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Sunday, January 17, 2021

Improving Language AI

Improving, heating up, getting more useful.   But I still think there are considerable problems with not only interpreting/delivering language, but also managing multiple element conversations that refer to particular and changing context.   This is the nature of human intelligence.   Siri, Echo, Google and Watson quickly reveal they cannot do this.  So  they rely on us to fill in the unknowns. Is it really improving? 

Language AI is really heating up   in Venturebeat   By Pieter Buteneers, Sinch

January 17, 2021 10:25 AM

In just a short number of years, deep learning algorithms have evolved to be able to beat the world’s best players at board games and recognize faces with the same accuracy as a human (or perhaps even better). But mastering the unique and far-reaching complexities of human language has proven to be one of AI’s toughest challenges.

Could that be about to change?

The ability for computers to effectively understand all human language would completely transform how we engage with brands, businesses, and organizations across the world. Nowadays most companies don’t have time to answer every customer question. But imagine if a company really could listen to, understand, and answer every question — at any time on any channel? My team is already working with some of the world’s most innovative organizations and their ecosystem of technology platforms to embrace the huge opportunity that exists to establish one-to-one customer conversations at scale. But there’s work to do.

It took until 2015 to build an algorithm that could recognize faces with an accuracy comparable to humans. Facebook’s DeepFace is 97.4% accurate, just shy of the 97.5% human performance. For reference, the FBI’s facial recognition algorithm only reaches 85% accuracy, meaning it is still wrong in more than one out of every seven cases.  .. "

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