Complex PolyVox


our journey in building conversational AI

How do AI Agents Understand Customer Queries?

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Kylie Whitehead

26 Jun 2019 - 7 minutes read

In order to provide excellent customer service, artificially intelligent agents (or AI agents) need to be able to understand what customers actually want. Our human understanding of the broad variance in natural language is easy to take for granted, but for AI agents, extracting the meaning from sentences is a complex process that’s still being explored by the world’s best dialogue teams. In this post, we’ll take a high level look at how AI agents process queries and derive the intents behind them.

The State of Conversational AI Today

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Kylie Whitehead

17 Jun 2019 - 8 minutes read

There’s been so much hype around conversational AI that – unless you’re a researcher in the field – it's difficult to know what’s possible and what’s not. From sloppy Facebook Messenger chatbots to fully sentient robot friends – the spectrum of AI in popular culture and our everyday lives is broad.

Towards Composing Multilingual Conversations

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Ivan Vulić

2 May 2019 - 8 minutes read

Speaking more languages simply means reaching more people. This statement is equally true when it relates to humans or to conversational AI systems. The transformative nature of polyglot AI technology opens up new opportunities by catering to wider audiences and offering multilingual solutions. At PolyAI, our mission is to overcome the language barriers through our data-driven and language-invariant philosophy of composing or orchestrating conversations.

A Repository of Conversational Datasets

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Matthew Henderson

15 Apr 2019 - 2 minutes read

Progress in Machine Learning is often driven by large datasets and consistent evaluation metrics. To this end, PolyAI is releasing a collection of conversational datasets consisting of hundreds of millions of examples, and a standardised evaluation framework for models of conversational response selection.

The Magic Triangle of Dialogue Data Collection

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Paweł Budzianowski

22 Mar 2019 - 9 minutes read

Data is the driving force behind all our machine learning models. Although the word data itself buzzes a lot, the craft of getting and leveraging data for building conversational AI is unknown to many. At PolyAI, we put as much effort in creating cutting-edge conversational systems as in mastering data collection, because we know that a good AI system never comes for free.

Neural Language Understanding of People’s Names

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Matthew Henderson

15 Feb 2019 - 7 minutes read

This is a deep-dive into one of the problems we face when we model dialogue: understanding mentions of people’s names in a restaurant booking system. This article presents how we approached the problem and solved it using some creative neural network structures.

Towards AI-Assisted Customer Support Automation

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Tsung-Hsien Wen

5 Feb 2019 - 5 minutes read

There is a growing need for automating customer support using the latest AI technology, and it has the potential to completely change the industry landscape. The following roadmap outlines how PolyAI plans to achieve the ambition through step-by-step milestones, which also provide insights to contact center owners on how technology can be leveraged to transform their businesses.

Moving from Engineering to Orchestrating Conversations

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Tsung-Hsien Wen

21 Jan 2019 - 7 minutes read

The idea of engineering chatbots has failed us for way too long. It’s time to embrace a new philosophy and start orchestrating conversations, through data! At PolyAI, it has been the cornerstone of an approach which has empowered us to innovate and challenge the status quo.

The Age of Personal Assistants: More Machine Learning, Less Hand-Crafting!

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Nikola Mrkšić

1 Mar 2018 - 6 minutes read

Personal assistants such as Alexa and Siri are everywhere, but have trouble handling any tasks more complex than setting an alarm or playing songs on Spotify. PolyAI is a new London-based startup with a next generation platform for building voice-based agents. We use machine learning to handle complex tasks across different application domains, in a wide array of world languages.

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