Data: The One Thing You Can’t Rent

As AI models approach data scarcity, companies face new barriers to access proprietary, verified information, shifting industry power toward data owners.

Data: The One Thing You Can’t Rent

In 2026, the AI industry faces a critical shift as data becomes the scarce resource that can’t be rented, reshaping competition and innovation.

Waves, Not a Wall: Inside DeepMind’s Map From AGI to Superintelligence

DeepMind researchers publish a detailed framework outlining pathways from artificial general intelligence to superintelligence, emphasizing ongoing uncertainties.

Waves, Not a Wall: Inside DeepMind’s Map From AGI to Superintelligence

Inside DeepMind’s new framework mapping the path from artificial general intelligence to superintelligence, highlighting pathways, challenges, and uncertainties.

QAtrial: Compliance That Shows Its Work

QAtrial introduces an open-source platform ensuring AI assistance in life sciences complies with regulatory traceability and audit requirements.

China: The Visible Hand

China’s government-led approach accelerates AI, robotics, and industrial growth through direct state ownership and planning, contrasting with market-driven models.

Avengers Labs: How Ukraine Turned Its Front Line Into the World’s Scarcest AI Dataset

Ukraine’s Avengers Labs leverages battlefield drone data to train AI models, creating a unique and scarce defense resource amid ongoing conflict.

The Safety Card, Played From Every Side: David Sacks, Anthropic, and the Fable Standoff

White House official claims Anthropic refused to fix a jailbreak vulnerability, leading to model bans; Anthropic disputes the severity of the flaw.

Anthropic’s Safety Story Has Become a Power Story

Anthropic claims its AI systems are increasingly capable of self-improvement, raising questions about technological and political implications.

When AI Builds Itself: Inside Anthropic’s Evidence on Recursive Self-Improvement

Anthropic reports measurable acceleration in AI’s ability to develop itself, with data suggesting potential for recursive self-improvement if key gaps close.