Artificial intelligence

Artificial intelligence

(In a direct challenge to Microsoft's Copilot offerings, Opus 4.6 includes a plugin with PowerPoint, enabling Anthropic Claude model to easily spin up entire slide decks without the need to export files between applications.) The agent teams feature allows users to deploy multiple AI agents simultaneously that handle different aspects of a larger project. The agents work in parallel and communicate with each other to coordinate their efforts-mimicking how human teams divide and conquer complex assignments.

Somewhere between six and seven million years ago, our ancestors began walking upright, and the advantages were considerable: Freed from locomotion, upper limbs could grasp, manipulate, eventually craft, and the opposable thumb became the hinge on which human civilization would turn. We are, above all else, tool users-fire, the wheel, writing, the printing press, the transistor-each tool reshaping not only what we could do but who we became.

The Microsoft AI CEO said in an episode of the "Exponential View" podcast published Thursday that AI tools now make it possible for anyone to quickly start launching code and apps. "It is so accessible now," said Suleyman. "You can watch a three-minute video, get spun up, launch one of these things." "You can create an app, a web app in seconds," he added. Suleyman said people don't need deep technical skills to get started. Instead, they can learn by experimenting, watching, and doing.

Datadog recently announced that its LLM Observability platform now provides automatic instrumentation for applications built with Google's Agent Development Kit (ADK), offering deeper visibility into the behavior, performance, cost, and safety of AI-driven agentic systems. The integration, highlighted on the Google Cloud Blog, aims to make it easier for developers and SRE teams to monitor and troubleshoot complex multi-step AI agent workflows without extensive manual setup or custom instrumentation.

A small group of prominent tech companies had been handing money to each other for some time. The best summary was visual: Bloomberg clearly showed the circular flow of finances between Nvidia, AMD, Oracle, OpenAI, CoreWeave, and others. In the case of the Nvidia-OpenAI deal, the $100 billion investment would benefit new AI infrastructure, mostly filled with Nvidia hardware, which in turn would be paid for with that investment money.

Tools to create tailored, even personalised, scams leveraging, for example, deepfake videos of Swedish journalists or the president of Cyprus are no longer niche, but inexpensive and easy to deploy at scale, said the analysis from the AI Incident Database. It catalogued more than a dozen recent examples of impersonation for profit, including a deepfake video of Western Australia's premier, Robert Cook, hawking an investment scheme, and deepfake doctors promoting skin creams.

The human brain is complex. Artificial intelligence (AI) machine learning and medical imaging data are accelerating breakthroughs in brain health, especially in medical diagnostics. A peer-reviewed study published today in Nature Neuroscience unveils an AI foundation model called BrainIAC (Brain Imaging Adaptive Core) that is capable of predicting brain age, dementia, time-to-stroke, and brain cancer from brain magnetic resonance imaging (MRI).

Oracle's investments in AI may prove costly. Investment bank TD Cowen says the company hopes to reduce costs to finance its ambitious AI infrastructure build. To that end, it has already accumulated $58 billion in debt in two months. A round of layoffs affecting 30,000 employees is possible, while even a spin-off of Oracle Health, formerly Cerner, is being considered. Since September, Oracle has lost half of its market value, which currently stands at just under $400 billion.

Rival OpenAI sees it differently, and now plans to embed advertising in ChatGPT, something that CEO Sam Altman had previously said would be a "last resort". It's an indication that AI companies are still trying to balance the cost of development with the provision of service to their users.

When ChatGPT launched in late 2022, I watched something remarkable happen. Within two months, it hit 100 million users, a growth rate that sent shockwaves through Silicon Valley. Today, it has over 800 million weekly active users. That launch sparked an explosion in AI development that has fundamentally changed how we build and operate the infrastructure powering our digital world.

It said that its offering "gives agents the same skills people need to succeed at work: shared context, onboarding, hands-on learning with feedback and clear permissions and boundaries. That's how teams move beyond isolated use cases to AI coworkers that work across the business." Frontier works with existing systems, the announcement said, allowing customers to integrate their applications using open standards, which takes away the need to replatform.

As companies bet big on AI's development-from Google saying it will double its capital expenditure to Meta's bet on an AI acceleration in 2026-Americans have soured on the technology. While most say they've used AI, more have grown wary: 50% say they're more concerned than excited about the technology, according to recent Pew research. That's up from 37% in 2021. And just 10% say they are more excited than wary about the technology.

For one, there's the sheer speed and breadth of it. In the span of two days, hundreds of billions of dollars were wiped off the value of stocks, bonds and loans of companies big and small across Silicon Valley. Software stocks were at the epicenter, plunging so much that the value of those tracked in an iShares ETF has now dropped almost $1 trillion over the past seven days.