"Changing" TV viewing behaviour

About five years ago, I wrote about how much TV viewing has really changed;

So - 85% of viewing is definitely not watched "as a family", because nearly half is watched alone... but that said, the point here is that I'm not seeing anything here that makes me think that there has been a significant change in viewing behaviour over the last decade. (Interestingly, we watch more TV on our own in the summer months- which is when we tend to watch less TV overall.)

This is a chart of the share of viewing time spent alone - ie. with nobody else in the room, whether or not they are actually "watching" the TV;

Since then - well, things have obviously changed.

Covid and lockdowns had a massive impact on the time people spent at home vs. out of home, with the longer-term legacy of working from home being increasingly 'normalised' (the current trend seems to be a gradual return to the office - but at least day or two WFH seems to be the 'normal' for what was 100% "office-based" work before.

SVOD subscriptions have rocketed; more TV viewing is to stuff that never had a TV broadcast.

Phones have got faster, and we've gone to 5G - making watching video on other devices a virtually frictionless experience.

More people are watching new platforms like TikTok.

AI is about to change the world again - and is already flooding social media feeds with growing volumes of slop.

So, how have those changes manifested themselves? What does an updated version of the chart above look like?

I've coloured 2020 - the obvious 'change point' black to make it clearer where all that dramatic change in behaviour really kicked off.

Plus ça change, plus c'est la même chose…

(Footnote 1- this data is about viewing to television sets; whatever it is that is being viewed, based on Barb Audiences' data. I've written extensively before on what I think "television" is, and in my view, its basically "whatever is on the TV". There's a whole other conversation where that might have come from and which "pipe" it went down to get there - but my personal interest and focus is always on the media behaviour rather than the content.)

(Footnote 2 - In case you were wondering why the data only goes up to June, its because I wrote this post in July as a draft, forgot to click 'publish', and just spent ages trying to find the link to a thing I knew I had written but couldn't find. Whoops.)

AI and "Apple Intelligence"

(Title based on a Threads post from Daniel Jalkut.

What Is Apple Doing in AI? Summaries, Cloud and On-Device LLMs, OpenAI Deal - Bloomberg

But the company knows consumers will demand such a feature, and so it’s teaming up with OpenAI to add the startup’s technology to iOS 18, the next version of the iPhone’s software. The companies are preparing a major announcement of their partnership at WWDC, with Sam Altman-led OpenAI now racing to ensure it has the capacity to support the influx of users later this year.

Nah- I'm not buying it. For one - OpenAI and Microsoft are "true" partners; Microsoft's Azure compute + OpenAI's models + Microsoft's apps/OS ¹ are getting deeply intertwined. An Apple + OpenAI partnership seems like a strategy to be permanently one step behind Microsoft.

But it seems inevitable that there's big Apple + AI news coming. Siri needs a significant upgrade. The new iPad Pro announcement made a big deal about having "AI compute" power². "AI features" announcements at WWDC 2024 seems like the safest bet in tech.

So, what might be coming?

• Siri was a pretty early bet on the future - but possibly too early, given the advancements in machine learning/deep learning since Siri was first released. But "Siri" is more of a brand than a technology - there are "Siri" features that don't seem to have anything to do with the voice assistant.
• Meanwhile, while Siri might seem to be stuck in a rut, Apple's own proprietary ML/AI technology has been coming along. Apple Music has had a 'karaoke' feature where you can turn down the vocals - which I had wondered whether it was an AI-powered thing or just that they get separate stems; the latest Logic Pro which lets you split vocals, drums, bass and 'everything else' seems to suggest that its AI rather than a 'special access to the masters' situation. Given Apple's insistence on owning any technology that they rely on, this seems like the most likely approach. Whether Siri as a brand is dead or not… We'll see. (Worth noting that Siri came out before the film 'Her' - while OpenAI's latest release seems clearly... 'inspired' by the film, Siri looks more like the inspiration for the film.)
• That said - it seems that Apple needs to catch up a lot, and fast. So a partnership with a technology leader does make sense. So... with who?
  • Meta? Meta's AI push has been for 'open' models (as opposed to - ironically - OpenAI's proprietary approach) that anyone can use. Apple's strength is in using on-device computing power (because they have a fair amount of it - it also fits with their 'privacy first' approach.) Maybe Apple would be licensing these models - but I suspect that the Apple/Meta relationship isn't strong enough to make it likely that Apple would want to put their future in Mark Zuckerberg's hands.
  • Google's AI journey has been... interesting. They seem to be leaders in terms of the underlying tech - but struggling to actually execute; OpenAI/ChatGPT/Copilots seem to be conclusively winning the PR/branding fight - perhaps they need a partner who can make a better product (away from the issues of competing with Search as a business model) that can better reflect the power of the underlying tech than Google's efforts to date. The Transformer architecture that led to the LLM explosion came out of Google, as did the Tensorflow software framework. While everyone else is fighting over nVidia's GPU chips, Google have been making their own TPUs for nearly a decade. Google is arguably the only GPU-rich business at the moment, and there is a general vibe of the AI industry being Google vs. Everyone Else - having a big partner might be exactly what they need right now. Maybe most importantly, Google pays Apple a lot of money for search engine prominence. The question is how much of the old Android/iOS friction still exists on Apple's side, while Google's opportunity is to make an AI-powered "Google Android" a distinct product from... lets call it the "Samsung Android" ecosystem - which doesn't make as much sense if Apple gets benefits that cheaper Android phones don't.
  • Microsoft? If Apple could get a more... lets say "grown-up" business partner without the volatility of OpenAI, then that could be interesting... And if the 'everyone vs Google' view of the market is right, then it seems to be in Microsoft's interests too. But it seems that Microsoft's clear positioning of 'Copilot+ PCs' as going head-to-head with Macbooks would be unlikely if that was in the pipeline.
  • There are other AI companies (eg. Anthropic) - but I'm not sure how many of them are scalable enough (read: access to the compute resources that would be needed to potentially switch on for every iPhone/iPad/Mac owner in the world overnight.)

If I had to make a bet, my money would be on a Google partnership, with something like the Gemma model running locally on iPhone/iPads etc. as 'Siri 2.0' and access to Gemini for the kind of tasks that need access to 'full fat' LLMs and more computing power.

1. Also- GitHub CoPilot ↩

2. Yes, iPads/iPhones/Macs have had 'neural cores' for a few years - but the new iPad seems to be stepping this up significantly, but with no news on what its actually going to power. Worth noting - if you're developing AI/ML/LLM-type software on a Mac, you're using the GPU - not NPU chips. So far, they seem to be locked away for Apple's use (which includes Apple's APIs if you're building apps for the app store - but not if you're running something like TensorFlow in Python.) ↩

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.

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.