The hype around DeepMind’s new AI model misses what’s actually cool about it

Earlier this month, DeepMind presented a new “generalist” AI model called Gato. The model can play Atari video games, caption images, chat, and stack blocks with a real robot arm, the Alphabet-owned AI lab announced. All in all, Gato can do 604 different tasks. 

But while Gato is undeniably fascinating, in the week since its release some researchers have gotten a bit carried away.

One of DeepMind’s top researchers and a coauthor of the Gato paper, Nando de Freitas, couldn’t contain his excitement. “The game is over!” he tweeted, suggesting that there is now a clear path from Gato to artificial general intelligence, or AGI, a vague concept of human- or superhuman-level AI. …Unsurprisingly, de Freitas’s announcement triggered breathless press coverage that DeepMind is “on the verge” of human-level artificial intelligence. This is not the first time hype has outstripped reality.

…That’s a shame, because Gato is an interesting step. Some models have started to mix different skills, …DeepMind’s AlphaZero learned to play Go, chess, and shogi, …but here’s the crucial difference: AlphaZero could only learn one task at a time. After learning to play Go, it had to forget everything before learning to play chess, and so on. It could not learn to play both games at once. This is what Gato does: it learns multiple different tasks at the same time, which means it can switch between them without having to forget one skill before learning another. It’s a small advance but a significant one. Read More

#singularity

The dark secret behind those cute AI-generated animal images

Another month, another flood of weird and wonderful images generated by an artificial intelligence. In April, OpenAI showed off its new picture-making neural network, DALL-E 2, which could produce remarkable high-res images of almost anything it was asked to. It outstripped the original DALL-E in almost every way.

Now, just a few weeks later, Google Brain has revealed its own image-making AI, called Imagen. And it performs even better than DALL-E 2: it scores higher on a standard measure for rating the quality of computer-generated images, and the pictures it produced were preferred by a group of human judges.

“We’re living through the AI space race!” one Twitter user commented. “The stock image industry is officially toast,” tweeted another. Read More

#image-recognition

Copilot, GitHub’s AI-powered coding tool, will be free for students

Last June, Microsoft-owned GitHub and OpenAI launched Copilot, a service that provides suggestions for whole lines of code inside development environments like Microsoft Visual Studio. Available as a downloadable extension, Copilot is powered by an AI model called Codex that’s trained on billions of lines of public code to suggest additional lines of code and functions given the context of existing code. Copilot can also surface an approach or solution in response to a description of what a developer wants to accomplish (e.g. “Say hello world”), drawing on its knowledge base and current context.

While Copilot was previously available in technical preview, it’ll become generally available starting sometime this summer, Microsoft announced at Build 2022. Copilot will also be available free for students as well as “verified” open source contributors. On the latter point, GitHub said it’ll share more at a later date. Read More

#devops