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The Euclid space telescope has revealed its first full-colour images, showing the universe as it has never been seen before. The five images, taken by the European Space Agency’s newly launched flying observatory, show the shining lights of distant galaxies. Scientists hope they will also prove useful in better understanding those galaxies, which includes some of the most massive structures in the known universe. Many of the galaxies have never been seen before. And much of the information in them could help explain mysteries such as dark energy and the expansion of the universe. The images released on Tuesday include one of the Perseus cluster of galaxies which shows 1,000 galaxies belonging to the cluster, and more than 100,000 additional galaxies further away in the background. Many of these faint galaxies were previously unseen, and some of them are so far that their light has taken 10 billion years to reach us. Another image captures the spiral galaxy IC 342, nicknamed the Hidden Galaxy, because it is difficult to observe as it lies behind the busy disc of our Milky Way, and so dust, gas and stars obscure our view. One of the new pictures is of globular cluster NGC 6397 - the second-closest globular cluster to Earth, located about 7,800 light-years away. Globular clusters are collections of hundreds of thousands of stars held together by gravity. These faint stars tell us about the history of the Milky Way and where dark matter is located. To create a 3D map of the universe, Euclid will observe the light from galaxies out to 10 billion light-years. The first irregular dwarf galaxy that Euclid observed is called NGC 6822 and is located just 1.6 million light-years from Earth. And the fifth image shows a panoramic and detailed view of the Horsehead Nebula, also known as Barnard 33 and part of the constellation Orion. Scientists hope to find many dim and previously unseen Jupiter-mass planets in their celestial infancy, as well as young brown dwarfs and baby stars, in this new observation. Professor Carole Mundell, ESA director of science, said: “Dark matter pulls galaxies together and causes them to spin more rapidly than visible matter alone can account for; dark energy is driving the accelerated expansion of the universe. “Euclid will for the first time allow cosmologists to study these competing dark mysteries together. “Euclid will make a leap in our understanding of the cosmos as a whole, and these exquisite Euclid images show that the mission is ready to help answer one of the greatest mysteries of modern physics.” Rene Laureijs, the ESA’s Euclid project scientist, said: “We have never seen astronomical images like this before, containing so much detail. “They are even more beautiful and sharp than we could have hoped for, showing us many previously unseen features in well-known areas of the nearby universe. “Now we are ready to observe billions of galaxies, and study their evolution over cosmic time.” Euclid was launched on a SpaceX Falcon 9 rocket from Cape Canaveral in Florida on July 1. Named after the ancient Greek mathematician Euclid, the two-tonne probe made its way towards an area in space known as the second Lagrange point, where the gravitational forces of Earth and the sun are roughly equal - creating a stable location for the spacecraft. The UK has contributed £37 million towards the £850 million mission, with scientists playing key roles in designing and building the probe and leading on one of the two scientific instruments on board. Dr Caroline Harper, head of space science at the UK Space Agency, said: “These first colour images showcase Euclid‘s enormous potential, giving us incredibly sharp images of galaxies and stars, and helping us understand more about the impacts of dark matter and dark energy on the universe. “The UK has played an important role in the mission, leading on the development of the visible imager (VIS) instrument and on key elements of the data processing pipeline, funded by the UK Space Agency. “And this is just the start - UK researchers will be using Euclid data for many years to come to make significant new scientific discoveries about the composition and evolution of the cosmos.” Additional reporting by Press Association Read More Euclid space telescope releases first full-colour images of cosmos First full-colour images of universe captured by Euclid telescope revealed Watch again: ESA reveals first full-colour images of ‘dark universe’ from Euclid Tim Peake: Possibility of all-UK space mission a ‘very exciting development’ Strange purple light phenomenon ‘Steve’ spotted across UK skies Nasa sending VR headset up to ISS to treat astronaut’s mental health

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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