Spooky entanglement revealed between quantum AI and the BBC

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Spooky entanglement revealed between quantum AI and the BBC
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QC: Still not actually useful, but it's increasingly intriguing

The UK's national broadcaster, the BBC, its R&D team and its entire 100-year, 15 million item archive are part of a new consortium investigating QNLP, Quantum Natural Language Processing, with the ultimate aim of automating the extraction of meaning from humanity's babble.

"The most incomprehensible thing about the universe is that it's comprehensible," is one of those rare Einstein quotes that Einstein actually said. We don't know what he might have said aboutas he died 14 years before its first transmission. But it is fascinating to wonder what he, as one of the founders of quantum physics, might have made of the idea of quantum computing signposting why the universe is comprehensible in the first place.

The consortium, announced on November 25, receives funding from the Royal Academy of Engineering, and will build on work on quantum mechanics and linguistics by Professor Bob Coecke, chief scientist at UK QC company Quantinuum; Professor Stephen Clark, head of AI at Cambridge Quantum; and Professor Mehrnoosh Sadrzadeh of the Computer Science department at University College London. Two geeks in a garage it is not.

Long-term followers of the quantum computing news will know that every story about QC exists mostly in the future tense: the technology is more promise than product. It is limited by the current state of the art, noisy intermediate-scale quantum or NISQ. Current systems are too noisy and too small to be useful. Much of today's QC research is in developing techniques and algorithms that will be world-beating, once we're out of NISQ and into fault-tolerant, large-scale systems.

What makes it interesting is where it's come from. The professorial collaborators and their teams have 15 years of research under their belts in analyzing language. One result of which is the splendidly named DISCOCAT framework, which creates a data set from groups of sentences that can be analysed on a quantum system. The inherently interesting part of this is that DISCOCAT produces a tensor network that maps very closely to how quantum logic naturally works.

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