sarah guo

@traestephens this is a great idea

I’ve been arguing for over a decade that mandatory civil service would make America stronger. The typical response was that it would just be an obstacle between people and their goals…or that it’s uNConStITutioNaL and that we’d rather have violent tribalwarfare between the purple hair baristas and the incels. Now that widespread job loss driven by AI looms, the idea has become a lot more palatable. Go check out the argument @PirateWires. Come at me, bro.

@alextoussss asking for a friend is there a humane version of this that will zap geese just enough to make sure they stay away from a lawn forever

infinite summer ☀️

@brainstub @iyanmoonyang hey, know your audience. some of us have a decade on you and are still cringe posting their siblings out here

I’m so juiced about it

guys, robots are real

@Mike_A_Merrill I scooped ice cream and made websites

@jackdent @gradypb @IndexVentures @kleinerperkins @sequoia @_DimensionCap @m_delamerced @nytimes from science to engineering!

Thrilled to announce our $400M Series C led by @IndexVentures, with @kleinerperkins, @sequoia, @_DimensionCap and others. Great to speak to @m_delamerced @nytimes about how drug discovery using AI is moving from a promise to actual deployment.

so proud of the amazing team @chaidiscovery! deployment with Eli Lilly, Pfizer and Novartis, and another $400M to build. we are standing in the foothills of the next era of medicine

.@ouraring Tom I would pay for the ability to inflate my own sleep metrics, to myself

it took 1 intern 3 months of continuous work, but eventually, a quantization method that beat every other algo in the market, including @nvidia's official modelopt to explain why this matters, i ask for exactly 69 seconds of your attention (275 words @ avg reading speed of 238 wpm): frontier models (like glm52) are huge (~0.8T params). as released, each parameter takes 2 bytes (bf16), so overall size is about 1.6 tb a b200 has 180gb of memory. a node of 8 gives you 1.44 tb, barely fits weights, much less activations / kv cache must quantize the model (reduce the size of each individual parameters) to serve. fp8 quantization means each parameter takes 1 byte (fits in 0.8 tb), fp4 takes 1/2 a byte (fits in 0.4 tb) cutting the model to a quarter its original size is necessary for it to run a) cheap b) fast, and every lab serving models does this. but, quantization lobotomizes the model if not done correctly (this is why you see people complain about @AnthropicAI nerfing claude or @OpenAI nerfing codex) there are currently several algorithms (like Nvidia's official model-opt) that attempt to figure how to quantize a model with the least amount of damage. they find the redundant layers that can be slashed, and sensitive/important layers that need to stay in full-precision. these algo's have two drawbacks: 1) they take a long time to run 2) they quite often result in a sub-optimal configuration for the past 3 months, a research (and, as always, waterloo) intern on our model perf team (@the_joshua_hill) came up with a new quant algorithm. it consistently finds the optimal configuration: a) in less time than SOTA b) with more aggressive quant than SOTA c) scoring higher on benchmarks than SOTA achieving just one of the above is a feat on its own. all three...excited for the paper to come out this week

my first ever (!) stock pick, in 2011, was $BKNG. this week's @NoPriorsPod with @BookingHoldings CEO Glenn Fogel on marketplaces, travel, AI, and why moats aren't real

@xbradtc 👀

If your name is Sarah and you’re not telling people it’s short for Triceratops, what are you even doing with your life?

@Alfred_Lin @HarryStebbings @MattEvantic 🙏🏽

@HarryStebbings @saranormous @MattEvantic Both incredible people and investors, and they're starting to get more of the recognition they deserve.

Every week I speak to 3-5 LPs about various different things. They all ask; which manager of the last 2-3 years has broken out above all others? So easy. - @saranormous beyond crushed with Conviction: - @MattEvantic is in literally every 🚀 in Europe and US in last 12 months. Mega respect to both. Incredible.

@alexshander03 @adarsh_exe @bfspector @AqilNaeem13 Or the 👑 @pranavreddy

Pretty much. Turns out that being trained in making well substantiated arguments about the state of the world translates well to making well substantiated bets about the future of the world There's a long list that comes to mind... @adarsh_exe, @bfspector & asher, @AqilNaeem13, @adhit_sankaran, just to name a few who else

@fidjissimo 💜 Fidji

Today, I shared with the OpenAI team that I have decided to leave my full-time role at OpenAI and transition to being a part-time advisor. Three months ago, I had to go on medical leave after a severe exacerbation of a chronic illness I’ve lived with for seven years. During that time, it became clear that the road to recovery would be much longer and more complex than I had anticipated—and that I needed to focus on it fully. When I went on leave, many people told me I was courageous for prioritizing my health. The truth is that I am only making this decision now because I failed to make it many times before. Over the years, doctors, friends, colleagues, and loved ones encouraged me to slow down. Two years after I got sick, Facebook offered me the opportunity to take a full year of medical leave. I didn’t even pause to consider it. I immediately said no. At the time, Zuck told me I should play the long game. I wish I had listened. Looking back, I realize that a lot of what made me successful also made this decision incredibly difficult. I grew up believing that opportunities were precious and that when they appeared, you grabbed them with both hands. That mindset carried me from a small town in southern France to opportunities I never could have imagined. By the time I turned 40, I had already gotten to do more than I’d ever dreamed possible as a kid growing up in Sète. I love building. My work has always given me a deep sense of purpose. OpenAI in particular felt like a role that my entire career had been building toward, which made this decision even harder. But what I’m learning now is that grit and endurance are not the only skills required to have impact over decades. Sometimes the harder thing is to stop, listen, and trust that taking care of yourself today makes it possible to contribute for much longer tomorrow. This experience has also strengthened my conviction about why this work matters. It has been a jarring experience to spend my days helping build the future while simultaneously navigating a disabling disease that still has no cure. Over the last seven years, I’ve spent countless hours in doctors’ offices, dealing with symptoms, treatments, insurance, uncertainty, and all the invisible work that comes with being a patient. Like millions of others living with chronic illness, I’ve experienced firsthand how difficult healthcare can be to navigate, even when you have every possible advantage. More than ever, I believe that some of the most important opportunities for AI lie in helping people solve real problems in their daily lives: their health, their finances, their time and the everyday burdens that shape human experience. In particular, curing disease is the most important thing AI could accomplish. I’m excited to continue working towards cures through OpenAI but also through my work with @ChronicleBioAI and @CODA_research. I’m deeply grateful to @sama, @gdb and the OpenAI board for their support during this time and for offering a way for me to continue contributing to the mission without sacrificing my chances of recovery. I’m also so thankful to my team and the many extraordinary colleagues I’ve had the privilege to build alongside. For now, my focus is recovery. But my belief in the potential of technology to solve deeply human problems has never been stronger.

@MerriamWebster definition of “democratic socialism” along with Denmark's Prime Minister (Lars Løkke Rasmussen) stating clearly that his country is not socialist, but as a robust capitalist free-market economy supported by a strong welfare safety net

Americans want to own homes, build wealth, and have economic opportunity. So some are voting for socialists like Mamdani because he has recognized these anxieties and identified a villain (but not a real solution). What is most likely to help? Socialism consistently makes everyone equally poor. The experiment has been run already! You don’t build prosperity by attacking the entrepreneurs, businesspeople, or investors who create it. We do not want to be Maoist China, the Soviet Union, Venezuela, Cuba, East Germany, North Korea. This is a very bad club of outcomes. The next decade will create more business owners than the last century. AI gives anyone with entrepreneurial spirit cheap access to extraordinary human capital. Reindustrialization will bring back productive work. Broad asset ownership can put millions more Americans on the path to wealth. And every dollar will go further as economic productivity surges. Ordinary Americans will suffer if irresponsible politicians, educators and malicious international influence campaigns create 100M Marxists. It will prosper with 100M more Bogleheads. We can be a nation of wealthy owners.

We are hiring for @Harvey’s model training team. This team will help Harvey expand from the application layer into the model layer and from legal into high end knowledge work more broadly. We are hiring AI researchers of all seniority, particularly those with experience post-training frontier or open source models. Our program is centered around large-scale model training, synthetic data generation, long horizon reinforcement learning, and rigorous evaluation in real world deployments. We are scaling-pilled and believe that nothing beats the combination of larger models and better training data. We’ve been able to generate incredibly realistic legal environments and validated that this allows us to post-train open source models to achieve frontier performance with agents. We plan to scale up these data generation and training efforts significantly across legal to start, and eventually other verticals. As a researcher, you will have access to thousands of GPUs and unique training data from our product and customer relationships. Your research will inform Harvey’s product strategy and power AI used for some of the most economically and societally impactful work in the world.