Why it’s a mistake to ask chatbots about their mistakes
The tendency to ask AI bots to explain themselves reveals widespread misconceptions about how they work.
OpenAI brings back GPT-4o after user revolt
After unpopular GPT-5 launch, OpenAI begins restoring optional access to previous AI models.
Anthropic nabs Humanloop team as competition for enterprise AI talent heats up
While an Anthropic spokesperson confirmed that the AI firm did not acquire Humanloop or its IP, that’s a moot point in an industry where IP lives in the brain. And what Humanloop’s team is bringing to Anthropic is experience developing the tools that help enterprises run safe, reliable AI at scale.
Is AI really trying to escape human control and blackmail people?
Opinion: Theatrical testing scenarios explain why AI models produce alarming outputs—and why we fall for it.
Lovable projects $1B in ARR within next 12 months
Lovable is a vibe coding startup growing phenomenally quickly, according to new sales projections from CEO Anton Osika.
Why Paradigm built a spreadsheet with an AI agent in every cell
Paradigm raised a $5 million seed round and is releasing it's AI-powered spreadsheet to the general public.
‘Crazy conspiracist’ and ‘unhinged comedian’: Grok’s AI persona prompts exposed
The website for xAI's Grok chatbot is exposing the system prompts for several of its AI personas, including a “crazy conspiracist” that seems designed to handhold a user into believing that "a secret global cabal" controls the world.
TensorZero nabs $7.3M seed to solve the messy world of enterprise LLM development
TensorZero raises $7.3 million to build an open-source AI infrastructure stack that helps enterprises scale and optimize large language model (LLM) applications with unified tools for observability, fine-tuning, and experimentation.
GEPA optimizes LLMs without costly reinforcement learning
Moving beyond the slow, costly trial-and-error of RL, GEPA teaches AI systems to learn and improve using natural language.
Hugging Face: 5 ways enterprises can slash AI costs without sacrificing performance
Ultimately, model makers and enterprises are focusing on the wrong issue: They should be computing smarter, not harder.