Machine Learning Versus Linguistic Learning

I recently took time out from a conference to talk with Access-AI about the different approaches to building conversational systems.

Most schools of thought fall into one of two camps.

If you believe the machine learning crowd, then all you need to do is throw some data at a machine and out pops a natural language interface ready to go. Needless to say, that is not the case as I explain why in the video.

The other camp is for linguistic learning, also known as rules based, but this has a reputation for being too rigid and slow to build.

At Artificial Solutions we’ve taken the best of both methodologies and combined them at a deep level in our NLI approach. This enables developers to improve the speed of building conversational systems and their AI capabilities.

Conversation is becoming increasingly more important to interact with a range of technology from intelligent devices to applications and websites. Key to their success is humanlike understanding for a variety to reasons as you’ll see when you watch the video.

We built Teneo as a platform so that you have all the tools you need in one place to build intelligent conversational systems that can be deployed in multiple languages, across multiple channels, running over multiple operating systems.

But the true value of humanlike interaction can often only be understood when you start to see your customers respond by telling you their likes and dislikes, preferences and thinking processes—whether you asked for their opinion or not.

That’s why Teneo can also analyse these conversation in real-time to produce even more personalised responses to keep the conversation going and lead your customer to the logical conclusion.

While machine learning and linguistic learning both have their place in developing conversational systems, it’s only when a hybrid approach is taken that you can really deliver not just a great customer experience, but generate a faster ROI too.

Conversational AI

Andy Peart, CMSO of Artificial Solutions, talks all things conversational AI.


Our Vision: Making Technology Think

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