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Frugality meets Accuracy: Cost-efficient training of GPT NeoX and Pythia models with AWS Trainium

AWS Machine Learning - AI

Their quick adoption is evident by the amount of time required to reach a 100 million users, which has gone from “4.5yrs by facebook” to an all-time low of mere “2 months by ChatGPT.” A generative pre-trained transformer (GPT) uses causal autoregressive updates to make prediction. We’ll outline how we cost-effectively (3.2

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Named Entity Recognition: The Mechanism, Methods, Use Cases, and Implementation Tips

Altexsoft

A corpus can range from a set of news articles to academic journals or even social media posts. Word embeddings translate words or phrases into numerical vectors of fixed size, making it easier for machine learning models to process. This is a collection of texts used for linguistic analysis and training NER models. Why use it?

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My belated 2022 recap: blog posts and articles

Puppies, Flowers, Rainbows and Kittens

Spotify’s grand plan to monetize its open source Backstage project via premium plugins [link] by Paul Sawers Backstage was created when I was at Spotify. It’s cool to see how it has developed over the years, and it was also cool to see that Spotify had open-sourced it. I’ve broken it into sections based on content.

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AI Image Generation Explained: Techniques, Applications, and Limitations

Altexsoft

Generative Adversarial Networks (GANs) Generative Adversarial Networks , commonly called GANs , are a class of machine learning algorithms that harness the power of two competing neural networks – the generator and the discriminator. By the way, you can learn more about large language models and ChatGPT in our dedicated articles.