backed plasticity is tackling the problem

28. srpna 2018 v 11:15
  Y Combinator backed plasticity is tackling the problem of getting software systems to better understand text, using deep learning models trained to understand what they're reading on Wikipedia articles - and offering an ApI for developers to enhance their own interfaces.
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  Specifically they're offering two ApIs for developers to build "more robust conversational interfaces", as they put it - with the aim of becoming a "centralized solution" for Natural Language processing (NLp). Their ApIs are due to be switched from private to public beta on Monday.
  "One thing where we think this is really useful for is conversational interfaces where you want to integrate real world knowledge," says co-founder Alex Sands. "We think it's also really useful when you want to provide instant answers in your application - whether that's over the entire Internet or over a custom corpus."
  One example might be search engines that are competing with Google and don't have their own instant answer technology. "[They] could use something like this. We're in talks with a few of them," notes Sands.
  "The other application is conversational interfaces who want a new NLp stack that will give them a lot more information than what an academic package like Stanford CoreNLp would provide them today," he adds.
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  A few years back, the founders worked on a hack project that expanded the powers of Apple's AI voice assistant Siri, by adding support for custom commands - such as playing a Spotify track or dialing up the temperature via a Nest device. This was before Apple opened up Siri to third party apps so they were routing voice commands through a proxy - and claim to have basically built "the first app store for voice commands".
  The experience taught them that "NLp in general is not robust" for handling more complex commands and queries, says other co-founder Ajay patel.
  "The other problem was a lot of the natural language processing tools out there really take a simplistic approach to understanding what a user says," he adds. "The most simplistic way to explain it is they're looking for keywords to figure out what a user is asking."
  plasticity is taking a different approach vs these keyword-based NLp systems; building a system that understands the semantics of a sentence so it can perform a linguistic breakdown - "to figure out all of the relationships and entities in a sentence".
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  They can then hand that information to developers so they can build "more robust conversational interfaces around it", as patel puts it - such as, for example, a chatbot that's more conversational and capable, given it can serve up answers it found online.
 

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