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All Posts

How to Deploy Conversational AI for Voice

APPROACH 1 DIY, from scratch Some companies opt to build their own DIY voice assistant in-house, from scratch.  Bank of America’s “Erica” Bank of America did just that with their AI-driven virtual financial assistant: Erica. This completely self-owned system was created by a development team of 100 people in 2017. It took the team nearly […]

Nikola Mrkšić on the Practical AI Podcast

PolyAI CEO & Co-Founder Nikola Mrkšić spoke to Daniel Whitenack and Chris Benson last week on the Practical AI podcast. The topic of the podcast is next-gen voice assistants, and Nikola takes Daniel and Chris on a deep dive into conversational AI, discussing the next generation of voice assistants that will be capable of handling […]

PolyAI Maintains Lead Over IBM Watson Assistant and Other Popular Language Understanding Models

In December 2020, the team at IBM published a blog post and technical paper in which they benchmarked the performance of a new-and-improved Watson Assistant against other conversational AI platforms from Google, Microsoft and Rasa. Naturally, we were very curious.  As it happens, some of the training datasets used in the benchmark test were the […]

Conversational ID&V vs Voice Biometrics: A New Approach to Authenticating Customers on Customer Service Calls

Language is full of characters and words that sound frustratingly similar. Sorry, was that M or N? Did you say three, free, or tree? In normal conversation amongst friends, this is easily overcome but customers are less forgiving when they have an issue with a product or service. Before customers even get the opportunity to […]

How Voicebots Handle Languages & Accents

Let’s face it. Understanding your customers isn’t always easy. They tell stories, go off track and they often can’t think of a good way to explain an issue to you. And those are just the customers that speak the same language as you. Even for humans, it can be really difficult to understand people with […]

PolyAI’s ConveRT Model Outperforms BERT and GPT-Based Models in Salesforce Research Evaluation

In a recent evaluation by Salesforce Research, PolyAI’s ConveRT model performed top across a range of metrics, while using a fraction of the computational resources. Salesforce’s recent paper, Probing Task-Oriented Dialogue Representation from Language Models, compared ConveRT to other pre-trained models, evaluating their ability to encapsulate conversational knowledge in application to Conversational AI tasks. ConveRT […]

ConVEx: How PolyAI created the most accurate value extractor on the market

We’re thrilled to announce our recently published paper on the PolyAI ConVEx framework. Our new technique, ConVEx (Conversational Value Extractor), is the most accurate value extractor on the market. It requires significantly less data than previous best systems, which means that PolyAI can create virtual assistants faster and better than anyone else, across any customer […]

Intent Classification with Geometrically-Friendly Embeddings

At PolyAI, our conversational agents are powered, in part, by machine learning models that detect the intent behind what a user says. For example, in a banking environment, if a customer says “When did you send me my new card?”, the models will detect that you’re enquiring about card arrivals and the agent will route […]

The State of AI 2020: Creating a Model That Performs Better than Google, at a Fraction of the Cost

The latest State of AI report from Nathan Benaich and Ian Hogarth has just been released and we’re thrilled that PolyAI has featured – twice! The report highlights the vast costs of training a model. “Based on variables released by Google et al., you’re paying circa $1 per 1,000 parameters. This means OpenAI’s 175B parameter […]