Gustav Söderström
speaker
294 appearances
1 recordings
1 series
first heard May 2025
last heard May 2025
Gustav Söderström’s voice in public audio — every appearance, attributed to the second.
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Appearances
And these gifts keep coming almost on a schedule and they actually come gradually. closer and closer. Previously, technology companies were not called technology companies. As a side note, they were called car companies, but it wasn't technology companies or pharmaceutical. That was a state of the art technology right then.
But because these microwaves came so far apart, they call themselves a car company. They never became ubiquitous technology companies. They overfitted to that. I think somewhere in the 90s, around Google, Amazon, et cetera, these macros started coming so fast that people tried to pin them down. Amazon is a books company, and they were like, no, not really.
We're doing books, but here's other stuff we're selling. And then, okay, you're the everything store company. It's like, no, not really. Now we're selling Amazon Web Services over here. So I think these companies are the first set of companies to have technology as the strategy. The previous ones took...
one wave as the strategy and IBM comes along and does computers as a strategy or first memory and so forth. I think this is the first wave of general technology companies, which interestingly might mean that it could be, I mean, companies almost always die after a while. These could be the first companies that never die because they're ubiquitous technology companies.
Whatever the technology gift is, just try to have a company that can quickly wrap around it, figure out the product and business model. So I think that's interesting. And that's how I think about Spotify. Yes, we're music company and then a podcast company and then a book company and a video company.
But it's really about trying to anticipate technology, figure out what it can do, and then adapt the product and often the business model. So I said mobile was one of these things where we needed to change the business model. And I think what happens when one of these technology gifts comes along is There is a big change when the technology happens. Piracy, big havoc.
But the real change happens when someone also figures out the business model. So I tell my product teams, technology can do good things and a new business model can really change the world. But without a business model, there's seldom like large scale change. You can destroy a lot of things, but you never really create value.
So mobile was the first where we need to figure out a free tier on mobile without cannibalizing our paid tier. And what we did there was we looked at our data and saw that 50% of premium users were listening in shuffle mode. So we said, what if we take shuffle as a feature, give that away for free?
It should be 50% of premium consumption, so very valuable, but it's not going to be 100% of anyone's premium consumption, so no cannibalization. And we managed to create a tier where you could playlist all your favorite songs in a playlist, press play, put the phone in your pocket and listen forever for free in the background. So that was a business model innovation, along with technology.
The most previous one was audiobooks, where there were audiobooks in the US a la carte. And sure, we did some nice innovation around being able to stream that book. But the real thing is not stream a book. You've been able to stream audio for a long time. The real... Innovation, that was the business model to be able to bundle audiobooks into Spotify Premium. It's almost like music.
Music was also a la carte and quite niche. And once we made it an access model with no marginal cost, it got way larger. And that's what we think about audiobooks as well. So we've seen a few of those and managed to adopt them. To your question, is AI going to do that? Do we need to change the business model? I'm not sure.
I think there is one glaring thing that is different, which is the previous VC model coming all the way back from chips and silicon was you make a big upfront investment and then you amortize and you get to almost zero marginal cost. That's how software worked. It's not how AI worked. The marginal cost is high and you need to cover it.
So you could say that that should change everyone's business model. You're going to need to somehow either monetize very effectively through ads or charge users. And you see OpenAI being a subscription product. And I think you're going to see more of those. So the marginal cost is a net new thing.
For Spotify, it's interesting because we're like the one technology company that always had a marginal cost. One more stream... was a marginal cost to labels. So we grew up in a world where if we were too successful on the free tier, we could go bankrupt overnight, which was never true for Twitter or Facebook, which is why VC said, just go crazy, worry about monetization later.
Spotify could never do that because we could go bankrupt overnight. So we always had to worry about monetization and the balance between free tier and pay tier conversion and free tier monetization. So the good thing for us is we're fairly used to marginal cost in our business model. I think you're going to see those things.
It's very likely that some consumers are going to want tons and tons of inference. And because that's a marginal cost, you're probably going to have to pay somehow for that as a consumer. So I think you're going to see more tiering of consumer products based on how much inference you want. But for us, that's not that new. We've had several tiers already.
I'm curious because I'm an investor in a company called Etch that's going to be one of these companies that pushes down that inference cost. Like the history of compute, you're going to see this incredible consumer surplus and consumer benefit that comes from cheaper and cheaper unit by unit inference cost.
But the countervailing force is that we would just use more of it, more reasoning tokens, more whatever. So it makes me wonder how much more you can imagine better models being useful to you. It seems like if we just froze
reasoning and model capabilities today, we probably still have decade plus of digestion to do of how we could use these models to make better products, better features, whatever. Can you imagine another couple orders of magnitude better models opening up lots of features that you can't currently do? Is that a thing?
Or do you think we have what we need and therefore inference we could expect to be really cheap?
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