Year in Review

The Batch - AI News & Insights: Last week, I attended the NeurIPS conference in New Orleans. It was fun to catch up with old friends, make new ones, and also get a wide scan of current AI research.

Fans of AI-driven music pressed play, while a major recording company reached for the stop button. AI grabbed listeners by the ears when it helped produce a new single by The Beatles, mimicked the voices of beloved stars, and generated music from text prompts.

Angst at the prospect of intelligent machines boiled over in moves to block or limit the technology. Fear of AI-related doomsday scenarios prompted proposals to delay research and soul searching by prominent researchers. Amid the doomsaying, lawmakers took dramatic regulatory steps. 

Information may not want to be free after all. The age-old practice of training AI systems on data scraped from the web came into question as copyright owners sought to restrict AI developers from using their works without permission.

The movie capital became a front line in the battle over workplace automation. U.S. film and television writers went on strike in May, and actors followed in July. They took up a variety of issues with their employers, but concern that AI would damage...

This year, AI became virtually synonymous with generative AI. Launched in November 2022, OpenAI’s ChatGPT ushered in a banner year for AI-driven generation of text, images, and an ever widening range of data types. 

Individual deep learning models proved their mettle in hundreds of tasks. The scope of multi-task models expanded dramatically in the past year.

Researchers pushed the boundaries of language models to address persistent problems of trustworthiness, bias, and updatability.

Work on vision transformers exploded in 2022. Researchers published well over 17,000 ViT papers during the year. A major theme: combining self-attention and convolution.

Behind schedule on a software project? There’s an app for that. Language models fine-tuned on computer code proved capable of generating software routines similar to the work of experienced developers — though the results can be hit-or-miss.

Pictures produced by AI went viral, stirred controversies, and drove investments. A new generation of text-to-image generators inspired a flood of experimentation, transforming text descriptions into mesmerizing artworks and photorealistic fantasies.

Musicians and filmmakers adopted AI as a standard part of the audio-production toolbox. What happened: Professional media makers embraced neural networks that generate new sounds and modify old ones. Voice actors bristled.

While models like GPT-3 and EfficientNet, which work on text and images respectively, are responsible for some of deep learning’s highest-profile successes, approaches that find relationships between text and images made impressive

In 2021, transformers were harnessed to discover drugs, recognize speech, and paint pictures — and much more.

Legislators worldwide wrote new laws — some proposed, some enacted — to rein in societal impacts of automation.What happened: Authorities at all levels ratcheted up regulatory pressure as