The generative gold rush is on. Venture capitalists are betting hundreds of millions of dollars on startups that use AI to generate images, text, and more, Wired reported.

Sentence pairs that have equivalent meanings in different languages — typically used to train machine translation systems — have been available in sufficient quantities for only around 100 languages. New work doubled that number and produced a more capable model.

For the debut episode of a new podcast series, Play.ht synthesized a 19-minute interview between the rock-star podcaster and late Apple CEO.

Only a week ago, researchers unveiled a system that generates a few seconds of video based on a text prompt. New work enables a text-to-video system to produce an entire visual narrative from several sentences of text.

A worldwide collaboration produced the biggest open source language model to date. BLOOM is a family of language models built by the BigScience Research Workshop, a collective of over 1,000 researchers from 250 institutions around the globe.

You can reduce your model’s carbon emissions by being choosy about when and where you train it.

Machine learning is helping lawyers sift through mountains of documents to find evidence. The legal technology company Everlaw launched a clustering feature that automatically organizes up to 25 million documents for lawyers gathering evidence to be used during a trial.

A chatbot persuaded at least one person that it has feelings. A senior engineer at Google announced his belief that the company’s latest conversational language model is sentient.

Years ago, I had to choose between a neural network and a decision tree learning algorithm. It was necessary to pick an efficient one, because we planned to apply the algorithm to a very large set of users on a limited compute budget.

What kind of beast was Aristotle? The philosopher's follower Porphyry, who lived in Syria during the third century, came up with a logical way to answer the question...

Let’s get this out of the way: A brain is not a cluster of graphics processing units, and if it were, it would run software far more complex than the typical artificial neural network. Yet neural networks were inspired by the brain’s architecture.

There was a moment when logistic regression was used to classify just one thing: If you drink a vial of poison, are you likely to be labeled “living” or “deceased”? Times have changed.

Itching to get your hands on a fully trained large language model? The wait is over. Meta introduced the OPT family of transformer-based language models with nearly unfettered access to source code and trained weights.

Vision Transformer (ViT) outperformed convolutional neural networks in image classification, but it required more training data. New work enabled ViT and its variants to outperform other architectures with less training data.

The emerging generation of trillion-parameter language models take significant computation to train. Activating only a portion of the network at a time can cut the requirement dramatically and still achieve exceptional results.