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 qwenlm.github.io
GSPO: Towards Scalable Reinforcement Learning for Language Models | Qwen
| | allenai.org
Tülu 3: The next era in open post-training | Ai2
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| | A technical deep-dive into Tülu 3, with the model "recipe", data, and more.
| | amatria.in
Beyond Token Prediction: the post-Pretraining journey of modern LLMs - AI, software, tech, and people. Not in that order. By X
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| | (This blog post, as most of my recent ones, is written with GPT-4 assistance and augmentation)
| | sebastianraschka.com
Predictive modeling, supervised machine learning, and pattern classification
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| | I'm Sebastian: a machine learning & AI researcher, programmer, and author. As Staff Research Engineer Lightning AI, I focus on the intersection of AI research, software development, and large language models (LLMs).
| | neuralnetworksanddeeplearning.com
Neural networks and deep learning
24.5 parsecs away

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| [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...