The Art of (Artificial) Reasoning
Scaling laws suggest that “more is more” — brute-force scaling of data and compute leads to stronger AI capabilities. However, despite rapid progress on benchmarks, state-of-the-art models still exhibit "jagged intelligence," indicating that current scaling approaches may have limitations in terms of sustainability and robustness. Additionally, while the volume of papers on arXiv continues to grow rapidly, our scientific understanding of artificial intelligence hasn't kept pace with engineering advances, and the current literature presents seemingly contradictory findings that can be difficult to reconcile. In this talk, I will discuss key insights into the strengths and limitations of LLMs, examine when reinforcement learning succeeds or struggles in reasoning tasks, and explore methods for enhancing reasoning capabilities in smaller language models to help them close the gap against their larger counterparts in specific domains.
On the Science of “Alien Intelligences”: Evaluating Cognitive Capabilities in Babies, Animals, and AI
Today’s generative AI systems—termed by some researchers as “alien intelligences”—have exceeded human performance on many benchmarks meant to test humanlike cognitive capabilities. However, these systems still struggle in unhumanlike ways on real-world tasks requiring these capabilities. This disconnect may be due in part to neglect in the AI community of well-founded experimental protocols for evaluating cognition. In this talk I will summarize several recommendations on experimental methods from developmental and comparative psychology—fields that study the “alien intelligences” of babies and non-human animals—and demonstrate the application of such methods in two case studies of cognitive abilities in LLMs: analogical reasoning and visual abstraction.
Claiming Your True Market Value as an AI Researcher - Negotiation Workshop & Fireside Chat
As AI reshapes industries, compensation is changing faster than researchers can track. New labs, startups, and top companies are competing for talent with vastly different pay structures, currencies, and cultural norms. Yet most researchers are never formally taught how to understand their worth or navigate these systems. The result is an uneven landscape where brilliant minds often make life-changing decisions without the information they need.