Prompt Engineering Guide A great repository that covers history of LLMs, strategies, guidelines, and safety recommendations for working with and building programmatic systems with LLMs. https://
github.com/brexhq/prompt-
engineering
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LLMS
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Prompt Engineering Guide: LLM History, Strategies and Safety
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Why AI safety concerns suddenly matter to the public
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2019: OpenAI thought GPT-2 presented serious long term risks. Others in the community didn’t care. Public didn’t care. 2023: OpenAI releases GPT-4 with lots of safety tests. Loud parts of the community goes nuts. Public cares enough that governments rush to legislate. Explain?
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Step-by-Step Guide to Building Your Personal LLM Chatbot
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A step-by-step approach to set up your own personal #LLM chatbot. Nice one, Peter!
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Microsoft Bing and Edge: New Wave of AI Innovation
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Announcing the next wave of AI innovation with Microsoft Bing and Edge – The Official Microsoft Blog
https://bit.ly/3nzXQfn #AI #MachineLearning #DeepLearning #LLMs #DataScience -
Rick’s GPT Code Tutorial Guide
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First things first, check out Rick's excellent tutorial: https://
ricklamers.io/posts/gpt-code/ -
Facebook Custom LLaMA Training Services Enterprise Model
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You can imagine a company coming to Facebook, saying it wants a custom version of LLaMA, and Facebook deciding to do the training/fine-tuning/serving for it. All the tech is there, along with the talent, DNA, and resources.
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Facebook builds ML-focused Google Cloud competitor with LLaMA
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But there's another part of the story here: Facebook has built what seems to be a very early machine learning-focused prototype of.. Google Cloud. It has a training cluster technology it's developed, hardware for inference, and owns a massively popular OSS-ish LLM, LLaMA.
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AI Chip Startups Face Setbacks Amid Market Challenges
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Some of the hottest chip startups are now hitting snags. Graphcore laid off 160 people last year as a deal to supply Microsoft fell through, and SambaNova also went through some layoffs earlier this year. Cerebras has pushed hard into LLMs with its own OSS LLM models.
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Together Compute and Hugging Face Partnership for Model Inference
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We want to thank our partners @togethercompute for their valuable feedback, for hosting model inference and for providing the @huggingface front-end UI (6/6)
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BLOOMChat Achieves 66% Preference Over Open-Source LLMs
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1. BLOOMChat achieved a average win rate of 45.25% compared to GPT-4's 54.75% across 6 languages in a human preference study. 2. BLOOMChat was preferred 66% of the time compared to mainstream open-source chat LLMs across 6 languages in a human preference study. (3/6)