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. Continue reading →
Imagine a song nearly 50 years in the making, waiting for technology to advance, to finally free a lost voice trapped inside a long-lost tape recording!
John Lennon recorded some rough ideas for a hit song on tape for his friend, Paul McCartney but, tragically, he’d never get to record it properly as his life was cut short. After John’s death, the tape sat in a cupboard until 1994, but the technology of the time couldn’t free his voice from the demo tape as the vocals were merged with the piano meaning his rough idea couldn’t be edited and produced into a polished, releasable song… until now! Continue reading →
For a long time, I’ve been interested in continually fostering a growth mindset. It’s a powerful belief that you can change your situation in life; that you aren’t fixed in terms of what life gives you. Instead, you can change it, learn new skills, and make your life dramatically better! Compare this to a fixed mindset where you believe that you are handed your lot in life and nothing you do will change it. That trying to improve yourself is some acknowledgement that you are not enough.
Recently I’ve been exploring ways in which ChatGPT can amplify some of the various self-help techniques I’ve picked up along the way to building a growth mindset… Techniques that have the potential to radically change your life. Continue reading →
“Are you crazy, nobody uses ChatGPT like that, you know that right?” Mark said as we sat in the pub. I took a sip of cold crisp beer, slightly puzzled. I thought about how I’d been using generative AI to change my life recently. How I had used it to build a zen-like focus-point around a huge Japanese Acer in my garden. “Surely everyone uses it like that, isn’t it obvious?” I said, feeling slightly self-conscious. I hesitated. Should I tell him how I had also spent all evening talking to ChatGPT coming up with ideas for a cottage garden? It had factored in thousands of different plants that would make even Monty Don drop his trowel in surprise. That was when it struck me that most people use ChatGPT like Google. They punch in a prompt pieced together from some cheat sheet they found on social media and watch it spew out information like a hot bubbling volcano of knowledge, before copying and pasting the answer and never to give it a second thought. For me, this was a bit like using an expensive Macbook Pro laptop as a tea tray. Sure, it works and it’s useful to some degree, but there is so much untapped power in this method of computing, and by method, I mean “conversational intelligence” computing.
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. Continue reading →
