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Stanford University’s latest AI Index Report reveals that while the AI performance rivalry between the US and China has nearly evened out, significant gaps in AI safety and responsible AI practices remain, raising concerns about the future of AI governance and public trust.
Anthropic’s co-founder Jack Clark detailed the company’s ongoing communications with U.S. government officials, including the Trump administration, regarding its AI system Mythos, even as the company pursues legal action against the government.
YouTube is introducing a new approach to advertising on livestreams by delaying ads during high-engagement periods to maintain viewer experience without requiring a Premium subscription.
Pillar, a financial risk management platform, has raised $20 million in a seed round led by a16z, aiming to democratize institutional-grade hedging tools for small and medium-sized enterprises.
Anthropic’s latest AI model, Claude Mythos Preview, has discovered thousands of cybersecurity vulnerabilities across major operating systems and browsers. Instead of public release, the company has partnered with key organizations to address these threats through Project Glasswing.
Security researchers have uncovered that several popular WordPress plugins were compromised with backdoors after ownership changes, leading to malware distribution across numerous websites.
Anthropic’s latest AI model, Claude Mythos Preview, has identified thousands of critical cybersecurity flaws across major operating systems and browsers. Instead of public release, the model is being shared selectively with key internet infrastructure organizations to enhance security.
Waymo has commenced testing its autonomous robotaxi service in London, moving closer to launching the city’s first commercial driverless taxi, pending UK government approval.
As the EU AI Act enforcement begins in August 2026, organizations deploying agentic AI systems face significant governance challenges. Ensuring traceability, human oversight, and compliance with strict regulatory requirements will be crucial to avoid penalties in high-risk AI applications.
IBM stresses that as AI evolves from standalone tools to foundational enterprise infrastructure, strong governance and open-source approaches are essential to manage risks, ensure operational resilience, and safeguard profit margins.