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fastml.com | ||
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jalammar.github.io
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| | | | | Discussions: Hacker News (397 points, 97 comments), Reddit r/MachineLearning (247 points, 27 comments) Translations: German, Korean, Chinese (Simplified), Russian, Turkish The tech world is abuzz with GPT3 hype. Massive language models (like GPT3) are starting to surprise us with their abilities. While not yet completely reliable for most businesses to put in front of their customers, these models are showing sparks of cleverness that are sure to accelerate the march of automation and the possibilities of intelligent computer systems. Let's remove the aura of mystery around GPT3 and learn how it's trained and how it works. A trained language model generates text. We can optionally pass it some text as input, which influences its output. The output is generated from what the model "learned" during its training period where it scanned vast amounts of text. | |
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blog.adnansiddiqi.me
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| | | | | 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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blog.pdebruin.org
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| | | | | Retrieval Augmented Generation Hackathon starts on September 3. Repo with more info, stream schedule, samples, registration: https://aka.ms/raghack Large language models are powerful language generators, but they don't know everything about the world. RAG combines the power of large language models with the knowledge of a search engine. This allows you to ask questions of your own data, and get answers that are relevant to the context of your question. LLM AI YouTube playlists Thanks for reading! :-) | |
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initialcommit.com
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| | | The 10 Highest-Paying Software Development Certifications | ||
