InfoWorld

As enterprises rush to build AI agents that can reason over business data and take action, Databricks argues that the long-standing practice of separating operational and analytical data systems is turning into a liability. That separation, the cloud-based data warehouse provider says, is becoming increasingly strained as AI agents require simultaneous access to live operational data and historic…

Developers are caught between the joy — or pressure — of using agents to ship 10x faster today and the dread of how they will maintain that code tomorrow. The gap between “vibe” code and code that can be deployed to millions of users is vast and easy to underestimate. Closing the gap requires care, expertise, and effort, with the payoff coming later. Agents are able to complete increasingly compl…

Every organization has data scattered across data warehouses, data lakes, SaaS platforms, cloud drives, and data centers. Data fabrics enable organizations to centralize and control data access, making it easier for users, such as data scientists and citizen data analysts , to find and use trusted and governed data sources. Data fabrics, data meshes, and distributed data clouds are all platforms …

Nvidia’s new RTX Spark is one of the most interesting personal computing announcements in years. That’s because it’s not just another PC platform, but tries to redefine the role of the personal computer in the age of AI . Announced at Computex 2026, RTX Spark is Nvidia’s new platform for slim Windows laptops and compact desktops, designed to combine an Arm-based CPU, Blackwell-based RTX graphics,…

AIs struggle to understand documents designed for humans; the DocLang working group seeks to flip that imbalance with its specification for machine-readable business documents “built from the ground up for LLM tokenizers.” The working group, founded by IBM, Nvidia, and Red Hat and hosted by the Linux Foundation’s LF AI & Data project, aims to create an open, universal, AI-native document format d…

For years, the cloud market has made a simple promise: Move workloads to large-scale platforms, gain better resilience, and worry less about downtime. That promise was never entirely wrong, but it is becoming less complete. The latest findings from Uptime Institute’s seventh Annual Outage Analysis suggest that the outage landscape is changing in ways that should concern both cloud providers and c…

We’ve all heard the mantra from the quants in the business community: you can’t manage what you can’t measure. And if that’s true for human intelligence, it should be true for the artificial kind too. How do we measure agents and large language models (LLMs)? We’re just beginning to come up with statistical metrics. Here are several of the most common metrics that designers and users toss about w…

Enterprises are increasingly investing copious amounts of cash in AI without a lot to show for it. This could be, in part, because the wrong people are leading the change. As I’ve argued before ⁠, AI isn’t likely to eliminate developers so much as change what we need from them. For example, we keep asking whether junior developers are needed in a world where large language models can write code f…

Extremely powerful large language models (LLMs) still operate as though they’re typing on a keyboard, processing workloads in a simple left-to-right fashion. But in locally-run, single-user scenarios, this sequential processing can leave graphics processing units (GPUs) and tensor processing units (TPUs) underutilized. Google is betting that DiffusionGemma can get around this bottleneck. The new …

CIOs and CISOs have many strategic and operational fears when it comes to unleashing fully-autonomous agents on tasks and hoping that everything works out. Will the agent start to delete critical files? Will the agent go off on a mission tangent and generate a massive token bill for the team when they return the next morning? Will it be tricked by a state actor and engage in malicious actions? To…

When Pope Leo XIV wrote about the effect that AI is having on our world in his encyclical, Magnifica Humanitas, he may not have imagined the document being referenced in an HR environment. But, according to a report by Business Insider , Erin Maus, a software developer in North Carolina, used the Pope’s message about the need for vigilance in how AI would be deployed to gain a special exemption f…

Microsoft has open-sourced an AI evaluation framework that converts natural-language requirements into executable tests, expanding its push into enterprise AI governance as organizations struggle to validate agent behavior before production deployments systematically. The framework, called ASSERT (Adaptive Spec-driven Scoring for Evaluation and Regression Testing), generates evaluation scenarios,…

Databricks on Wednesday unveiled OpenSharing, a new open protocol designed to let enterprises share AI models, agent skills, dashboards, and unstructured data across platforms without having to copy or move those assets. That sharing is made possible by OpenSharing’s zero-copy credential vending model that allows recipients to securely access shared assets directly from a provider’s cloud storage…

Between 2029 and 2032, every currently supported long-term support (LTS) version of Java will reach end-of-support within a single three-year window: Java 17 in 2029, Java 8 in 2030, Java 21 in 2031, and Java 11 in 2032. On paper, this looks like a manageable upgrade cycle. In practice, it creates a collision of timelines that most enterprises have failed to forecast. Organizations attempting to …

Modern AI systems have evolved beyond the simple chatbots that quickly became popular. Now they use semantic tools to manage workflows and link machines to machines, providing a flexible and effective framework for the next generation of business automation. What you used to build in Microsoft’s Power Platform or construct inside Biztalk is now an agent, built around large language models (LLMs) …