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JERUSALEM, Dec 26 (Reuters) — Israel’s government agreed to give Intel (INTC.O) a $3.2 billion grant for a new $25 billion chip plant it plans to build in southern Israel, both sides said on Tuesday, in what is the largest investment ever by a company in Israel.

The news comes as Israel remains locked in a war with Palestinian militant group Hamas in the wake of the Oct. 7 Hamas attack on Israel. It also is a big show of support by a major U.S. company and a generous offer by Israel’s government at a time when Washington has increased pressure on Israel to take further steps to minimise civilian harm in Gaza.

Shares of Intel, which has a bit less than 10% of its global workforce in Israel, opened up 2.73% at $49.28 on Nasdaq.

A lot of AI GPUs consume a lot of power.

The optimal choice of hypothesis is the weakest not the shortest.

Shared with Dropbox.

The processors of most computers work in series, performing one instruction at a time. This limits their ability to perform certain types of tasks in a reasonable period. An approach based on arrays of simultaneously interacting molecular switches could enable previously intractable computational problems to be solved.

Black holes are some of the most powerful objects in the universe — and humans could devise ways to harness that power as an energy source, a new theoretical study claims.

Researchers have experimentally demonstrated how to harness a property called negative capacitance for a new type of transistor that could reduce power consumption, validating a theory proposed in 2008 by a team at Purdue University.

The researchers used an extremely thin, or 2-D, layer of the semiconductor molybdenum disulfide to make a channel adjacent to a critical part of transistors called the gate. Then they used a “ferroelectric material” called hafnium zirconium oxide to create a key component in the newly designed gate called a negative capacitor.

Capacitance, or the storage of electrical charge, normally has a positive value. However, using the ferroelectric material in a transistor’s gate allows for negative capacitance, which could result in far lower power consumption to operate a transistor. Such an innovation could bring more efficient devices that run longer on a battery charge.

A computer chip processes and stores information using two different devices. If engineers could combine these devices into one or put them next to each other, then there would be more space on a chip, making it faster and more powerful.

Purdue University engineers have developed a way that the millions of tiny switches used to process information—called transistors—could also store that information as one device.

The method, detailed in a paper published in Nature Electronics, accomplishes this by solving another problem: combining a transistor with higher-performing memory technology than is used in most computers, called ferroelectric RAM.

One of the most actively debated questions about human and nonhuman culture is this: Under what circumstances might we expect culture, in particular the ability to learn from one another, to be favored by natural selection?

Researchers at the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany, have developed a simulation model of the evolution of social learning. They showed that the interplay between learning, memory and forgetting broadens the conditions under which we expect to see social learning to evolve.

Social learning is typically thought to be most beneficial when the environments in which individuals live change quite slowly—they can safely learn tried and tested information from one another and it does not go out of date quickly. Innovating brand-new information, on the other hand, is thought to be useful in dynamic and rapidly changing environments.

To effectively assist humans in real-world settings, robots should be able to learn new skills and adapt their actions based on what users require them to do at different times. One way to achieve this would be to design computational approaches that allow robots to learn from human demonstrations, for instance observing videos of a person washing dishes and learning to repeat the same sequence of actions.

Researchers at University of British Columbia, Carnegie Mellon University, Monash University and University of Victoria recently set out to gather more reliable data to train robots via demonstrations. Their paper, posted to the arXiv preprint server, shows that the data they gathered can significantly improve the efficiency with which robots learn from the demonstrations of human users.

“Robots can build cars, gather the items for shopping orders in busy warehouses, vacuum floors, and keep the hospital shelves stocked with supplies,” Maram Sakr, one of the researchers who carried out the study, told Tech Xplore. “Traditional robot programming systems require an expert programmer to develop a robot controller that is capable of such tasks while responding to any situation the robot may face.”