This website and blog support the Virtual Humans book by David Burden and Maggi Savin-Baden published by Taylor & Francis in February 2019. Here you can find links to images, videos, papers, articles and application resources related to the topics covered by the book, and a blog maintained by the authors to track the development of this fascinating and vitally important topic.
Showing posts with label natural language. Show all posts
Showing posts with label natural language. Show all posts
Meena - the latest Google ML Chatbot
There's been quite a bit in the press recently about Meena, Google's new chatbot powered by a "Evolved Transformer seq2seq" neural network model which is even more powerful than the recently touted GPT2. The bot has been trained on "341 GB of text, filtered from public domain social media conversations".
Whilst the results for general conversation seem impressive, I can't help but think that this is a bit of a dead end as the bot really has no idea and is in no way directing the conversation, its just coming up with the "best" response to each input, albeit taking the conversation to date into account. It just doesn't seem to have any intent or goals of its own.
More interestingly though Google has been measuring the performance of the bot (and using that as part of its reward function) with just two variables - how sensible is a reply, and how specific is it. Lots of bots try to go for sensibility and the expenses of specificity, they come back with general statements ("why do you say that") rather than actually trying to drive the conversation forward. For a while now we've been using Grice's maxims as a way of assessing bot performance (quantity, quality, relation, manner) which aim to cover similar ground, but the Google model may be even simpler and sharper - particularly when trying to train a human to do the assessing!
W3C Conversational Interfaces Community Group
W3C has set up a Conversational Interfaces Community Group "to enable web developers to collaborate and share conversational experiences for a variety of domains. Most dialogue systems serve interactive experiences in their own domain specific language, causing a fragmented zoo of proprietary formats. For example, Google Home or Alexa do not share a common intermediate representation, which makes writing wide-spread content inaccessible to the mass audience. We study existing specs and design standards to harness proven techniques into common agreement. "
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