Enlarge / The VISIR instrument before its impending upgrades. (credit: ESO ) Today, the European Southern Observatory announced an agreement with Breakthrough Starshot, the group dedicated to sending hardware to return data from the nearest stars. The agreement would see Breakthrough Starshot fund the development of new hardware that would allow the ESO’s Very Large Telescope to become an efficient planet hunter. The goal is presumably to confirm there’s something in the Alpha Centauri system worth sending hardware to image. Breakthrough Starshot’s audacious plan involves using ground-based lasers and light sails to accelerate tiny craft to a significant fraction of the speed of light. This would allow the craft to visit the stars of the Alpha Centauri system within decades. The company’s goal is to get data back to Earth while many of the people alive today are still around. Getting meaningful data requires a detailed understanding of the Alpha Centauri system, which is where the new telescope hardware will come in. Last year, scientists confirmed the existence of an exoplanet orbiting the closest star of the three-star system, Proxima Centauri. But we’ll want to know significantly more about it, its orbit, and whether there are signs of any other planets in the system before we send spacecraft. The other two stars of Alpha Centauri are also worth a closer look. Read 5 remaining paragraphs | Comments
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Breakthrough Starshot to fund planet-hunting hardware for telescope
A new AI tool created by Google and Oxford University researchers could significantly improve the success of lip-reading and understanding for the hearing impaired. In a recently released paper on the work, the pair explained how the Google DeepMind-powered system was able to correctly interpret more words than a trained human expert. From a report: To accomplish the task, a cohort of scientists fed thousands of hours of TV footage — 5000 to be precise — from the BBC to a neural network. It was made to watch six different TV shows, which aired between the period of January 2010 and December 2015. This included 118, 000 difference sentences and some 17, 500 unique words. To understand the progress, it successfully deciphered words with a 46.8 percent accuracy. The neural network had to recognize the same based on mouth movement analysis. The under 50 percent accuracy might seem laughable to you but let me put things in perspective for you. When the same set of TV shows were shown to a professional lip-reader, they were able to decipher only 12.4 percent of words without error. Thus, one can understand the great difference in the capability of the AI as compared to a human expert in that particular field. Read more of this story at Slashdot.