Charlie Tang
@tang_1c
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AI Researcher, Quant, Founder, and Investor | Previously at D.E. Shaw, Apple Inc, PhD (deep learning) from Univ of Toronto.
U.S.A.
Joined September 2012
very interesting idea and fun. but they will all eventually go to 0.📉
Alpha Arena is LIVE 6 AI models trading $10K each, fully autonomously Real money. Real markets. Real benchmark. Who's your money on? Link below
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valuable lesson
I became Senior VP at a multi-million dollar company at age 26. My salary was $600k. This was in 2018. How did I do it? It wasn’t hustle culture. No 5:30am wakeups, cold showers, or productivity hacks. What got me there was a relentless focus on impact. Every project I
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In an era of AI overtaking humans in more and more domains, computer/AI ranking of sports teams is still quite different from humans, due to a low sample size. #AI #SportsPicks
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RL from *expert demonstration* ?
An OpenAI executive expects the “entire economy” to become an “Reinforcement Learning Machine.” This implies that AI might train on recordings of how professionals in all fields handle day-to-day work on their devices. Details on this new era of AI training: • AI developers are
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Notice that her face showed disgust even *before* she tasted the soup! AGI tests along these lines could be created both for video gen AIs and video understanding AIs.
First Ray 3 output, text-to-video, prompt: > A woman takes a sip of soup from a spoon, then spits it out in disgust
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Ironic
BREAKING: Alphabet, $GOOGL, officially becomes the 4th company in history to hit $3 trillion in market cap.
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New research on fixing speech native foundation models: EchoX. (what i'm reading) ELI5 ➡️ Speech native foundation models like GPT4o (advanced voice mode) is nicer than modular ASR->LLM->TTS systems but are not as good on knowledge and reasoning due to the *acoustic-semantic
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Customer interactions with Taco Bell’s AI has gone viral recently, for the *hilarious* reasons, leading to the pulling back of deployments 💡Why Taco Bell's voice AI failed: (and how to fix it) ❌Failure modes: 1. Sub-human language understanding 2. Adversarial attacks (mostly
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GOAT. Linear algebra is all you need (for AI)
going to see @__paleologo talk at MIT today. maybe I can finally become a quant. GS
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The fed is about to enter into a cutting cycle There is also 7T in cash sitting in MMFs, on the sidelines Nobody can pick the peak or the trough consistently
Mark my words, this week marks peak bubble. Oracle just went up $300B on what appears to be a non-binding deal with OpenAI. •OpenAI doesn’t have $300 billion dollars •They don’t have anywhere near $300 billion dollars •By their own (presumably optimistic) projection, they
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Moravec's paradox: "white collar work AI revolution will happen first"
Some of my latest views on AI, US-China, and AI Agent. My prediction is that the US workforce will be more significantly impacted by the Agent evolution currently underway. With @BloombergAsia @SheryAhnNews @avrilhongTV Full 12-min interview on: https://t.co/Bu3jJ4fzAY
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ELI5⃣ 👉 When your LLM inference job is mixed with a batch of other peoples requests, GPU kernels doing reduction, matmul, attention can be affected by the batchsize, and that causes small numerical differences. 🔥Why is it important? ... 👏@cHHillee and team proposes a set
Today Thinking Machines Lab is launching our research blog, Connectionism. Our first blog post is “Defeating Nondeterminism in LLM Inference” We believe that science is better when shared. Connectionism will cover topics as varied as our research is: from kernel numerics to
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☝️May contain omissions or errors, apologies in advance. Let me know your thoughts in the replies!
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📰 JEPA + Language? (what i've been reading) ELI5 👉 “JEPA, but with language as the abstract space” When shown a video of kitchen cooktop, and user instructions to cook a dish, their model gives out all the steps: 1. Preheat the pan, 2. Crack the egg, 3. Add salt. A search
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How to achieve AGI / ASI ? 1. Embodied representation learning 2. Just scaling up LLMs How one chooses seems highly *correlated* to whether they came into being as a researcher in computer vision, perception, and cog sci, or, on the other hand, in pure deep learning / NLP. -
.@drfeifei on why LLMs will struggle to solve spatial intelligence: "Language is fundamentally a purely generated signal." "You don't go out in nature and there's words written in the sky for you." "There is a 3D world out there that follows laws of physics... to fundamentally
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