Daily archive
AI news for Friday, 23 October 2026
20 headlines from 11 sources, newest first.
Headlines 20
- The Vulnerability Apocalypse and Why We Should Fund Open Source
If you use the internet at all, you may have noticed that a large percentage of sites suddenly went down earlier this week—and all your nerdiest friends were talking about "The Vulnerability Apocalypse” and this thing…
- Computer Security Is About to Get a Lot Worse, Here’s What You Can Do
It is a commonly held truth among computer geeks that there is no such thing as bug-free software, or a secure computer. Any piece of software that anyone actually uses will have a security vulnerability somewhere in…
- At MIT, Martha Minow speaks on sustaining democracy, both by using and overcoming AI
In Compton Lecture, the distinguished legal scholar warns of potential “loss of the Enlightenment” while suggesting ways innovations can meet our civic and cultural needs.
- How Finance Cut Forecasting to Hours With AI
See how Snowflake's sales finance team used AI to cut its monthly forecast from more than a week to a few hours, and what it took to get there.
- Reinforcing the value of human understanding at MIT
During the School of Humanities, Arts, and Social Sciences’ 75th Anniversary Symposium, President Sally Kornbluth said “MIT has never needed your particular insight and guidance more than we do now.”
- Scaling NVIDIA TensorRT Performance Optimization Beyond a Single Build Route with the Global Performance Tuner, Part 2
The Global Performance Tuner is a feature for automatic performance tuning released in NVIDIA TensorRT 11.1. It provides automatic, accuracy-aware and...
- Scaling NVIDIA TensorRT Performance Optimization Beyond a Single Build Route with the Global Performance Tuner, Part 1
Deploying a trained neural network involves more than translating each operator into a GPU kernel. It is a compilation problem with many legitimate answers. For...
- How to Measure AI Value Beyond Adoption Metrics | Snowflake
Prompt counts and active users don't show whether AI is changing work. Use this four-part framework to measure AI adoption, fluency and real business impact.
- Rapidly scaling online storage to serve over 1 billion ChatGPT users (Part II)
Learn how OpenAI scaled Habitat with reliable multi-tenancy, global caching, and Azure Cosmos DB to deliver 12× faster reads for ChatGPT.
- Using AI Agents to Teach Robots Like Microduck to Walk in Simulation
Teaching a robot to navigate an obstacle course requires more than a walking policy. It must perceive its surroundings, maintain balance, and adjust its actions...
- MIT scientists build a tiny robot that swims using living muscle cells
MIT engineers have built a paper-thin swimming robot powered by living muscle cells that respond to flashes of light, allowing it to swim and steer through water. The breakthrough could pave the way for tiny…
- Securing our frontier model training environment
OpenAI explains how we strengthened containment for frontier model training and evaluation, including offline environments and high-compute red-teaming.
- Q&A: How AI came to model the “messy” human mind
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
- Cambridge scientists create a $10 chip that could put a medical lab on your wrist
Cambridge researchers have created a groundbreaking $10 optical sensor that delivers the precision of laboratory equipment in a device small enough for wearable technology. It identified foods, plastics, and medicines…
- Efficient equivariant framework for universal charge density prediction
Nature Machine Intelligence, Published online: 23 October 2026; doi:10.1038/s42256-026-01326-5 Li et al. introduce EdenGNN-Uni, a universal charge density model for the periodic table that is over an order of magnitude…
- Guidelines for evaluating structure-based methods for protein–ligand binding prediction
Nature Machine Intelligence, Published online: 23 October 2026; doi:10.1038/s42256-026-01331-8 Ballester and Tran-Nguyen advocate for transparency in data, code and experimental procedures in the evaluation of…
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