How can you use deep learning models to enrich conversational AI experiences?
Recently, I wrote about a number of amazing conversation AI systems introduced in 2020 like Google Meena, Facebook’s BlenderBot, and OpenAI’s GPT-3. These systems used Deep Learning techniques and trained on huge amounts of text data to learn how to make open-domain conversation.
How chatbots can steer conversations by understanding the nuances in user utterances?
One of the trickiest problem designing and building chatbots is to build its capability to understand user’s utterances. This is the very first challenge facing the chatbot — understanding what the user wants from what they say. We call this the intent classification problem. What are intents? How can you come up with a set of intents that the chatbot need to be looking for in customer’s utterances? Although, intent classification is an essential part of most popular chatbot solutions (e.g. IBM Watson Assistant, Google DialogFlow, MS LUIS…
Measuring chatbot performance beyond traditional metrics and software testing methods
How do you test a Conversational AI solution? How do you evaluate if your chatbot is fit to be deployed to face your customers? Out of all the types of Natural Language Processing systems like Machine Translation, Question Answering Systems, Speech recognition, Speech synthesis, Information Retrieval, etc., Conversational AI is the most challenging one to measure. Conversations are not one-shot tasks. They are multi-turn and whether a conversation succeeded or failed is not easily apparent. …
A review of 4 defining Conversation AI systems that we saw in 2020
2020 is over! What a roller-coaster ride that was?!
Conversational AI systems progressed a lot in 2020. Certainly, as the pandemic started, we saw many chatbots built to deal with the need to provide reliable and trustable health and safety information to people. Many governmental organisations took to chatbots on popular channels like Whatsapp to disseminate authentic information.
A new set of conversational AI systems made their mark in 2020. These were based not on traditional rule based architecture for conversational flow. Instead they used deep learning…
Chatbots are everywhere now! By chatbots, I usually talk about all conversational AI bots — be it actions/skills on smart speakers, voice bots on the phone, chatbots on messaging apps, or assistants on the web chat. All of them have the same underlying purpose — to do as a human agent would do and allow users to self-serve using a natural and intuitive interface — natural language conversation.
If you breakdown the design of conversational AI experience into parts, you will see at least five parts — User Interface, AI technology, Conversation design, Backend integration, and Analytics. If you are…
Finding a new vision for Conversational AI
Have you ever finished a conversation with a friend not realising how much time you have talked or all the other stuff that had been going on in the space around you two? This feeling of being in a state of flow is what I am going to call — Conversational Singularity.
Conversational Singularity is a state of flow that is achieved during conversation that dissolves the duality of conversational partners and creates a unified singular experience.
They can talk for hours and still not realize that time has passed. They exchange info…
How can chatbots become truly intelligent by combining five different models of conversation?
Conversational AI is all about making machines communicate with us in natural language. They are called using various names — chatbots, voice bots, virtual assistants, etc. In reality, they may be slightly different to each other. However one key feature that ties them all together is their ability to understand natural language commands and requests from us-human users.
In the back-end, these agents will have to deal with carrying out the request and engage in a conversation. …
How to solve world’s wicked problems?
Systems Thinking is a way of thinking about ourselves and our place in the world. It is about understanding that the things we see in the world are all inter-connected and therefore influence each other. It is a way to look at the whole and not just the parts that make up the whole. Systems Thinking prods us to see the deeper connections and influences in the world as we begin to identify problems and devise solutions. It helps us to solve complex problems without creating new ones.
Watch this video to get started..
What is NLP and how does it make machines smarter at communication?
One of the first things that fascinated me in Artificial Intelligence is for a computer having the ability to speak and have a conversation with humans. When I saw C-3P0 speak on a giant screen, way back when I was a kid, I was mesmerized. I probably didn’t realise it was fake back then, but I wanted in. I wanted to build robots that can speak, that can take instructions, that can have an engaging conversations with me.
Here I am now, in my almost 40s, still building…
A series of stories on how to design great conversational AI experiences using insights from psychology, human-centered design, and design thinking. Hope you find these useful.
Over the years, I have written a series of articles on various aspects of chatbot design. Here they are, all indexed in one place: