NeurIPS 2023: Our Favorite Papers on LLMs, Statistical Learning, and More
Two Sigma researchers highlight some of the most captivating papers and presentations on machine learning from NeurIPS 2023.
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Ben Wellington Talks AI, Data Science, and Improv on The Gradient Podcast
Ben Wellington joins The Gradient podcast to discuss his career at the intersection of finance and AI, along with key lessons he's learned on the journey.
A Guide to Large Language Model Abstractions
The authors map the landscape of frameworks for abstracting interactions with and between large language models, and suggest two systems of organization for reasoning about the various approaches to, and philosophies of, LLM abstraction.
Systematic and Discretionary Macro: Better Together
Systematic and discretionary macro funds have had similar risk-adjusted returns on average, and intuitively have different relative advantages. This analysis demonstrates that over the past ~15 years, a blend of the two delivered a higher Sharpe ratio than either approach alone.
Hype vs. Reality: David Siegel on Large Language Models
Two Sigma Co-Chairman David Siegel speaks about the significant potential—and considerable hype—surrounding large language models like GPT-4 and other innovations in artificial intelligence.
Series: Elevating Your Skills as a Two Sigma Engineer
An overview of some of the ways Two Sigma supports the growth and development of our engineers, helping them to cultivate their ability to think about hard problems in novel ways and apply fresh approaches to solving them.
Latest Insights & Research
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News From Around Two Sigma
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April 13, 2023
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Sustainability Science in Action: Measuring the Carbon Intensity of a Compute Environment
We highlight some of the early initiatives the Sustainability Science team has led to accurately determine the carbon footprint of certain parts of Two Sigma’s compute environment, with a specific focus on a critical first step: How to measure power consumption at the server level accurately.