OpenAI, Anthropic, and DeepMind accelerate automation of AI development itself, with tools now writing up to 90% of code at some firms, raising questions about capability acceleration.
Insiders from OpenAI, Google, and Microsoft describe systems becoming harder to govern, while U.S. polling shows majority now expects AI to cause harm.
Security experts warn that artificial intelligence has eliminated the detection buffer organizations once relied on, with attackers now exploiting vulnerabilities the moment they surface.
The company disclosed that enterprise clients now account for over 40% of revenue, with APIs processing 15 billion tokens per minute as agentic workflows drive adoption.
A decade after defeating Lee Sedol, DeepMind's dual-model architecture and self-play methods are now embedded in reasoning systems at OpenAI, Anthropic, and beyond.
From Indian agriculture to UK fintech, organizations struggle to operationalize AI not for lack of algorithms, but due to fragmented data systems and risk aversion.
Peer-reviewed research warns that rapid deployment of commercial large language models in defense operations may erode personnel judgment and targeting accuracy.
Researchers at Université de Genève developed MangroveGS, an AI system that predicts cancer spread by identifying genetic signals, challenging the assumption that metastasis is random.
