Within the past few years, models that can predict the structure or function of proteins have been widely used for a variety of biological applications, such as identifying drug targets and designing new therapeutic antibodies. These models, which are based on large language models (LLMs), can make very accurate predictions of a protein’s suitability for…
In 1943, while the world’s brightest physicists split atoms for the Manhattan Project, the American psychologist B.F. Skinner led his own secret government project to win World War II. Skinner did not aim to build a new class of larger, more destructive weapons. Rather, he wanted to make conventional bombs more precise. The idea struck…
Prompted in part by Apple’s paper about the limits of large language models (“The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity”), I spent some time playing with Tower of Hanoi. It’s a problem I solved some 50 years ago when I was in college, and…
The AI Frontiers article (reproduced below) builds on a previous Asimov Addendum article written by Tim O’Reilly, entitled: “Disclosures. I do not think that word means what you think it means.” I (Ilan) think it’s important to first very briefly go through parts of Tim’s original piece to help recap why we—at the AI Disclosures Project—care about protocols…
Despite the promise of AIOps, the dream of fully automated, self-healing IT environments remains elusive. Generative AI tools may be the solution that finally abstracts away enough of the workload to get there. However, today’s reality is far more complex. Internet performance monitoring firm Catchpoint’s recent SRE Report 2025 found that for the first time…
I’ve been thinking a lot lately about a species of carpenter ant that lives in the mountains around Jerusalem. These tiny insects might just hold the key to one of AI’s biggest challenges: alignment. The ants in question are called Camponotus sanctus, and they do something remarkable that puts our most sophisticated AI systems to…
Jay Alammar, director and Engineering Fellow at Cohere, joins Ben Lorica to talk about building AI applications for the enterprise, using RAG effectively, and the evolution of RAG into agents. Listen in to find out what kinds of metadata you need when you’re onboarding a new model or agent; discover how an emphasis on evaluation…
The following is Part 1 of 3 from Addy Osmani’s original post “Context Engineering: Bringing Engineering Discipline to Parts.” Context Engineering Tips: To get the best results from an AI, you need to provide clear and specific context. The quality of the AI’s output directly depends on the quality of your input. How to improve…
Last month, I spoke with Matthew Prince, cofounder and CEO of Cloudflare, as part of my ongoing series of public conversations, Live with Tim O’Reilly. Cloudflare made waves with its July 1 announcement that it will block AI crawlers by default and give content owners the ability to decide who can use their material for…
Since ChatGPT appeared on the scene, we’ve known that big changes were coming to computing. But it’s taken a few years for us to understand what they were. Now, we’re starting to understand what the future will look like. It’s still hazy, but we’re starting to see some shapes—and the shapes don’t look like “we won’t…