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Three Kuhnian Revolutions in ML Training
| | jalammar.github.io
How GPT3 Works - Visualizations and Animations - Jay Alammar - Visualizing machine learning one concept at a time.
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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.
| | jack-clark.net
Import AI 392: China releases another excellent coding model; generative models and robots; scaling laws for agents | Import AI
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| | Welcome to Import AI, a newsletter about AI research. Import AI runs on lattes, ramen, and feedback from readers. If you'd like to support this, please subscribe. Subscribe now Generative models are unlocking all-purpose home robots:...Household robots are getting closer, but will need to be far more robust and adaptable to withstand a home containing...
| | www.shaped.ai
Size Isn't Everything - How LLaMA democratizes access to Large-Language-Models | Shaped Blog
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| | Recently, Meta announced the release of a new AI language generator called LLaMA. While tech enthusiasts have been primarily focused on language models developed by Microsoft, Google, and OpenAI, LLaMA is a research tool designed to help researchers advance their work in the subfield of AI. In this blog post, we will explain how LLaMA is helping to democratize large language models.
| | kavita-ganesan.com
A Gentle Introduction to Deep Neural Networks with Python - Kavita Ganesan, PhD
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| This article examines the parts that make up neural networks and deep neural networks, as well as the fundamental different types of models (e.g. regression), their constituent parts (and how they contribute to model accuracy), and which tasks they are designed to learn.