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For decades, the IQ test has been one of the most familiar — and most contested — yardsticks for human intelligence. Now, a startup project called AI IQ is applying the same metaphor to artificial intelligence, assigning estimated intelligence quotients to more than 50 of the world's most powerful language models and plotting them on a standard bell curve. The result is a set of interactive visualizations at aiiq.org that have ricocheted across social media in the past week, drawing praise from

Good news, OpenClaw fans — you can once again use your Claude AI subscription to power the hit, open source, autonomous AI agentic harness! But, there's a big catch with how it's being enacted. A few hours ago, Anthropic announced via its official developer communications account on X, @ClaudeDevs, that it is changing its Claude paid subscription tiers, introducing a new subcategory of "Agent SDK" credits for all paid subscribers, which they can now allocate specifically for "programmatic" uses

For the first time since the AI race began, more American businesses are paying for Anthropic's Claude than for OpenAI's ChatGPT. Adoption of Anthropic rose 3.8% in April to 34.4% of businesses, according to the May 2026 release of the Ramp AI Index. OpenAI's adoption fell 2.9% to 32.3%. Overall AI adoption among businesses rose 0.2 percentage points to 50.6%. The crossover — published Tuesday by Ramp, the corporate card and finance automation platform that tracks spending patterns across more

As large language models become more capable, users are tempted to delegate knowledge tasks where models process documents on their behalf and provide the finished results. But how far can you trust the model to stay faithful to the content of your documents when it has to iterate over them across multiple rounds? A new study by researchers at Microsoft shows that large language models silently corrupt documents that they work on by introducing errors. The researchers developed a benchmark that

Any development environment that installed or imported one of the 172 compromised npm or PyPI packages published since May 11 should be treated as potentially compromised. On affected developer workstations, the worm harvests credentials from over 100 file paths: AWS keys, SSH private keys, npm tokens, GitHub PATs, HashiCorp Vault tokens, Kubernetes service accounts, Docker configs, shell history, and cryptocurrency wallets. For the first time in a TeamPCP campaign, it targets password managers

AI that can see and understand what's happening in a video — especially a live feed — is understandably an attractive product to lots of enterprises and organizations. Beyond acting as a security "watchdog" over sites and facilities, such an AI model could also be used to clip out the most exciting parts of marketing videos and repurpose them for social, identify inconsistencies and gaffs in videos and flag them for removal, and identify body language and actions of participants in controlled st

Between May 6 and 7, four security research teams published findings about Anthropic’s Claude that most outlets covered as three separate stories. One involved a water utility in Mexico, another targeted a Chrome extension, and a third hijacked OAuth tokens through Claude Code. In one case, Claude identified a water utility’s SCADA gateway without being told to look for one. These are not three bugs. They are one architectural question playing out on three surfaces. No single patch released so f

Presented by EdgeVerve For most enterprises, AI adoption began with a straightforward ambition: automate work faster, cheaper, and at scale. Chatbots replaced basic service requests, machine‑learning models optimized forecasts, and analytics dashboards promised sharper insights. Yet many organizations are now discovering that deploying individual AI solutions does not automatically translate into enterprise‑level impact. Pilots proliferate, but value plateaus. The next phase of AI maturity is n

Presented by Apptio, an IBM company AI spending is surging, but the full impact often remains an open question. Closing the gap requires clear answers to how AI is governed, measured, and tied to business outcomes. ROI uncertainty isn’t unique to AI: In the Apptio 2026 Technology Investment Management Report, 90% of technology leaders surveyed said that ROI uncertainty has a moderate or major impact on overall tech investment decisions, a 5-percentage point year-over-year increase. In other wor

Is AI leaving the era of "turn-based" chat? Right now, all of us who use AI models regularly for work or in our personal lives know that the basic interaction mode across text, imagery, audio, and video remains the same: the human user provides an input, waits anywhere between milliseconds to minutes (or in some cases, for particularly tough queries, hours and days), and the AI model provides an output. But if AI is to really take on the load of jobs requiring natural interaction, it will need t

A doctor in a hospital exam room watches as a medical transcription agent updates electronic health records, prompts prescription options, and surfaces patient history in real time. A computer vision agent on a manufacturing line is running quality control at speeds no human inspector can match. Both generate non-human identities that most enterprises cannot inventory, scope, or revoke at machine speed. That is the structural problem keeping agentic AI stuck in pilots. Not model capability. Not

AI agents choose tools from shared registries by matching natural-language descriptions. But no human is verifying whether those descriptions are true. I discovered this gap when I filed Issue #141 in the CoSAI secure-ai-tooling repository. I assumed it would be treated as a single risk entry. The repository maintainer saw it differently and split my submission into two separate issues: One covering selection-time threats (tool impersonation, metadata manipulation); the other covering execution