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 →
“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 →
2020 was a hectic year and somehow I didn’t manage to post on my blog, however I was hard at work finishing some of my side projects. One such side project has now been approved and is live in the Mac App Store – Text Calculator.
Time is an odd concept. It’s suppose to be linear but sometimes you can watch the clock and 5 minutes seems like an hour. At other times you can look up from your desk after what barely seems like 5 minutes and find the night settling in.
It’s been 8 months since my last blog post and I hadn’t meant to leave it so long but I’ve been busy with a few things… I architected in-app subscriptions into my weather app for drones, released a brand new version with new features, joined a new startup, studied for a number of flying exams, lost a few hours to Starcraft Remastered, rebuilt Pac-Man from scratch, forked and heavily updated an open source project, started work on a prototype AI concept, watched a whole season of Game of Thrones, went to the gym a lot, learnt an old song on guitar, remembered to socialise oh and got quite into Rick and Morty again. Hence why I haven’t found the time to blog! However I should be posting again soon.
In the mean time, you should watch this interesting TED talk about a guy who thinks the brain hallucinates your reality which could have some interesting applications for AI.