Trevor Chow
I write about how AGI and markets collide - subscribe!
My writing has been covered by outlets like Bloomberg, The Economist, Vox and the Financial Times, as well as being used by thinktanks like the AEI and Open Phil.
Previously, I was at Stanford, where I worked on inference time scaling with Hazy Research and was published at NeurIPS, ICLR and ACL. I’ve also spent time on the S&P volatility desk at Optiver.
Feel free to DM me on Twitter.
Bookshelf
Feeling the AGI
Pre-Training Isn't Dead, It's Just Resting
Pre-training scaling laws haven’t bent, but the marginal dollar has moved to RL. It’ll come back and the OOMs will grow.
VC Investments in AI Labs are Betting Against AGI
Scaling laws reward the consolidation of AI labs, but investors are diversifying anyways. This indefinite optimism is a mistake.
You Can Find the Best LLM Output Without Labels
By taking advantage of a weak supervision-inspired approach, we can find the best LLM output at inference time, without needing ground truth labels. Accepted to NeurIPS ‘24.
Reasoning Will Speed Up AI Research
o1 is a bigger deal than ChatGPT: it marks the start of the reasoning paradigm. Decades of progress will occur in months.
Pre-Training is About Data Above All Else
The three key insights from pre-training LLMs in the last 4 years all point to the importance of data.
Polysemantic Neurons Can Occur Incidentally
Polysemantic neurons are an obstacle to interpreting AI. Even in over-parameterised models, they can arise incidentally. Accepted to BGPT & Re-Align @ ICLR ‘24.
Bond Markets Aren't Predicting AGI
The arrival of AGI means an increase in real interest rates. Rates are still low: markets are not expecting AGI in the next 30 years! Accepted to Oxford GPR ‘23.
Pre-Training Isn't Dead, It's Just Resting
Pre-training scaling laws haven’t bent, but the marginal dollar has moved to RL. It’ll come back and the OOMs will grow.
VC Investments in AI Labs are Betting Against AGI
Scaling laws reward the consolidation of AI labs, but investors are diversifying anyways. This indefinite optimism is a mistake.
You Can Find the Best LLM Output Without Labels
By taking advantage of a weak supervision-inspired approach, we can find the best LLM output at inference time, without needing ground truth labels. Accepted to NeurIPS ‘24.
Reasoning Will Speed Up AI Research
o1 is a bigger deal than ChatGPT: it marks the start of the reasoning paradigm. Decades of progress will occur in months.
Pre-Training is About Data Above All Else
The three key insights from pre-training LLMs in the last 4 years all point to the importance of data.
Polysemantic Neurons Can Occur Incidentally
Polysemantic neurons are an obstacle to interpreting AI. Even in over-parameterised models, they can arise incidentally. Accepted to BGPT & Re-Align @ ICLR ‘24.