Original Link: Training a SOTA Code LLM in 1 week and Quantifying the Vibes — with Reza Shabani of Replit
Summary
From Quantitative Trading to AI Leadership: Reza Shabani’s Journey and Predictions
Alessio Fanelli, partner and CTO in residence at Decibel Partners, and co-host swyx, a writer and editor of the Latent Space podcast, invite Reza Shabani, the Head of AI at Replit, for a chat. Reza details his surprising background, beginning with a PhD in economics from Berkeley, moving on to startup founding, followed by a stint in systematic equity trading at BlackRock and Wellington. A common assumption is that Reza doesn't know how to code given his econ background, but he clarifies that coding and data analysis were indeed part of his wheelhouse.
The conversation takes a deep dive into quantitative finance and data engineering. Reza describes his grad school experience, which entailed extracting and analyzing data from financial news channels to gauge the market response to specific companies. He touches on his experiences at BlackRock, where he dabbled in utilizing emerging technologies, like NLP and machine learning, to trade effectively. They further discuss how identifying early adoption of emerging technologies by companies can serve as an indicator of their potential success in the stock market. For instance, Walmart's early focus on mobile technology as opposed to Sears’ lack of attention to it was discussed as an example. The conversation also touches on the challenge of signals being overshadowed by noise in the finance world. Towards the end, Reza raises an intriguing question about the potential for AI to excel in quantitative finance.