashboards either drown you in numbers or hide the signal behind a paywall. Crypto Dashboard is my attempt at a clean, AI-augmented view of the market that runs entirely in your browser. Try Live Demo
If I reopened the 2026 folder in 2030, I would check one thing first: did the work completed with AI change a real problem and leave evidence that others could verify and build upon?
The thing that almost stranded me on this international trip was not a typhoon, but several unrelated systems deciding at the same time that they did not trust me.
In my first post on this I described sending a patch through GitGitGadget and watching it land on the mailing list as v1. That post ended with the patch waiting for review. It has since merged. Now that I have seen the full lifecycle, from typo to master, here is what actually mattered.
Earlier today I published a piece called “Four Ego Mistakes I Made as a 22-Year-Old Founder.” Then I ran it through Gemini 2.5 Pro as an independent reviewer. Gemini’s verdict was that the essay is itself an ego move. I think Gemini is mostly right.
“这b人生过的值不值” — roughly, “was this damn life worth it?” — is a phrase that does a lot of emotional work on the Chinese internet. ZuoGuoHuaDiao (做过划掉) is a small web tool that takes the phrase seriously and tries to answer it with numbers. Try Live Demo
Goal: Use a 4x3 grid to place every relevant person “by position, with a matching strategy,” then review it regularly to maximize resource use and manage risk.
Port Aransas South Jetty published an Institute Insights feature on May 28, 2026 about how our University of Texas team is using satellite remote sensing and AI to monitor Texas coastal water quality.
I am deeply honored to join my colleagues in contributing to the newly published paper, “On the Ethics of Generative GeoAI: Explainability, Bias, Hallucination, Accountability, Privacy, and Trust,” specifically focusing on the section regarding GeoAI Trust (Section 8).
Top physics researchers aren’t blind to what AI is doing in the application layer. They’re locked by their own evaluation system and can’t afford to look.
A PhD is hard. A PhD in 2026 — with the field moving faster than your committee can read — is a different kind of hard. AI PhD Survival Guide is a handbook for surviving and finishing an AI or ML PhD without burning out and without falling behind.
Research, stock trading, and startups all share a common pattern: success comes from combining a defensible core competency with the ability to ride trending waves. You don’t need exhaustive preparation anymore. You need methodology and the ability to produce content when it matters. When the right moment arrives, you strike.
A PhD system built on a 19th-century apprenticeship model is failing by nearly every empirical measure — ~40–50% attrition, depression rates six times the general population, and tenure-track placement below 15% in many fields — while venture capital has spent four decades perfecting bilateral contracts that manage exactly the risks PhD programs ignore: information asymmetry, moral hazard, hold-up, and misaligned incentives. The literature across economics, education policy, signaling theory, and AI research converges on a striking conclusion: the structural tools to fix the PhD already exist in VC contract design, but academia has never imported them. This research compendium maps the evidentiary landscape across six domains to ground the argument.
To be totally honest with you, you don’t need to understand the underlying architecture of large language models to get your name on a top-tier AI paper right now, you just need to be a true expert in your own field.
Dr. Zong-Liang Yang’s Land Environment and Atmospheric Dynamics (LEAD) Group at UT-Austin employs satellite remote sensing, earth system modeling, and high-performance computing to advance understanding of Earth system sciences.
If you’re serious about understanding LLMs and AI engineering, Simon Willison’s Newsletter is one of the best resources out there. With over 38,000 subscribers, it provides detailed analysis on AI, LLMs, web engineering, open source, data science, and Python.
Securing up to $150,000 in research funding over three years can define a graduate career, and NASA’s FINESST program is the primary vehicle for that transformation. This guide distills the complex application process into actionable strategies for Earth and Space Science researchers seeking to join the next generation of Future Investigators.
Call it a (10^5) gap if you like, once you put semantic entropy and effective training samples on the board, the difference between internet-scale text and embodied robotics data stops sounding like rhetorical inflation and starts sounding almost conservative. You just have to separate raw physics bits from semantics a learner can actually use.
Lay out every hyped multiAgent product on a table in front of Steve Jobs and he would probably squint, frown, and ask one question, why on earth are you showing the user any of this.
I asked Claude Code a narrow question: can I protect this machine from Codex accidentally deleting files forever, just by aliasing rm to trash? The honest answer turned out to be no, for a reason that is not obvious until you actually test it, and the fix ended up being a five-layer setup rather than a one-liner.
School rankings are a single number standing in for a multi-dimensional decision. School Evaluator is a small web tool that lets you score a school across the dimensions that actually shape your life there. Try Live Demo
Most of biology is averages. You measure a million cells, you get a mean. Eric Greene’s lab figured out how to actually watch one DNA molecule at a time, repair itself, in real time, and that changes what kind of questions biology can ask.
The promise of AI-automated science is intoxicating: imagine machines that can generate hypotheses, design experiments, and publish papers while we sleep.
Most physics undergraduates know Chen Ning Yang as a Nobel laureate and the Y in Yang-Mills. Building him a chronicle made me see something the textbooks gloss over: the most consequential single fact about his life is who his father was, and what that father had set up for him before he was born.
Sometimes a piece of old science fiction stays in your head not because of the gadgets, but because it got the emotional structure of the future right.
The promise of AI-automated science is intoxicating: imagine machines that can generate hypotheses, design experiments, and publish papers while we sleep.
I’ve been playing with mixed-language builds (Fortran calling into C++ and C via iso_c_binding) and wanted a demo that was more interesting than “add two numbers across languages.” So I built fortran-zip-bomb: a small program that generates a genuine ZIP bomb — a small archive that expands into a much larger file on decompression.
Exchanging money for time is a privilege I rarely indulge in, but a surprise membership benefit that cleared airport security in ten minutes changed my perspective on friction and market regulation. While a Clear Plus membership normally costs over a hundred dollars annually, obtaining it for free through an Uber membership allowed me to experience a level of efficiency that money can’t always buy—at least not without a well-regulated system behind it.
I asked Claude Code a narrow question: can I protect this machine from Codex accidentally deleting files forever, just by aliasing rm to trash? The honest answer turned out to be no, for a reason that is not obvious until you actually test it, and the fix ended up being a five-layer setup rather than a one-liner.
In October 2023 I asked ChatGPT an over-engineered question: how do you fry rice so that every grain of rice ends up bonded to egg, with no bare rice grains and no isolated clumps of egg sitting off on their own? I saved that conversation as an HTML file, dropped it in my Downloads folder, and did not look at it again for almost three years. Last week I finally turned it into an actual open-source repo, and going back through the original conversation to build it was more interesting than I expected.
When gold gets too expensive relative to silver, you sell your gold and buy silver. When silver catches up, you swap back. This sounds like folk wisdom, but it’s one of the most time-tested strategies in precious metals.
Most of biology is averages. You measure a million cells, you get a mean. Eric Greene’s lab figured out how to actually watch one DNA molecule at a time, repair itself, in real time, and that changes what kind of questions biology can ask.
Earlier today I published a piece called “Four Ego Mistakes I Made as a 22-Year-Old Founder.” Then I ran it through Gemini 2.5 Pro as an independent reviewer. Gemini’s verdict was that the essay is itself an ego move. I think Gemini is mostly right.
Earth system models are some of the most complex scientific software ever written, and they are also some of the worst-documented for newcomers. I have been building a series of “skill packages” — structured, progressive-disclosure knowledge bundles — for the major Earth system and land surface models, designed to be used by both new graduate students and AI coding agents.
Decades of Earth-system modeling judgment live in PDFs, mailing lists, and senior researchers’ heads, and none of it is loadable by an AI coding agent. earth-space-ai.org is an attempt to fix that.
I ended up in the wrong NEXUS line at Vancouver International Airport. By the rules, the mistake was mine. By design, it was an almost predictable wrong turn.
Beyond the wayfinding problem that led me into the wrong NEXUS line, my connection at Vancouver International Airport left me with several observations unrelated to signs. I noticed an older-looking mix of people, a departures area that offered almost nowhere to work, and a visible contrast between people in Vancouver and Texas. This post records those observations. The full account of the NEXUS incident is in How I “Reasonably” Ended Up in the Wrong NEXUS Line at YVR.
The same way text foundation models ate NLP and image models ate computer vision, someone is going to build the foundation model that eats spatial reasoning. Gengchen Mai is one of the people taking that bet seriously, and his SEAI Lab at UT Austin is one of the places it is being built.
Earlier today I published a piece called “Four Ego Mistakes I Made as a 22-Year-Old Founder.” Then I ran it through Gemini 2.5 Pro as an independent reviewer. Gemini’s verdict was that the essay is itself an ego move. I think Gemini is mostly right.
People love saying that ten years to a billion-dollar valuation is the normal pace for a unicorn, neither fast nor slow. But once you actually crunch the compound numbers, you realize what hides behind that word “normal” is a beast that doubles in value every single year.
Lay out every hyped multiAgent product on a table in front of Steve Jobs and he would probably squint, frown, and ask one question, why on earth are you showing the user any of this.
Yuxuan and I have been discussing AI agent ideas for a while. Yesterday, we finally decided: we’re building Atomize, a task-breaking agent system evolved from Goblin Tools.
Lay out every hyped multiAgent product on a table in front of Steve Jobs and he would probably squint, frown, and ask one question, why on earth are you showing the user any of this.
Research, stock trading, and startups all share a common pattern: success comes from combining a defensible core competency with the ability to ride trending waves. You don’t need exhaustive preparation anymore. You need methodology and the ability to produce content when it matters. When the right moment arrives, you strike.
A student-built navigation homepage that consolidates all essential UT Austin links in one place, solving the frustration of navigating deep university website hierarchies. Visit ut01.github.io
Earth system models are some of the most complex scientific software ever written, and they are also some of the worst-documented for newcomers. I have been building a series of “skill packages” — structured, progressive-disclosure knowledge bundles — for the major Earth system and land surface models, designed to be used by both new graduate students and AI coding agents.
A PhD is hard. A PhD in 2026 — with the field moving faster than your committee can read — is a different kind of hard. AI PhD Survival Guide is a handbook for surviving and finishing an AI or ML PhD without burning out and without falling behind.
Every knowledge worker is now competing with an LLM for some part of their job. AI Survival Guide is a handbook for figuring out which parts, what to do about it, and how to come out the other side better at your craft instead of replaced by it.
The US is full of small traps that nobody warns you about until after you’ve fallen into one. US Survival Guide is a handbook for Chinese students and newcomers on identifying risk early, knowing your rights, and building a financial defense before you need it. Read the Guide
I’ve been playing with mixed-language builds (Fortran calling into C++ and C via iso_c_binding) and wanted a demo that was more interesting than “add two numbers across languages.” So I built fortran-zip-bomb: a small program that generates a genuine ZIP bomb — a small archive that expands into a much larger file on decompression.
The roar of cooling systems in the Texas Advanced Computing Center (TACC) isn’t just noise—it’s the power of supercomputers translating the overwhelming dimensionality of climate data into something students can finally see and understand.
The promise of AI-automated science is intoxicating: imagine machines that can generate hypotheses, design experiments, and publish papers while we sleep.
I spent a whole evening with Gemini taking apart the Buy Borrow Die playbook that American billionaires run, expecting that with a little scaling down I could just copy the moves, and what I found instead was that almost every single move has an F-1 trapdoor underneath it, and the list of things I can actually do fits on one page.
The silence surrounding the Alamo chapel in San Antonio belies the brutal, thirteen-day siege that transformed this former Spanish mission into the ultimate symbol of Texan independence. Standing before its weathered facade today, one can almost hear the echoes of a conflict that remains one of the most legendary chapters in American history.
Port Aransas South Jetty published an Institute Insights feature on May 28, 2026 about how our University of Texas team is using satellite remote sensing and AI to monitor Texas coastal water quality.
People love saying that ten years to a billion-dollar valuation is the normal pace for a unicorn, neither fast nor slow. But once you actually crunch the compound numbers, you realize what hides behind that word “normal” is a beast that doubles in value every single year.
Top physics researchers aren’t blind to what AI is doing in the application layer. They’re locked by their own evaluation system and can’t afford to look.
Sometimes a piece of old science fiction stays in your head not because of the gadgets, but because it got the emotional structure of the future right.
Every generation has its own way of managing work: paper notebooks, SaaS task managers, and now programmable agentic workflows powered by tools like OpenClaw heartbeat.
I spent a whole evening with Gemini taking apart the Buy Borrow Die playbook that American billionaires run, expecting that with a little scaling down I could just copy the moves, and what I found instead was that almost every single move has an F-1 trapdoor underneath it, and the list of things I can actually do fits on one page.
When gold gets too expensive relative to silver, you sell your gold and buy silver. When silver catches up, you swap back. This sounds like folk wisdom, but it’s one of the most time-tested strategies in precious metals.
A hand-controlled 3D visualization of your AI conversation history - fly through ChatGPT conversations and explore artificial intelligence concepts. Try Live Demo
Ask which campus actually sits on the best multimodal feedstock for GPT-4V-class perception, Sora-class video, Gemini-scale bundles, and Meta Emu-style image stacks, and the short answer is almost vulgar in how cleanly it splits three big piles. Meta still pulls ahead by a chasm on stills, ByteDance owns the high-velocity short-video river that is really motion plus audio, and X ships the smallest absolute media volume yet the weirdest leverage on tight text-image coupling and live-event semantics.
TQQQ is the 3x-leveraged Nasdaq-100 ETF. It is also one of the most asymmetric instruments retail investors touch — the upside is real, the drawdowns are brutal, and the daily-rebalance math means buy-and-hold doesn’t behave the way most people assume. TQQQ ML Trend is an experiment in using machine learning to predict the trend regime, not the price.
The Tmux Orchestrator enables Claude agents to work autonomously, schedule their own check-ins, and coordinate across multiple projects without human intervention - a project I explored and learned a lot from.
Every indie developer who has ever burned through a free API tier knows the feeling: you build something cool, and then your OPENAI_API_KEY runs out at the worst possible moment. hao-tokens is a curated list of the legitimate ways to get free or low-cost LLM tokens so you can keep building.
TQQQ is the 3x-leveraged Nasdaq-100 ETF. It is also one of the most asymmetric instruments retail investors touch — the upside is real, the drawdowns are brutal, and the daily-rebalance math means buy-and-hold doesn’t behave the way most people assume. TQQQ ML Trend is an experiment in using machine learning to predict the trend regime, not the price.
TQQQ is the 3x-leveraged Nasdaq-100 ETF. It is also one of the most asymmetric instruments retail investors touch — the upside is real, the drawdowns are brutal, and the daily-rebalance math means buy-and-hold doesn’t behave the way most people assume. TQQQ ML Trend is an experiment in using machine learning to predict the trend regime, not the price.
When gold gets too expensive relative to silver, you sell your gold and buy silver. When silver catches up, you swap back. This sounds like folk wisdom, but it’s one of the most time-tested strategies in precious metals.
Ask which campus actually sits on the best multimodal feedstock for GPT-4V-class perception, Sora-class video, Gemini-scale bundles, and Meta Emu-style image stacks, and the short answer is almost vulgar in how cleanly it splits three big piles. Meta still pulls ahead by a chasm on stills, ByteDance owns the high-velocity short-video river that is really motion plus audio, and X ships the smallest absolute media volume yet the weirdest leverage on tight text-image coupling and live-event semantics.
A receipt in Singapore showed S$5.50, while a U.S. credit-card account displayed only US$4.27. Another purchase of about S$48 appeared as roughly US$38. A bank-card transit ride also failed to appear immediately as pending.
The thing that almost stranded me on this international trip was not a typhoon, but several unrelated systems deciding at the same time that they did not trust me.
The silence surrounding the Alamo chapel in San Antonio belies the brutal, thirteen-day siege that transformed this former Spanish mission into the ultimate symbol of Texan independence. Standing before its weathered facade today, one can almost hear the echoes of a conflict that remains one of the most legendary chapters in American history.
Exchanging money for time is a privilege I rarely indulge in, but a surprise membership benefit that cleared airport security in ten minutes changed my perspective on friction and market regulation. While a Clear Plus membership normally costs over a hundred dollars annually, obtaining it for free through an Uber membership allowed me to experience a level of efficiency that money can’t always buy—at least not without a well-regulated system behind it.
I plugged a Western Digital external drive full of data into a MacBook Air, tried to copy a file onto it, and nothing happened. No error dialog, no progress bar, just a drive that would let me read everything and write nothing. My first instinct was that something was broken, or that I needed to fix permissions. Both were wrong, and chasing the wrong explanation almost led me to permanently downgrade the security of the whole laptop.
我把一块装满数据的西部数据(WD)移动硬盘插到 MacBook Air 上,想往里拷一个文件,结果什么都没发生。没有报错弹窗,没有进度条,就是一块能读出所有东西、却一个字节都写不进去的硬盘。我的第一反应是它坏了,或者是我得去修一下权限。这两个判断都是错的,而且顺着错误的解释找下去,差点让我把整台笔记本的安全性永久降级。
Ask which campus actually sits on the best multimodal feedstock for GPT-4V-class perception, Sora-class video, Gemini-scale bundles, and Meta Emu-style image stacks, and the short answer is almost vulgar in how cleanly it splits three big piles. Meta still pulls ahead by a chasm on stills, ByteDance owns the high-velocity short-video river that is really motion plus audio, and X ships the smallest absolute media volume yet the weirdest leverage on tight text-image coupling and live-event semantics.
Most crypto dashboards either drown you in numbers or hide the signal behind a paywall. Crypto Dashboard is my attempt at a clean, AI-augmented view of the market that runs entirely in your browser. Try Live Demo
School rankings are a single number standing in for a multi-dimensional decision. School Evaluator is a small web tool that lets you score a school across the dimensions that actually shape your life there. Try Live Demo
Exchanging money for time is a privilege I rarely indulge in, but a surprise membership benefit that cleared airport security in ten minutes changed my perspective on friction and market regulation. While a Clear Plus membership normally costs over a hundred dollars annually, obtaining it for free through an Uber membership allowed me to experience a level of efficiency that money can’t always buy—at least not without a well-regulated system behind it.
People love saying that ten years to a billion-dollar valuation is the normal pace for a unicorn, neither fast nor slow. But once you actually crunch the compound numbers, you realize what hides behind that word “normal” is a beast that doubles in value every single year.
The US is full of small traps that nobody warns you about until after you’ve fallen into one. US Survival Guide is a handbook for Chinese students and newcomers on identifying risk early, knowing your rights, and building a financial defense before you need it. Read the Guide
Port Aransas South Jetty published an Institute Insights feature on May 28, 2026 about how our University of Texas team is using satellite remote sensing and AI to monitor Texas coastal water quality.
AlphaEarthHack is the project our team built for the UT Austin Geoscience Hackathon. The goal: see how far we could push AI on Earth system data inside a single weekend. Try Live Demo
A student-built navigation homepage that consolidates all essential UT Austin links in one place, solving the frustration of navigating deep university website hierarchies. Visit ut01.github.io
Most people think of summer vacation as time off. I started wondering whether that framing undersells it. Summer Calculator is a small web tool that estimates the full value of your summer — money, learning, relationships, health — not just the days you didn’t work. Try Live Demo
People love saying that ten years to a billion-dollar valuation is the normal pace for a unicorn, neither fast nor slow. But once you actually crunch the compound numbers, you realize what hides behind that word “normal” is a beast that doubles in value every single year.
Most land surface models treat a tree like a passive straw. Water comes in at the roots, water leaves at the leaves, end of story. Ashley Matheny’s research basically says no, a tree is an active hydraulic system with storage, capacitance, and a strategy, and if you do not model it that way you are going to be wrong about drought.
Virtual cell models powered by neuromorphic computing and gene language models represent one of the most capital-intensive and scientifically ambitious convergences in biotech AI. If you’re evaluating this space as a VC intern, you need to understand three core components: what these systems actually do, why the market is moving now, and where the investable opportunities lie.
A PhD system built on a 19th-century apprenticeship model is failing by nearly every empirical measure — ~40–50% attrition, depression rates six times the general population, and tenure-track placement below 15% in many fields — while venture capital has spent four decades perfecting bilateral contracts that manage exactly the risks PhD programs ignore: information asymmetry, moral hazard, hold-up, and misaligned incentives. The literature across economics, education policy, signaling theory, and AI research converges on a striking conclusion: the structural tools to fix the PhD already exist in VC contract design, but academia has never imported them. This research compendium maps the evidentiary landscape across six domains to ground the argument.
Earth system models are some of the most complex scientific software ever written, and they are also some of the worst-documented for newcomers. I have been building a series of “skill packages” — structured, progressive-disclosure knowledge bundles — for the major Earth system and land surface models, designed to be used by both new graduate students and AI coding agents.
Virtual cell models powered by neuromorphic computing and gene language models represent one of the most capital-intensive and scientifically ambitious convergences in biotech AI. If you’re evaluating this space as a VC intern, you need to understand three core components: what these systems actually do, why the market is moving now, and where the investable opportunities lie.
Ask which campus actually sits on the best multimodal feedstock for GPT-4V-class perception, Sora-class video, Gemini-scale bundles, and Meta Emu-style image stacks, and the short answer is almost vulgar in how cleanly it splits three big piles. Meta still pulls ahead by a chasm on stills, ByteDance owns the high-velocity short-video river that is really motion plus audio, and X ships the smallest absolute media volume yet the weirdest leverage on tight text-image coupling and live-event semantics.
The roar of cooling systems in the Texas Advanced Computing Center (TACC) isn’t just noise—it’s the power of supercomputers translating the overwhelming dimensionality of climate data into something students can finally see and understand.
A hand-controlled 3D visualization of your AI conversation history - fly through ChatGPT conversations and explore artificial intelligence concepts. Try Live Demo
Ask which campus actually sits on the best multimodal feedstock for GPT-4V-class perception, Sora-class video, Gemini-scale bundles, and Meta Emu-style image stacks, and the short answer is almost vulgar in how cleanly it splits three big piles. Meta still pulls ahead by a chasm on stills, ByteDance owns the high-velocity short-video river that is really motion plus audio, and X ships the smallest absolute media volume yet the weirdest leverage on tight text-image coupling and live-event semantics.
Warren Buffett: The “Open Source” Leader Half a Century Before GitHub
巴菲特:比GitHub早了半个世纪的“开源”运动领袖
3 minute read
Published:
In an era driven by code, collaboration, and transparency, GitHub has become synonymous with the “open source” spirit. But if we turn our gaze to the world of finance, we find a pioneer of “open source” who predates the birth of GitHub by a full half-century. His name is Warren Buffett.
I ended up in the wrong NEXUS line at Vancouver International Airport. By the rules, the mistake was mine. By design, it was an almost predictable wrong turn.
“这b人生过的值不值” — roughly, “was this damn life worth it?” — is a phrase that does a lot of emotional work on the Chinese internet. ZuoGuoHuaDiao (做过划掉) is a small web tool that takes the phrase seriously and tries to answer it with numbers. Try Live Demo
Most people think of summer vacation as time off. I started wondering whether that framing undersells it. Summer Calculator is a small web tool that estimates the full value of your summer — money, learning, relationships, health — not just the days you didn’t work. Try Live Demo
A student-built navigation homepage that consolidates all essential UT Austin links in one place, solving the frustration of navigating deep university website hierarchies. Visit ut01.github.io
A handcrafted website universe where every webpage, balloon, click, and line of code says “I love you” - designed exclusively for Momo. Visit Live Site
Today I had an interesting experience collaborating with Claude Code to completely overhaul my personal academic website. As a PhD student in Geological and Earth Sciences at UT Austin, I needed to update my GitHub Pages site with real professional information instead of the placeholder content that had been sitting there.
From the vast datasets of Earth System Models to the specialized niches of high-performance computing, this space documents my journey as a PhD student at UT Austin pushing the boundaries of Geological and Earth Sciences. This website is more than just a portfolio—it’s a hub where data-driven climate science meets the practical challenges of modern research.
I plugged a Western Digital external drive full of data into a MacBook Air, tried to copy a file onto it, and nothing happened. No error dialog, no progress bar, just a drive that would let me read everything and write nothing. My first instinct was that something was broken, or that I needed to fix permissions. Both were wrong, and chasing the wrong explanation almost led me to permanently downgrade the security of the whole laptop.
我把一块装满数据的西部数据(WD)移动硬盘插到 MacBook Air 上,想往里拷一个文件,结果什么都没发生。没有报错弹窗,没有进度条,就是一块能读出所有东西、却一个字节都写不进去的硬盘。我的第一反应是它坏了,或者是我得去修一下权限。这两个判断都是错的,而且顺着错误的解释找下去,差点让我把整台笔记本的安全性永久降级。
Every generation has its own way of managing work: paper notebooks, SaaS task managers, and now programmable agentic workflows powered by tools like OpenClaw heartbeat.
Earth system models are some of the most complex scientific software ever written, and they are also some of the worst-documented for newcomers. I have been building a series of “skill packages” — structured, progressive-disclosure knowledge bundles — for the major Earth system and land surface models, designed to be used by both new graduate students and AI coding agents.
Ask which campus actually sits on the best multimodal feedstock for GPT-4V-class perception, Sora-class video, Gemini-scale bundles, and Meta Emu-style image stacks, and the short answer is almost vulgar in how cleanly it splits three big piles. Meta still pulls ahead by a chasm on stills, ByteDance owns the high-velocity short-video river that is really motion plus audio, and X ships the smallest absolute media volume yet the weirdest leverage on tight text-image coupling and live-event semantics.