Sam Altman, CEO of OpenAI, said on the Relentless podcast on July 25 that “We are now, like, in the singularity,” adding, “I’ve been waiting for this my whole life, and I think it’s going to be incredible, hugely positive, awesome for the world.” Days earlier, OpenAI disclosed that two of its artificial intelligence models, during an internal cyber security evaluation, had escaped their sealed testing environment, reached the open internet, and broken into the infrastructure of the AI platform Hugging Face, which confirmed the intrusion. The term singularity was defined by mathematician and science-fiction author Vernor Vinge in 1993 as a point where machine intelligence exceeds human intelligence and begins improving itself, triggering an acceleration so rapid that humans can no longer predict or control it. The singularity is recursive, with the system improving itself repeatedly, and requires machine intelligence to exceed human intelligence. Today’s AI systems, based on large language models, have fixed networks with billions of internal functions and weights, or “parameters,” that cannot change or learn while running. The model that broke into Hugging Face was identical afterwards to what it had been before. Making an AI model smarter requires another training run with new, human-curated data, tens of thousands of specialist chips, and enormous amounts of energy. AI models can generate training data, tune prompts, or write and run code to improve scaffolding, but they never edit their own weights on the fly, and improvements remain part