Recursive self-improvement AI now has a co-evolving evaluator: a Cambridge and NVIDIA preprint introduces the Red Queen Gödel ...

Alex L. Zhang was 13 years old when he published a video game that went viral. More than 100,000 people bought the game for ...

https://www.thehindubusinessline.com/info-tech/llm-collapse-the-danger-of-training-llms-on-ai-generated-data/article71094267.ece Copy What happens when a new ...

One of the world’s leading artificial intelligence companies has implored the industry to pause development on AI, because the latest models could be reaching a tipping point where they become capable ...

The companies at the frontier of artificial intelligence should be ready to slow down, one of the fastest-moving among them says. Anthropic, the maker of the Claude chatbot, has claimed AI systems may ...

One of the key challenges of current multi-agent AI systems is that they communicate by generating and sharing text sequences, which introduces latency, drives up token costs, and makes it difficult ...

Richard Socher's new $650 million startup wants to build an AI that can research and improve itself indefinitely — and he insists it will actually ship products.

Penn researchers have developed a smarter AI method for solving notoriously difficult inverse equations, which help scientists uncover hidden causes behind observable effects. By introducing ...

Jack Clark argues in a long essay that the building blocks for AI systems training their own successors are largely in place. He puts the odds at 60 percent by the end of 2028. In his newsletter ...

Penn Engineers have developed a new way to use AI to solve inverse partial differential equations (PDEs), a particularly challenging class of mathematical problems with broad implications for ...

Abstract: Particle Flow Filters estimate the “a posteriori” probability density function (PDF) by moving an ensemble of particles according to the likelihood. Particles are propagated under the system ...

Creating self-improving AI systems is an important step toward deploying agents in dynamic environments, especially in enterprise production environments, where tasks are not always predictable, nor ...