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Category: robotics/AI – Page 382

CWM: An Open-Weights LLM for Research on Code

We release Code World Model (CWM), a 32-billion-parameter open-weights LLM, to advance research on code generation with world models. To improve code understanding beyond what can be learned from training on static code alone, we mid-train CWM on a large amount of observation-action trajectories from Python interpreter and agentic Docker environments, and perform extensive multi-task reasoning RL in verifiable coding, math, and multi-turn software engineering environments. With CWM, we provide a strong testbed for researchers to explore the opportunities world modeling affords for improving code generation with reasoning and planning in computational environments. We present first steps of how world models can benefit agentic coding, enable step-by-step simulation of Python code execution, and show early results of how reasoning can benefit from the latter.

Google’s top AI scientist says ‘learning how to learn’ will be next generation’s most needed skill

Speaking at an ancient Roman theater at the foot of the Acropolis in Athens, Demis Hassabis, CEO of Google’s DeepMind, said rapid technological change demands a new approach to learning and skill development.

“It’s very hard to predict the future, like 10 years from now, in normal cases. It’s even harder today, given how fast AI is changing, even week by week,” Hassabis told the audience. “The only thing you can say for certain is that huge change is coming.”

The neuroscientist and former chess prodigy said artificial general intelligence—a futuristic vision of machines that are as broadly smart as humans or at least can do many things as well as people can—could arrive within a decade. This, he said, will bring dramatic advances and a possible future of “radical abundance” despite acknowledged risks.

AI chips are getting hotter. A microfluidics breakthrough goes straight to the silicon to cool up to three times better

AI is hot – literally.

The chips that datacenters use to run the latest AI breakthroughs generate much more heat than previous generations of silicon. Anybody whose phone or laptop has overheated knows that electronics don’t like to get hot. In the face of rising demand for AI and newer chip designs, the current cooling technology will put a ceiling on progress in just a few years.

To help address this problem, Microsoft has successfully tested a new cooling system that removed heat up to three times better than cold plates, an advanced cooling technology commonly used today. It uses microfluidics, an approach that brings liquid coolant directly inside the silicon – where the heat is. Tiny channels are etched directly on the back of the silicon chip, creating grooves that allow cooling liquid to flow directly onto the chip and more efficiently remove heat. The team also used AI to identify the unique heat signatures on a chip and direct the coolant with more precision.

Piecing together the puzzle of future solar cell materials

Global electricity use is increasing rapidly and must be addressed sustainably. Developing new materials could give us much more efficient solar cell materials than at present; materials so thin and flexible that they could encase anything from mobile phones or entire buildings.

Using computer simulation and , researchers at Chalmers University of Technology in Sweden have now taken an important step toward understanding and handling halide perovskites, among the most promising but notoriously enigmatic materials.

Electricity use is constantly increasing globally and, according to the International Energy Agency, its proportion of the world’s total energy consumption is expected to exceed 50% in 25 years, compared to the current 20%.