Everyone is talking about agents: single agents and, increasingly, multi-agent systems. What kind of applications will we build with agents, and how will we build with them? How will agents communicate with each other effectively? Why do we need a protocol like A2A to specify how they communicate? Join Ben Lorica as he talks with…
Google has just released a technical report detailing how much energy its Gemini apps use for each query. In total, the median prompt—one that falls in the middle of the range of energy demand—consumes 0.24 watt-hours of electricity, the equivalent of running a standard microwave for about one second. The company also provided average estimates…
I remember once flying to a meeting in another country and working with a group of people to annotate a proposed standard. The convener projected a Word document on the screen and people called out proposed changes, which were then debated in the room before being adopted or adapted, added or subtracted. I kid you…
As an acquisitions editor at O’Reilly, I spend considerable time tracking our authors’ digital footprints. Their social media posts, speaking engagements, and online thought leadership don’t just reflect expertise—they directly impact book sales and reveal promotional strategies worth replicating. Not surprisingly, some of our best-selling authors are social media mavens whose posting output is staggering….
Recent surveys point to a massive growth in AI-driven bots crawling the internet looking for APIs. While many of these have malicious intent, a growing number are well-meaning API consumers just trying to discover, consume, and benefit from existing APIs. And, increasingly, these API requests are coming from MCP-driven platforms (Model Context Protocols) designed to…
We think we see the world as it is, but in fact we see it through a thick fog of received knowledge and ideas, some of which are right and some of which are wrong. Like maps, ideas and beliefs shape our experience of the world. The notion that AI is somehow unprecedented, that artificial…
The following is Part 2 of 3 from Addy Osmani’s original post “Context Engineering: Bringing Engineering Discipline to Parts.” Part 1 can be found here. Great context engineering strikes a balance—include everything the model truly needs but avoid irrelevant or excessive detail that could distract it (and drive up cost). As Andrej Karpathy described, context…
Using machine learning, MIT chemical engineers have created a computational model that can predict how well any given molecule will dissolve in an organic solvent — a key step in the synthesis of nearly any pharmaceutical. This type of prediction could make it much easier to develop new ways to produce drugs and other useful…
How do you want your AI to treat you? It’s a serious question, and it’s one that Sam Altman, OpenAI’s CEO, has clearly been chewing on since GPT-5’s bumpy launch at the start of the month. He faces a trilemma. Should ChatGPT flatter us, at the risk of fueling delusions that can spiral out of…
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…