Google DeepMind Blog
· deepmind.google
Sep 3, 2026
Blog
Updates and guides from us, plus hand-picked reads from tech & AI blogs.
MIT News · Artificial Intelligence
· news.mit.edu
Sep 2, 2026
From MIT to IBM, expediting AI and quantum deployment
MIT affiliates engage with the MIT-IBM Computing Research Lab to bring rigorous theory to production systems.
MIT News · Artificial Intelligence
· news.mit.edu
Sep 2, 2026
System helps humans predict when self-driving cars will make mistakes
A new method, called CW-Net, translates the reasoning process of an autonomous vehicle’s AI system into understandable concepts that explain its behavior.
Hugging Face Blog
· huggingface.co
Sep 1, 2026
Introducing @huggingface/kernels: 200+ WebGPU Kernels for Local AI
Reach audiences
Advertise in front of researchers, engineers, and readers.
Google Research Blog
· research.google
Aug 27, 2026
Planetary prediction engine: Automating global models via Earth AI
Earth AI
Google DeepMind Blog
· deepmind.google
Aug 27, 2026
Piloting the world's first double-blind AI evaluations
Piloting the world's first double-blind AI evaluations
MIT News · Artificial Intelligence
· news.mit.edu
Aug 26, 2026
AI helps design new materials that work in the real world
The “CrysVCD” tool developed at MIT could cut the huge amounts of time and money spent on screening out chemically unstable designs.
Google Research Blog
· research.google
Aug 21, 2026
An AI tool for prioritizing candidate biomarkers from wearable sensor data
Generative AI
Google DeepMind Blog
· deepmind.google
Aug 21, 2026
From Atari to EVE Online: Building on 15 Years of AI Research in Games
Google DeepMind partners with game studios to prototype breakthrough AI gameplay.
Hugging Face Blog
· huggingface.co
Aug 20, 2026
Up to 3.2x Faster Inference with LFM2.5-DSpark
A Blog post by Liquid AI on Hugging Face
MIT News · Artificial Intelligence
· news.mit.edu
Aug 18, 2026
When AI art has no author: Study finds generated images often can’t be traced to training data
A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.