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electricarchaeology.ca | ||
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simonwillison.net
Embeddings are a really neat trick that often come wrapped in a pile of intimidating jargon. If you can make it through that jargon, they unlock powerful and exciting techniques ... |
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blog.adnansiddiqi.me
Learn the basics of Large Language Models (LLMs) in this introduction to GenAI series. Discover how LLMs work, their architecture, and practical applications like customer support, content creation, and software development. |
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shekhargulati.com
Today I was reading Chapter 9 "Multimodal Large Language Models" of Hands-On Large Language Models book and thought of applying it to a problem I face occassionally. The chapter covers CLIP model and how you can use them to embed both text and images in the same vector space. Like most normal humans, I take... |
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neuralnetworksanddeeplearning.com
[AI summary] The text provides an in-depth explanation of the backpropagation algorithm in neural networks. It starts by discussing the concept of how small changes in weights propagate through the network to affect the final cost, leading to the derivation of the partial derivatives required for gradient descent. The explanation includes a heuristic argument based on tracking the perturbation of weights through the network, resulting in a chain of partial derivatives. The text also touches on the historical context of how backpropagation was discovered, emphasizing the process of simplifying complex proofs and the role of using weighted inputs (z-values) as intermediate variables to streamline the derivation. Finally, it concludes with a citation and licens... |
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