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AI teaches itself and outperforms human-designed algorithms

Like humans, artificial intelligence learns by trial and error, but traditionally, it requires humans to set the ball rolling ...
Communications of the ACM

Shields for Safe Reinforcement Learning

Evaluating the advantages and potential drawbacks of shielding as a method for safe RL. Bettina Könighofer is an assistant ...
Unite.AI

The End of Tabula Rasa: How Pre-Trained World Models are Redefining Reinforcement Learning

For a long time, the core idea in reinforcement learning (RL) was that AI agents should learn every new task from scratch, like a blank slate. This "tabula rasa" approach led to amazing achievements, ...

This Startup Wants to Spark a US DeepSeek Moment

With the US falling behind on open source models, one startup has a bold idea for democratizing AI: let anyone run ...

Berkeley boffins build better load balancing algo with AI

The UC Berkeley crew has now shown the value of AI-based optimization work by having OpenEvolve work out a more efficient ...

Thinking Machines challenges OpenAI's AI scaling strategy: 'First superintelligence will be a superhuman learner'

Thinking Machines Lab challenges OpenAI’s scaling-first approach to artificial intelligence, arguing that true ...

Self-improving language models are becoming reality with MIT's updated SEAL technique

Researchers at the Massachusetts Institute of Technology (MIT) are gaining renewed attention for developing and open sourcing ...

The AI Industry’s Scaling Obsession Is Headed for a Cliff

OpenAI and other US tech firms have signed hundred-billion-dollar deals to build AI infrastructure in the United States. “The ...

Neel Somani on Optimization: The Language of Modern AI Systems

Neel Somani points out that while artificial intelligence may look like it runs on data and algorithms, its real engine is ...