The Quest for AGI: Q*, Self-Play, and Synthetic Data

One topic at the center of the AI universe this week is a potential breakthrough called Q*. Little has been revealed about this OpenAI project, other than its likely relationship to solving certain grade-school mathematical problems.Amid much speculation, we decided to bring in our new general partner, Anjney Midha – focused on all things AI – to sift through the sea of noise.Today, we discuss the key frontier research areas that AI labs are exploring on their path toward generalizable intelligence, from self-play, to model-free reinforcement learning to synthetic data. Anjney also shares his insights on which approach he expects to be most influential in the next wave of LLMs and why math problems are even a suitable testing ground for this kind of research. Topics Covered:02:03 - What is Q*?06:21 - Applying model-free reinforcement learning to complex spaces13:17 - The role of self-play19:04 - Synthetic data’s big unlock24:44 - What does this unlock for society? Resources:Follow Anjney on Twitter: }https://twitter.com/AnjneyMidha Stay Updated: Find a16z on Twitter: }https://twitter.com/a16zFind a16z on LinkedIn: }https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: }https://a16z.simplecast.com/Follow our host: }https://twitter.com/stephsmithioPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.