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The UK is considering plans to launch a satellite navigation system as a rival to the EU's Galileo project. The move comes after the UK was told it would be shut out of key elements of the programme after Brexit. The UK has spent 1,4bn euros (£1.2bn) on Galileo, which is meant to be Europe's answer to the US GPS system. Business Secretary Greg Clark is taking legal advice on whether the UK can reclaim the cash, according to the Financial Times. He told BBC News: "The UK's preference is to remain in Galileo as part of a strong security partnership with Europe.
Funding for the UK's own satellite navigation system to rival the European Union's Galileo project is expected to be announced. It comes after the UK was told it would not be able to access the EU-wide programme after Brexit next March. At least £92m has been promised by the Treasury to plan for a UK system, a government official has told the BBC. The UK has already spent 1.4bn euros (£1.2bn) on Galileo, Europe's answer to the US GPS system. Costs for a UK-only sat-nav system are likely to run to several billion pounds.
Computers can be taught to understand many things about the world, but when it comes to predicting what will happen when two objects collide, there's just nothing like real-world experience. That's where Galileo comes in. Developed by MIT's Computer Science and Artificial Intelligence Lab (CSAIL), the new computational model has proven to be just as accurate as humans are at predicting how real-world objects move and interact. Ultimately, it could help robots predict events in disaster situations and help humans avoid harm. Humans learn from their earliest days -- often through bumps, bruises and painful experience -- how physical objects interact.
The Multimission VICAR Planner (MVP) system is an AI planning system which constructs executable image processing programs to support Operational Science Analysis (OSA) requests made to the Jet Propulsion Laboratory (JPL) Multimission Image Processing Subsystem (MIPS). MVP accepts as input: image files and a high-level specification of desired corrections, enhancements, output properties (such as for mosaics). MVP then derives: unspecified but required processing steps, relevant image processing library programs, and appropriate parameter settings for such programs - constructing an executable image processing program to fill the image processing request. MVP is currently available to analysts to fill requests and reduces the effort to fill radiometric correction, color triplet reconstruction, and mosaicking tasks by over an order of magnitude.