GPT-3

A team in the United Arab Emirates, a seven-state federation on the Arabian Peninsula, built the latest top-performing open source large language model.

Text-to-image generators like DALL·E 2, Stable Diffusion, and Adobe’s new Generative Fill feature can revise images in a targeted way — say, change the fruit in a bowl from oranges to bananas — if you enter a few words that describe the change plus an indication of the areas to be changed.

Specialized chatbots are providing answers to scientific questions. A new breed of search engines including Consensus, Elicit, and Scite use large language models to enable scientific researchers to find and summarize significant publications, Nature reported.

If you want a model to answer questions correctly, then enriching the input with reference text retrieved from the web is a reliable way to increase the accuracy of its output. But the web isn’t necessarily the best source of reference text.

When you’re looking for answers from a large language model, some prompts are better than others. So how can you come up with the best one? A new model automates the process.

What do your GitHub projects reveal about your professional prospects? A new model aims to help recruiters find out. Prog.ai analyzes GitHub repositories to help employers find engineers skilled in particular areas, TechCrunch reported.

Media outlets are forging ahead with generative AI despite the technology’s high-profile misfires. Publishers are using text generators to produce light reading within constrained formats such as holiday messages and quizzes.

AI hobbyists created an homage to their favorite TV show . . . until it got knocked off the server. The creators of Nothing, Forever launched a fully automated, never-ending emulation of the popular TV show Seinfeld.

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.

Nvidia, known for chips designed to process AI systems, is providing access to large language models. Nvidia announced early access to NeMo LLM and BioNeMo, cloud-computing services that enable developers to generate text and biological sequences respectively.

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.

AI startups are helping writers tailor articles that appear near the top of Google’s search results. At least 14 companies sell access to software that uses GPT-3, the language model from OpenAI, to generate headlines, product descriptions, blog posts, and video scripts.

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.

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.

OpenAI unveiled a more reliable successor to its GPT-3 natural language model. InstructGPT is a version of GPT-3 fine-tuned to minimize harmful, untruthful, and biased output. It's available via an application programming interface.