What's Next in LLM Reasoning? with Roland Memisevic - #646
Analysis
This article summarizes a podcast episode discussing the future of Large Language Model (LLM) reasoning. It highlights a conversation with Roland Memisevic, a senior director at Qualcomm AI Research, focusing on the role of language in human-like AI, the strengths and weaknesses of Transformer models, and the importance of improving grounding in AI. The discussion touches upon topics like visual grounding, state-augmented architectures, and the potential for AI agents to develop a sense of self. The article also mentions Fitness Ally, a fitness coach used as a research platform.
Key Takeaways
- •The discussion centers on the evolution of LLM reasoning.
- •Key topics include the role of recurrence, visual grounding, and state-augmented architectures.
- •The potential for AI agents to develop a sense of self is explored.
Reference
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