A kind of admission that its hard to create general answers to questions? Further relating to my last post about this kind of approach. Do note its similarity to what you get with Google search, linking to previous questions with similar keywords and structure. I have noted recently an increased number of answers to questions. Attribution indication also interesting.
Amazon Alexa is beta testing crowdsourced answers
Customers in the invitation-only program can start contributing answers to Alexa today By Dami Lee@dami_lee in TheVerge.
Amazon announced recently that it’s beta testing Alexa Answers, an invitation-only program for users to add responses for questions that Alexa can’t answer. Amazon says that in the last month of its internal Alexa Answers beta program, 100,000 responses have been added and served to customers “millions of times.”
Starting today, selected customers who have received email invitations can participate via the Alexa Answers website. Users can browse through various topic categories, like science and geography, and choose to answer questions that have been asked by other customers that Alexa doesn’t know the answers to. Those answers may then be served to other Alexa customers, and their answer will be attributed to “an Amazon customer.” ... "
Showing posts with label Followup Questions. Show all posts
Showing posts with label Followup Questions. Show all posts
Thursday, January 03, 2019
Google Acquires Superpod
Relating to an examination of improved question and answer interacton.
Google secretly acquires Q&A startup Superpod
By Maria Deutscher in SiliconAngle
Google LLC usually publicizes its acquisitions, but there are exceptions.
The search giant has secretly bought a startup called Superpod Inc. that developed a crowdsourced question-and-answer app in the same vein as Quora. Axios broke the news this morning, citing an unnamed source, and a Google spokesperson confirmed the deal.
The tipster told the publication that the search giant paid less than “less than $60 million” for Superpod. Even if the actual deal size was only a fraction of that figure, it still represents an impressive exit for the Palo Alto, California-based startup. Superpod launched its app into private beta only about a year ago and didn’t attract much in the way of public attention during its brief run.
The startup shut down the service in September, which is presumably when the acquisition was signed. Superpod co-founders Sophia Yang and William Li hinted at the deal in a note still up on the startup’s website. ... "
Google secretly acquires Q&A startup Superpod
By Maria Deutscher in SiliconAngle
Google LLC usually publicizes its acquisitions, but there are exceptions.
The search giant has secretly bought a startup called Superpod Inc. that developed a crowdsourced question-and-answer app in the same vein as Quora. Axios broke the news this morning, citing an unnamed source, and a Google spokesperson confirmed the deal.
The tipster told the publication that the search giant paid less than “less than $60 million” for Superpod. Even if the actual deal size was only a fraction of that figure, it still represents an impressive exit for the Palo Alto, California-based startup. Superpod launched its app into private beta only about a year ago and didn’t attract much in the way of public attention during its brief run.
The startup shut down the service in September, which is presumably when the acquisition was signed. Superpod co-founders Sophia Yang and William Li hinted at the deal in a note still up on the startup’s website. ... "
Monday, September 03, 2018
Dealing with Followup Questions in Alexa
How can we deal with common expectations of conversation, like followup questions? See the reference to the upcoming paper. The blog linked to often has interesting, but technical results. Still, often useful to scan, since these are aimed at skill and architecture developers, to understand the difficulty involved. Also, how much context is meant to be in memory for followup?
Amazon researchers share how AI helps Alexa answer follow-up questions By Kyle Wiggers in VentureBeat
Humans have an easy time with context carryover — the ability to track references through rounds of conversation (like inferring the meaning of “there” in a follow-up to “How is the weather in San Francisco?”) — but it’s beyond the conversational repertoire of most smart speakers and virtual assistants. That’s nothing a little artificial intelligence (AI) can’t fix, though, and in a blog post today researchers at Amazon wrote about the progress they’ve made with Alexa.
During a typical chat with Alexa, users invoke multiple apps — skills, in Amazon’s parlance — in successive questions. Currently, Alexa analyzes the content of each query according to its domain (type of skill), intent (function of the skill), and slot (a variable the skill acts upon). But skills often repurpose slots like “town” and “city,” which poses an obvious problem — if a user asks for directions and follows up with a question about a restaurant’s location, how’s Alexa to know which thread to reference in its answer?
Gupta and colleagues describe a solution in the paper “Contextual Slot Carryover for Disparate Schemas,” a neural network that automatically learns to map one skill’s slots to another’s. The findings will be presented at the upcoming Interspeech conference in Hyderabad, India in September. .... "
Amazon researchers share how AI helps Alexa answer follow-up questions By Kyle Wiggers in VentureBeat
Humans have an easy time with context carryover — the ability to track references through rounds of conversation (like inferring the meaning of “there” in a follow-up to “How is the weather in San Francisco?”) — but it’s beyond the conversational repertoire of most smart speakers and virtual assistants. That’s nothing a little artificial intelligence (AI) can’t fix, though, and in a blog post today researchers at Amazon wrote about the progress they’ve made with Alexa.
During a typical chat with Alexa, users invoke multiple apps — skills, in Amazon’s parlance — in successive questions. Currently, Alexa analyzes the content of each query according to its domain (type of skill), intent (function of the skill), and slot (a variable the skill acts upon). But skills often repurpose slots like “town” and “city,” which poses an obvious problem — if a user asks for directions and follows up with a question about a restaurant’s location, how’s Alexa to know which thread to reference in its answer?
Gupta and colleagues describe a solution in the paper “Contextual Slot Carryover for Disparate Schemas,” a neural network that automatically learns to map one skill’s slots to another’s. The findings will be presented at the upcoming Interspeech conference in Hyderabad, India in September. .... "
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