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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 new VB Beyond the Pilot podcast. “We wanted to make sure we were positioned to ride that wave of dynamism.”The strategy appears to be paying off in a big way. MassMutual has measured a roughly 30% increase in developer productivity, while AI-powered contact center workflows have reduced resolution times from 10 minutes to one and cut costs from dollars to cents. But the broader lesson for IT leaders may be less about the results and more about how the company is thoughtfully building its AI infrastructure and keeping users at the center. Maintaining optiona

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, iPad, Mac, Apple Watch and Vision Pro, as revealed in the WWDC26 Apple Intelligence developer guide.In other words, if your company offers an application on Apple devices, whether it's served on iOS mobile device or Mac, the new Siri AI may force you to change how that application is discovered, served, and its contents and workflows made available to end users. Enterprise developers can expose app content throu

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 production workloads.The new open-source model is a 30 billion parameter mixture-of-experts (MoE) model with 3 billion parameters active per token, built for agentic software engineering including sub-agent orchestration, architecture mapping, code review and terminal work. The model supports a 256,000 token context window with a 64,000 token maximum generation length, and is available on Hugging

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 the weight set off DRAM entirely.The AFM 3 family was developed in collaboration with Google and spans five models: two on-device and three server-based, all running within Apple's Private Cloud Compute boundary. The server-side models, including AFM 3 Cloud Pro for agentic tool use and complex reasoning, run on Nvidia GPUs in Google Cloud. The on-device architecture is Apple's own. AFM 3 Core Advanced is a 20-billion-parameter model that stores weights in NAND flash rather than DRAM."Instead of forcing the entire model into DRAM, the ful

Anthropic today launched two new AI models — Claude Fable 5 and Claude Mythos 5 — marking the company’s first broad release of the powerful “Mythos-class” AI capabilities it previously made available only to participating organizations in its restricted cybersecurity program, Project Glasswing, which it announced two months ago.The company says Fable 5, which is the version most users and developers will get starting today, exceeds every Claude model it has previously made generally available — featuring stronger performance across software engineering, knowledge work, vision, scientific research and long-running tasks. It smashes the existing benchmarks and comes atop on nearly all of them, though the prior Claude Mythos Preview version of the model still takes the

Presented by Norton For 39 days this summer, the planet will be doing roughly the same thing at the same time. The 2026 World Cup spans 104 matches across 16 cities in the United States, Canada, and Mexico, with billions of people likely to watch over the course of the tournament. It could very well be one of the largest shared events the internet has ever been asked to carry. What’s changed since the last tournament isn’t the scale, it’s the screen. For a growing share of that audience, the match won’t come through television. It’ll come through a browser tab. The problem is the browser you have today simply does not give you a frictionless and reliable way to watch the World Cup for free.In the U.S., a majority of viewers now expect to stream the tournament digitally rather than watch on cable or satellite. It only works when you have a paid subscription. But there is a challenge — for example, fans coming from Europe for who want to w

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. But the more important implication is organizational. When software no longer relies on humans to provide context, companies can no longer assume that knowledge lives in employees' heads or is buried inside disconnected applications. The company itself has to become machine-readable.The winners in the AI era won't simply deploy more intelligent models. They'll build the data foundations, semantic context, and governance frameworks that allow machines to understand how the business works and act on that understanding with confidence.Context is becoming