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Ep 31: CEO and Co-Founder of Mistral Arthur Mensch on the Next Frontiers for LLMs, Why Open Source Will Prevail and AI Safety
Unsupervised Learning
Mistral CEO Arthur Mensch on Alternative Architectures to Transformers
Exploring alternative architectures to transformers is challenging because the ecosystem around transformers, including training methods, optimization algorithms, debugging processes, and hardware, has evolved to align with it over the past seven years. This co-adaptation makes it difficult to transition to a new architecture and match the performance of transformers. Enhancements can be made on the attention side, such as implementing sparse attention for improved memory efficiency. Despite potential improvements, the high benchmark set by transformers through iterative refinements makes it daunting to introduce a completely new architecture, which is why many still rely on transformers for natural language processing tasks.
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