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GenAI image generators like Stable Diffusion do not draw a picture pixel by pixel from left to right. They start with noise and iteratively refine the entire image in parallel until it converges, in a process known as diffusion. For years, applying that same principle to text generation had remained out of reach at scale. …

Google’s DiffusionGemma generates 256 tokens in parallel and self-corrects as it goes Read More »

Presented by Capital One Enterprises aren’t struggling to experiment with AI; they’re struggling to make it work in the real world. Moving from promising prototypes to reliable, production-scale systems is where most efforts stall. In my role within Capital One’s AI Foundations organization, I’ve seen firsthand that successful AI implementation isn’t just about adopting the …

Why AI that works in the lab often fails in production — and what actually fixes it Read More »

Researchers from the University of California, Berkeley’s Center for Responsible, Decentralized Intelligence (RDI), alongside an advisory committee of over 300 domain experts, have launched Agents’ Last Exam (ALE)—a grueling new benchmark built to measure whether artificial intelligence can actually execute economically valuable, long-horizon professional workflows. In a shocking upset, OpenAI’s GPT-5.5 from April, operating through …

Surprise upset: GPT-5.5 beats Claude Fable 5 on brutal new Agents’ Last Exam benchmark Read More »

Training a foundation LLM from scratch costs millions and requires internet-scale data — which is why most enterprises don’t bother. Sapient thinks it has a cheaper path. To overcome this brute-force scaling dogma, researchers at Sapient developed HRM-Text, which replaces standard Transformers with a highly sample-efficient Hierarchical Recurrent Model (HRM), an architecture they first introduced …

Researchers say they trained a foundation model from scratch for about $1,500 Read More »

In a sweeping new essay titled “Policy on the AI Exponential,” Anthropic co-founder and CEO Dario Amodei publicly calls for new government regulations governing the release of powerful AI models — specifically comparing AI industry to commercial aviation, which follows regulations enforced by the U.S. Federal Aviation Administration (FAA) — arguing that this is necessary …

Anthropic CEO calls for FAA-style regulation of powerful AI models: what enterprises should know Read More »

Enterprise AI teams face a dilemma: The best models today might not be the best models a year from now. MassMutual’s answer is to stop making long-term bets — and build infrastructure that can swap models as the market shifts. “The world of AI today is extremely dynamic,” Sears Merritt, MassMutual CIO, explained in a …

MassMutual’s AI strategy: 12-month contracts, 30% productivity gains, zero lock-in Read More »

Presented by Snowflake As AI agents become capable of reasoning across systems and taking action, software is evolving from something employees operate into something that understands intent. Instead of navigating disparate applications and dashboards, a single system will increasingly ask: What are you trying to accomplish? That sounds like a user experience breakthrough. It is. …

AI is about to replace the interface. Business leaders aren’t ready Read More »

Engineering teams building agentic coding pipelines now have a concrete open-source alternative to managed models like Claude Fable 5 — one that runs on a single H100. The tradeoff: Cohere’s North Mini Code, which launched Tuesday, generated three times the output tokens of comparable models in independent testing, a verbosity cost that compounds in high-volume …

Cohere open-sources a coding agent that runs on a single H100 Read More »

Apple’s new Siri AI, unveiled yesterday at Apple’s annual Worldwide Developers Conference (WWDC 2026), may look like a consumer product story on the surface. But for enterprise developers and IT leaders, the bigger news from WWDC26 is that Apple is turning Siri into a systemwide AI interface for apps, data and workplace actions across iPhone, …

Apple’s new Siri AI is more than just a smarter assistant — it’s a new enterprise app layer Read More »

On-device AI models have stayed small because the entire weight set has to live in DRAM, capping practical parameter counts well below what server-side deployments use. Enterprise architects evaluating agentic workloads have had to choose between capable cloud-dependent models and limited on-device ones. Apple’s third-generation foundation models, announced at WWDC26, break that constraint by moving …

On-device AI agents hit a hard memory limit. Apple’s new architecture routes around it. Read More »