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28min chapter
#157 - Gemini controversy, new Mistral models, Deepmind's Genie & Griffinn, AI Warfare is here
Last Week in AI
Advancements in AI Model Training and Quantum Computing Optimization
The chapter explores groundbreaking papers on training AI models without action labels, utilizing vector quantized variational auto encoders, and generating playable environments from diverse sources. It also delves into the evolution of RNN architectures with attention mechanisms and the scalability aspect, comparing the Griffin model to Lama2. Moreover, it discusses quantum circuit optimization using alpha tensor, focusing on quantum error correction and T gate optimization for efficient quantum computing.
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