For more than two decades, digital businesses have relied on a simple assumption: When someone interacts with a website, that activity reflects a human making a conscious choice. Clicks are treated as signals of interest. Time on page is assumed to indicate engagement. Movement through a funnel is interpreted as intent. Entire growth strategies, marketing budgets, and product decisions have been built on this premise.

Anthropic has upgraded its Claude AI model with new capabilities for Microsoft Excel and PowerPoint, marking a strategic move to expand its enterprise footprint and potentially challenging Microsoft’s newly launched Copilot Cowork — which Claude also partially powers. 

The announcement, made at the company's annual GTC conference in San Jose, lands at a moment when the AI industry is grappling with a fundamental tension: the most powerful models in the world require enormous data center infrastructure, but the developers and enterprises building on those models increasingly want to keep their data, their agents, and their intellectual property local. The DGX Station is Nvidia's answer — a six-figure machine that collapses the distance between AI's frontier and a single engineer's desk.

For more than two decades, digital businesses have relied on a simple assumption: When someone interacts with a website, that activity reflects a human making a conscious choice. Clicks are treated as signals of interest. Time on page is assumed to indicate engagement. Movement through a funnel is interpreted as intent. Entire growth strategies, marketing budgets, and product decisions have been built on this premise.

The past ten days have been among the most consequential in OpenAI's history, with developments stacking up across product, politics, personnel, and the courts. Here is what happened — and what it means.

The convergence of a major product launch, a federal legal battle, and a landmark distribution deal with the world's largest software company captures the extraordinary tension defining Anthropic's current moment. The San Francisco-based AI lab is simultaneously trying to grow a developer tools business approaching $2.5 billion in annualized revenue, defend itself against an unprecedented government designation as a national security threat, and expand its commercial footprint through the very cloud platforms now navigating the fallout.

The Nvidia CEO unveiled the Agent Toolkit, an open-source platform for building autonomous AI agents, and then rattled off the names of the companies that will use it: Adobe, Salesforce, SAP, ServiceNow, Siemens, CrowdStrike, Atlassian, Cadence, Synopsys, IQVIA, Palantir, Box, Cohesity, Dassault Systèmes, Red Hat, Cisco and Amdocs. Seventeen enterprise software companies, touching virtually every industry and every Fortune 500 corporation, all agreeing to build their next generation of AI products on a shared foundation that Nvidia designed, Nvidia optimizes and Nvidia maintains.

For more than two decades, digital businesses have relied on a simple assumption: When someone interacts with a website, that activity reflects a human making a conscious choice. Clicks are treated as signals of interest. Time on page is assumed to indicate engagement. Movement through a funnel is interpreted as intent. Entire growth strategies, marketing budgets, and product decisions have been built on this premise.

Presented by AudioEye

Recent reports about AI project failure rates have raised uncomfortable questions for organizations investing heavily in AI. Much of the discussion has focused on technical factors like model accuracy and data quality, but after watching dozens of AI initiatives launch, I’ve noticed that the biggest opportunities for improvement are often cultural, not technical.