Seven Years later: What I Learned from Building an AI Chatbot – Part 1

A detailed illustration of a human head in profile, filled with gears and circuits, representing a blend of mechanical and electronic elements.

Seven years ago, I embarked on an ambitious attempt to build a rudimentary rule-based AI chatbot. Frustrated by the limitations of Apple’s Siri and motivated by exciting updates to Apple’s Natural Language Processing APIs, I dreamed of building something that could understand complex queries, construct mental models of objects, and seamlessly interact with users using just their voice. Siri was merely a fancy voice control toy; I wanted to perform calculations, manipulate data and leverage the dynamic power of language to build a tiny virtual world inside my iPhone, just like an intelligent computer system from Star Trek.
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AI Thoughts: Computer Vision, ChatGPT and Captain Kirk

A few weeks ago, I had the pleasure of attending a compelling lecture on computer vision at The Royal Society in London. Professor Andrew Zisserman showcased an innovative approach to building models, much like how a child learns – by cross-referencing visual, audio, and text data. However that is an oversimplified summary, the actual process can broadly be summed up into 3 steps and really got me thinking deeply about AI and some of the issues the lecture uncovered.
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Machine Learning and AI with Prof. Brian Cox

Last month I attended an interesting discussion panel on machine learning and artificial intelligence held by The Royal Society. This was presented by the ever warm and friendly Professor Brian Cox, everyone’s favourite TV astronomer. The video is online now and very gentle on technical details so worth a watch even if you know nothing about the gooey parts of a robot’s brain!