Even the best AI models can suck at chess The launch of ChatGPT had an interesting effect on the online chess discourse. Chess has already long been conquered by machines. As early as 1996 a computer (IBM’s Deep Blue) was able to beat the human world champion, grandmaster Garry Kasparov, in a game w...
When my oldest child was born, I immediately set up Gmail and Twitter accounts in her name. I broadly announced her birth online and proceeded to plaster her photo across all sorts of platforms. In short, I began creating her digital footprint long before she could stand on her own two feet. Fast-f...
AI models flub these intelligence tests. Can you fare any better?
Puzzles and games have been central to AI development since the very beginning. Just as we humans like to test our smarts with crosswords or logic puzzles, developers can test how far models have advanced with a gaming gauntlet. The term “machine learning” was popularized in a 1959 article by the IB...
IBM Releases Granite 4.2: Bringing Native Reasoning and Agentic RL to Open Enterprise Models
IBM has released Granite 4.2, a family of open reasoning language models in 3B, 8B, and 30B sizes, all under Apache 2.0. Every model exposes a thinking / low-effort / non-thinking switch and native tool calling. The 8B and 30B additionally go through an agentic RL block that trains them to edit code...
How loveholidays is making everyone a builder with Codex
Discover how loveholidays uses OpenAI Codex to make software development accessible across the business, helping teams turn ideas into products faster.
Liquid AI Open-Sources Pipette: A Reproducible Benchmarking Suite That Measures On-Device Models, Quantization, Runtime and Hardware Together
Model cards report quality under server-class, full-precision conditions. Those numbers rarely predict how the same model behaves on a phone. This week, Liquid AI released Pipette. It is an open-source platform for benchmarking foundation models on edge devices, built in partnership with Artificial ...
Perplexity Ships Portable Computer on NVIDIA DGX Spark: Local Harness, OS-Enforced Sandbox, and Zero Per-Token Cost for Local Steps
Perplexity releases Portable Computer, packaging local models, harness, sandbox, and connectors into one system running on NVIDIA DGX Spark.
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Meta AI Introduces MetaRoCE: A Clean-Sheet RDMA Transport Built for AI-Scale Ethernet
Training and serving frontier models is now a networking problem as much as a compute problem. Collective operations like all-reduce and all-to-all synchronize thousands of accelerators during training, and the slowest transfer sets the pace for the entire job. Even small amounts of network friction...
The Design System as the Control Plane for AI-Generated UI
AI-assisted development has made it easier to generate frontend code quickly. A developer can ask for a form, a dashboard widget, a settings page, or a modal flow and get a working first draft in seconds. That speed is useful, especially when teams are moving through routine UI work. But speed creat...
OpenAI’s Jalapeño chip is built for fast inference at scale, benchmarks show
Tested on Semianalysis’s InferenceX benchmark, Jalapeño registered both more tokens per user and more throughput per kilowatt than the currently available state-of-the art.
Shadow Agents, Standing Privileges, and the Governance Gap Between Deployment and Discovery
There was a brief window where AI agent security felt like a future problem. Organizations deployed copilots, coding assistants, and autonomous workflows on the assumption that the worst case was a bad recommendation or a hallucinated answer. That window closed in the first half of 2026, when a clus...
I spent a day at a robot “carnival” in Shanghai. Here’s what I saw.
Humanoid robots are having a moment in China. The popular machines are part of the country’s strategy to bring artificial intelligence into daily life. Embedding the technology into physical systems—an idea called embodied AI—was a key facet of China’s latest five-year plan, and companies here are a...
OpenAI CFO Sarah Friar explains how advances across chips, compute, models, and products compound to deliver more useful intelligence at greater scale and lower cost.
Jalapeño’s first results show industry-leading speed and efficiency in AI inference
Jalapeño is a custom inference chip from OpenAI that delivers faster, more power-efficient AI inference, with higher throughput and lower latency for modern models.