Google Nested Learning Explained: Hope Architecture, Continual Learning, and the End of Frozen LLMs
Google’s Nested Learning paper and Hope model explained: a new approach to continual learning in LLMs that addresses catastrophic forgetting.
Mixture of Nested Experts: Adaptive Processing of Visual Tokens
In this post we dive into Mixture of Nested Experts, a new method presented by Google that can dramatically reduce AI computational cost
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Vision Transformers Explained | The ViT Paper
In this post we go back to the important vision transformers paper, to understand how ViT adapted transformers to computer vision
Large Language Models As Optimizers – OPRO by Google DeepMind
In this post we dive into the Large Language Models As Optimizers paper by Google DeepMind, which introduces OPRO (Optimization by PROmpting).
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