Microsoft is finally saying farewell to WordPad. The company announced Friday that it plans to

Nasa has received a signal from a spacecraft 10 million miles away. The message, delivered using a distant laser, could “transform” communications with spacecraft, the space agency has said. It represents a successful test of Nasa’s Deep Space Optical Communications or DSOC experiment. It is also the first time that data has been successfully relayed through a laser from further away than the Moon – and marks a rapid increase, at more than 40 times the distance from the lunar surface. At the moment, almost all communications with craft in deep space is achieved through radio signals, sent and received from vast antennas on Earth. They have proven reliable but their bandwidth is limited, meaning that it is slow or impossible to send large files such as high-definition photos and videos. Nasa’s work on DSOC is an attempt to use optical communications through lasers instead. The technology could improve data rates by as much as 100 times, the space agency says. The first attempt to test the technology beyond the Moon left the Earth on Nasa’s Psyche mission, which left Earth last month on a mission to study a distant asteroid. The spacecraft is carrying a laser transceiver than can both send and receive laser signals in near-infrared. Last week, that equipment locked onto a Nasa laser beacon in California. Nasa says that “first light” breakthrough is one part of a host of experiments that they hope will prove the laser technology can work. “Achieving first light is one of many critical DSOC milestones in the coming months, paving the way toward higher-data-rate communications capable of sending scientific information, high-definition imagery, and streaming video in support of humanity’s next giant leap: sending humans to Mars,” said Trudy Kortes, director of technology demonstrations for the Space Technology Mission Directorate at Nasa Headquarters in Washington. Nasa likens the precision pointing of the laser signal to trying to point a light at a coin from a mile away. What’s more, the laser and its target are constantly moving: in the 20 minutes it will take for the light to travel to Earth from Psyche’s furthest distance, both the planet and the spacecraft will have moved significantly. The team will now work to refine the systems that ensure the spacecraft is pointing its lasers in the right direction. When that happens, Nasa will try an experiment to demonstrate that the spacecraft is able to maintain high-bandwidth data transfer at different distances from Earth. It will do so by breaking the data into bits that can be encoded in the photons of light sent by the spacecraft. That light then arrives at the telescope on Earth and can be reassembled into images or other important data that will be sent by spacecraft – and perhaps humans – in the future. Read More SpaceX hints next Starship launch attempt could be soon SpaceX to launch world’s biggest rocket again after first attempt ended in explosion Nasa spots collection of shocking materials on distant planet

Prime Minister Justin Trudeau’s government plans to unveil its proposal to cap oil and gas emissions this fall,

Artificial intelligence is now on the agenda as world leaders, climate diplomats and thousands of others descend on

As teams play through the first week of the FIFA Women's World Cup™, which kicked

WASHINGTON New draft guidelines released by U.S. antitrust enforcers on Wednesday lay the groundwork for tougher scrutiny of

The biggest oil producer in the United Arab Emirates is setting itself more ambitious emissions-reduction targets as the

SALT LAKE CITY--(BUSINESS WIRE)--May 10, 2023--

Posco, one of the world’s top steelmakers, would need to consider moving some of its most energy-intensive manufacturing

ChatGPT’s creators have attempted to get the system to explain itself. They found that while they had some success, they ran into some issues – including the fact that artificial intelligence may be using concepts that humans do not have named for, or understanding of. Researchers at OpenAI, which developed ChatGPT, used the most recent version of its model known as GPT-4 to try and explain the behaviour of GPT-2, an earlier version. It is an attempt to overcome the so-called black box problem with large language models such as GPT. While we have a relatively good understanding of what goes into and comes out of such systems, the actual work that goes on inside remains largely mysterious. That is not only a problem because it makes things difficult for researchers. It also means that there is little way of knowing what biases might be involved in the system, or if it is providing false information to people using it, since there is no way of knowing how it came to the conclusions it did. Engineers and scientists have aimed to resolve this problem with “interpretability research”, which seeks find ways to look inside the model itself and better understand what is going on. That has often required looking at the “neutrons” that make up such a model: just like in the human brain, an AI system is made up of a host of so-called neutrons that represent parts of the data it uses. Finding those is difficult, however, since humans have had to pick through the neurons and manually inspect them to find out what they represent. But some systems have hundreds of billions of parameters and so actually getting through them all with people is impossible. Now, researchers at OpenAI have looked to use GPT-4 to automate that process, in an attempt to more quickly pick through the behaviour. They did so by attempting to create an automated process that would allow the system to provide natural language explanations of the neuron’s behaviour – and apply that to another, earlier language model. That worked in three steps: looking at the neuron in GPT-2 and having GPT-4 try and explain it, then simulating what that neuron would, and finally scoring that explanation by comparing how the simulated activation worked with the real one. Most of those explanations went badly, and GPT-4 scored itself poorly. But researchers said that they hoped the experiment showed that it would be possible to use the AI technology to explain itself, with further work. The creators came up against a range of “limitations”, however, that mean the system as it exists now is not as good as humans at explaining the behaviour. Part of the problem may be that explaining how the system is working in normal language is impossible – because the system may be using individual concepts that humans cannot name. “We focused on short natural language explanations, but neurons may have very complex behavior that is impossible to describe succinctly,” the authors write. “For example, neurons could be highly polysemantic (representing many distinct concepts) or could represent single concepts that humans don’t understand or have words for.” It also runs into problems because it is focused on specifically what each neuron does individually, and not how that might affect things later on in the text. Similarly, it can explain specific behaviour but not what mechanism is producing that behaviour, and so might spot The system also uses a lot of computing power, the researchers note. Read More Google to unveil major new AI AI robots figure out how to play football in shambolic footage White House asks hackers to break ChatGPT White House reveals plan to ‘protect’ citizens from danger of AI DeepMind boss says human-level AI is just a few years away Regulator to probe use of artificial intelligence such as ChatGPT

CAMARILLO, Calif.--(BUSINESS WIRE)--Aug 1, 2023--

South Africa’s supply of natural gas is set to plunge within the next three to four years and