Tianhao Wu

I am a 3rd year Ph.D. student jointly advised by Prof. Jiantao Jiao and Prof. Kannan Ramchandran at UC Berkeley. During my undergrad, I worked with Prof. Liwei Wang and graduated with a B.S. degree in Mathematics
Currently, my research focuses on fine-tuning LLMs using reinforcement learning with human feedback (RLHF). Building on this, my ambition is to construct an AI agent with the inherent ability to self-evolve without human supervision. I envision a paradigm where computational resources can be directly translated to the intelligence an AI possesses. Such an AI would vastly outpace human intelligence
I’m also quite intrigued by the idea of forming an AI Society. Imagine in the future, each person possesses a personalized AI agent . These agents could link together in a modular fashion to form a more capable collective intelligence, as well as being flexible enough to be added or removed from the collective. This decentralized paradigm could mitigate the huge memory and computing demand that limit centralized AI systems today.
news
Nov 28, 2023 | We released Starling-7B, an open-source large language model leveraging RLAIF |
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Sep 12, 2023 | A paper regarding RLHF will be coming soon by the end of Sep ![]() ![]() |
latest posts
Dec 4, 2023 | Starling-7B: Improving LLM Helpfulness & Harmlessness with RLAIF |
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Oct 1, 2023 | Rethinking the Role of PPO in RLHF |