The U.S. military enlisted natural language processing to combat disinformation. Primer, a San Francisco startup, is developing a system for the Department of Defense that sifts through news, social media, research, and reports to spot propaganda campaigns.

An open source library could spawn trillion-parameter neural networks and help small-time developers build big-league models. Microsoft upgraded DeepSpeed, a library that accelerates the PyTorch deep learning framework.

People granted early access to OpenAI’s latest language model are raving about its way with words — and more. Beta testers of GPT-3 are showing off the model’s ability to write business memos, craft blogs, pen tweets, and even generate computer code.

Which headline was written by a computer? A: FIFA to Decide on 2022 World Cup in March B: Decision in March on 48-team 2022 World Cup, Says Infantino

MIT withdrew a popular computer vision dataset after researchers found that it was rife with social bias. Researchers found racist, misogynistic, and demeaning labels among the nearly 80 million pictures in Tiny Images, a collection of 32-by-32 pixel color photos.

Facebook uses automated systems to block hate speech, but hateful posts can slip through when seemingly benign words and pictures combine to create a nasty message. The social network is tackling this problem by enhancing AI’s ability to recognize context.

I’m thrilled to announce our new Natural Language Processing Specialization! Courses 1 and 2 are available on Coursera. We expect to release Courses 3 and 4 soon.

The words “big” and “large” have similar meanings, but they aren’t always interchangeable: You wouldn’t refer to an older, male sibling as your “large brother” (unless you meant to be cheeky). Choosing among words with similar meanings is critical in language tasks like translation.

I’m thrilled to announce our new Natural Language Processing Specialization! Courses 1 and 2 are available on Coursera. We expect to release Courses 3 and 4 soon. NLP is reshaping daily life.

Progress in language models is spawning a new breed of chatbots and, unlike their narrow-domain forebears, they have the gift of gab. Recent research tests the limits of conversational AI.

Music that features a “singing” koala bear took the prize in one of Europe’s highest-profile AI competitions yet. A team of Australian programmers, designers, and musicians won the inaugural AI Song Contest with a koala-tinged track called “Beautiful the World.”

AI has added an unlikely language to its catalog of translation capabilities: brain waves. Joseph Makin led a group from the University of California San Francisco to render a person’s neural signals as English text while the person while the person read a sentence aloud.

A new algorithm can triage programming bugs, highlighting dangerous flaws. Microsoft researchers developed a machine learning model that reads the titles of bug reports and recognizes those describing flaws that compromise security.

Earlier language models powered by Word2Vec and GloVe embeddings yielded confused chatbots, grammar tools with middle-school reading comprehension, and not-half-bad translations. The latest generation is so good, some people consider it dangerous.

As language models show increasing power, a parallel trend has received less notice: The vogue for naming models after characters in the children’s TV show Sesame Street.