The Device is the Boring Bit

The Apple Vision Pro is now on sale. People are getting their hands on them, and sharing their opinions. People who haven't got their hands on them are sharing their opinions. There are a lot of opinions flying around.

First thing - sure, I'm interested in the headset, and the device actually getting in 'normal' people's hands (or on their faces) is this week's news; I'm not going to buy one, because it's ridiculously expensive and if I had that sort of money to throw around, I probably wouldn't be driving a car that's approaching either its 18th birthday or its last trip to the scrapyard and has done the equivalent milage of 5 times around the circumference of the earth.


But what I'm really interested in is the Vision platform; the bits in the software that are going to be the same when the next headset device is launched. And once there are a bunch of different ‘Vision’ devices - where they will fit, in the spaces in people's lives.

Who owns Taylor Swift's voice?

Ben Evans on Threads;

It's a lot easier to understand the IP issues in 'give me this song but in Taylor Swift's voice' than 'make me a song in the style of the top ten hits of the last decade.' If a human did that, they wouldn't necessarily have to pay anyone, so why would an LLM?

There's an interesting twist with the "Taylor Swift's voice" example; Scooter Braun owns all of Taylor Swift's recordings (at least, I think all the ones released before any ChatGPT-era training dataset were compiled) - he bought the record company, so he owns the master recordings (and all the copies of the master recordings, and the rights relating to them) - but not the songs themselves. Taylor Swift still owns them - which is why she can make her "Taylor's Version" re-recordings (which Scooter Braun doesn't get a penny out of.)

So there's a key difference here; a human would copy the songs (that is, they would be working off the version of the songs that are in their heads - the idea of the songs), so Swift would get paid as the owner of the songs.

But the kind of generative AI we're talking about would be copying 100% from the recordings (ie. the training data would be the sounds, digitised and converted into a stream of numbers) - which Swift doesn't own. The AI doesn't "see" the idea of the songs - it wouldn’t “know” what the lyrics were, what key the songs were in, what chords were being played on what instrument - any more than a Large Language Model “knows” what the words in its (tokenised) training dataset or output mean.

She still owns her songs, but she’s sold her voice.

(Pre) WWDC 2023

WWDC usually isn’t one to look forward to - unless you’re the sort of person who cares about things like Xcode features - because it isn’t the venue where they talk about the new iPhones. Maybe there will be clues about new iPhone features in some new APIs or something, but the focus is generally on developers.

This year is different…

Somebody, make it stop

Well, my son is learning to play the guitar - at 13, he's about the age I was when I started learning, but he's been playing for a good few years and it won't be long until he's better than me at 45 (if he isn't already...)

One of the songs he's learning with his guitar teacher at the moment is Smells Like Teen Spirit - which came out in 1991, when I was about the same age that he is now and also learning how to play it on the guitar.

Which got me wondering - if I was playing something when I was 13 that is as old as that song he's playing is now, what would I have been playing? I know that I was playing 'old stuff' at the time - learning a lot of Jimi Hendrix riffs, some Beatles, some Cream etc. After all, the '60s were a hell of a decade for guitar heroes…

Well, I did the maths, and the equivalent for me in 1991 would have to have been a song from 1959. That wasn't just before all the "old" stuff from the (late) 1960s that I would have been playing- that was a time when Jimi Hendrix was still "Jimmy Hendrix" and learning how to play on his first $5 acoustic guitar. Keith Richards was still studying at technical college, and The Beatles hadn't even started playing with Pete Best yet - let alone Ringo. Elvis Presley was in the army, discovering amphetamines and meeting the 14 year old girl who he would marry seven years later. Tamala Motown had only just been formed.

Oddly though, it was also the year that the most valuable Gibson Les Pauls were made - even though it was still years until they would become famous, thanks to the likes of Keith Richards, Eric Clapton, Jimmy Page and Peter Green.

Anyway, now I feel old.

Robot War part 3: The Race

This is the tech war of the moment; a race to be the first to develop an AI/Machine Learning/Deep Learning product that will be a commercial success. Google have a head start - Microsoft+OpenAI look like they could be set to catch up, and maybe even overtake Google. But if this is a race then where is the finish line? What is the ultimate goal? Is it all about the $175 billion Search advertising market - or is it bigger than that?

The Next Big Thing (2023)

Nine years ago (Jan 2014), I wrote a post about "the next big thing". I think its fair to say that in a history of technological innovations and revolutions, there isn't really much in the last decade or so that would warrant much more than a footnote; the theme has been 'evolution, not revolution'.

Well, I think the Next Big Thing is - finally - here. And it isn't a thing consumers will go out and buy. Its an abstract, intangible thing; software not hardware, service not product.

For the first time in years, tech has got genuinely interesting again.

Unordered S2E1 - Reboot

A collection of things that caught my attention about Twitter blowing up, Taylor Swift blowing up the charts, Sim City blowing off parking, Amazon not really losing a trillion dollars, a book about The Beatles, the comedy of The Simpsons, and the fundamental importance of comedy.