AI Restoration, Ethics and an Unfinished Beatles Song

Cassette Tape in a tape machine

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!
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Using ChatGPT to Chase Your Dreams and Goals

adventure flying plane private jet

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.
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Vision Pro: How it converted me on VR in 5 minutes

To me, VR and AR had always been somewhat of a cheesy gimmick. What would possibly have changed my mind in just 5 minutes? I found myself eagerly watching the big screen at NSLondon, an exclusive nomadic developer gathering with only 60 coveted spots free that often vanish within minutes of the waitlist opening. Did I mention there was free beer and pizza? I sat watching the Apple WWDC (World Wide Developer Conference) keynote – also known as iOS developer Christmas, that reveals new Apple software and teaches developers how to build amazing things with it months before it’s released. However, rarely do physical, shiny new products from Apple get announced at “dub-dub”, the developers’ abbreviation of the 8-syllable tongue twister that is dub-bull-yew-dub-bull-yew-dee-see. Believe me, it’s even tricker to say mid-bite when consuming beer and pizza.
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Wrangling AI: How I Turned ChatGPT into My Creative Sidekick for Garden Design

My Cottage style garden with Mediterranean influence - Lavender, and various grasses are in the foreground.

“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.

Steve Jobs famously once compared the computer to a bicycle for the mind — for its efficiency in propelling humans to where they wanted to go. I would be so bold as to say, extending this analogy… That AI is a motorcycle for the mind.

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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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