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What’s Next in LLM Reasoning? with Roland Memisevic - #646

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

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The Evolution of Language Models

This chapter explores the progression from RNN-based architectures to transformers, emphasizing their improved efficiency in language tasks. It discusses the complexities and potential pitfalls of these models, particularly in reasoning and context retention. Furthermore, it examines the intersection of language, cognition, and visual grounding, proposing enhancements for more robust AI reasoning capabilities.

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