Ahmad Beirami

Ahmad Beirami, a former Google researcher, dives into the intricacies of reinforcement learning and its relevance to AI models. He highlights the evaluation challenges in AI research and argues for a shift towards deeper analysis rather than chasing small gains. Ahmad also critiques the current conference review system, revealing its strain and the issues it creates. Discussions include agent workflows, the implications of quantization, and the need for better methods in RL evaluation, all emphasizing the importance of integrating theoretical insights with empirical work.