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Improve multi-hop reasoning in LLMs by learning from rich human feedback

AWS Machine Learning Blog

In this post, we show how to incorporate human feedback on the incorrect reasoning chains for multi-hop reasoning to improve performance on these tasks. Those confident but nonsensical explanations are even more prevalent when LLMs are trained using Reinforcement Learning from Human Feedback (RLHF), where reward hacking may occur.

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The Full Story of Large Language Models and RLHF

Hacker News

In the grand tapestry of modern artificial intelligence, how do we ensure that the threads we weave when designing powerful AI systems align with the intricate patterns of human values? What is the learning process of a language model? What is RLHF and how to make language models more aligned with human values?

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How DALL-E 2 Actually Works

AssemblyAI

Plenty of background information will be given and the explanation levels will run the gamut, so this article is suitable for readers at several levels of Machine Learning experience. A birds-eye view of the DALL-E 2 image generation process (modified from source ). From a bird's eye-view, that's all there is to it!

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Dialogue-guided visual language processing with Amazon SageMaker JumpStart

AWS Machine Learning Blog

Visual language processing (VLP) is at the forefront of generative AI, driving advancements in multimodal learning that encompasses language intelligence, vision understanding, and processing. Their use cases span various domains, from media entertainment to medical diagnostics and quality assurance in manufacturing.

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Best prompting practices for using the Llama 2 Chat LLM through Amazon SageMaker JumpStart

AWS Machine Learning Blog

Its model parameters scale from an impressive 7 billion to a remarkable 70 billion. Diving deeper into Llama 2’s architecture, Meta reveals that the model’s fine-tuning melds supervised fine-tuning (SFT) with reinforcement learning aided by human feedback (RLHF).

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