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DARPA has tapped Raytheon to design and develop a wireless, airborne relay system to “deliver energy into contested environments,” as part of its Energy Web Dominance program, in which DARPA wants to be able to power anything from nearly anywhere.

Under a two-year, US$10 million DARPA contract, Raytheon will create a Persistent Optical Wireless Energy Relay (POWER) system, using a series of high altitude unmanned aircraft equipped with laser-based power receiving and transmitting capabilities. Energy will be beamed up to high altitude, then relayed across however many jumps are necessary to reach the target area.

That target might be on the ground, or it might itself be another autonomous aerial platform, in which case it could stay airborne as long as necessary, its batteries being constantly charged from afar.

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Artificial intelligence is more likely to save humanity than to destroy it, Jeff Bezos said recently. The billionaire also said he would like to see the human population grow to one trillion, with most people living in huge cylindrical space stations.

In an interview with podcaster Lex Fridman, the Amazon AMZN, +1.73% founder and former CEO rejected the idea that humans should colonize other planets, saying he believes building space colonies is the only way to achieve such population growth.

Japanese scientists said they have succeeded in creating the world’s first mental images of objects and landscapes from human brain activity by using artificial intelligence technology.

The team of scientists from the National Institutes for Quantum Science and Technology, another national institute and Osaka University was able to produce rough images of a leopard, with a recognizable mouth, ears and spotted pattern, as well as objects like an airplane with red lights on its wings.

The technology, dubbed “brain decoding,” enables the visualization of perceptual contents based on brain activity and could be applied to the medical and welfare fields.

A team of computer scientists at Google’s DeepMind project in the U.K., working with a colleague from the University of Wisconsin-Madison and another from Université de Lyon, has developed a computer program that combines a pretrained large language model (LLM) with an automated “evaluator” to produce solutions to problems in the form of computer code.

In their paper published in the journal Nature, the group describes their ideas, how they were implemented and the types of output produced by the new system.

Researchers throughout the scientific community have taken note of the things people are doing with LLMs, such as ChatGPT, and it has occurred to many of them that LLMs might be used to help speed up the process of scientific discovery. But they have also noted that for that to happen, a method is required to prevent confabulations, answers that seem reasonable but are wrong—they need output that is verifiable. To address this problem, the team working in the U.K. used what they call an automated evaluator to assess the answers given by an LLM.

Barry’s prowess is evident in tests, boasting a maximum payload-to-weight ratio of 2 on flat terrain.


Aiming to solve the challenge of legged robots still being “weak, slow, inefficient, or fragile to take over tasks that involve heavy payloads,” a team of researchers from the Robotic Systems Lab at ETH Zurich has developed a promising proposition.

Meet Barry, a dynamically balancing quadruped robot optimized for high payload capabilities and efficiency, which promises to help humans tackle challenging manual work scenarios. The quadruple’s new leg design ensures that it can “handle unmodeled payloads up to 198 pounds (90 kilograms) while operating at high efficiency,” according to a study by the team.

AI is making it easy for anyone to create propaganda outlets, producing content that can be hard to differentiate from real news.


Artificial intelligence is automating the creation of fake news, spurring an explosion of web content mimicking factual articles that instead disseminate false information about elections, wars and natural disasters.

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