In their conversation, they bring up mobile as a recent platform shift that caused a lot of disruption. But I think it's interesting to remember how slow that took. The iPhone was released in 2007, but the real winners of mobile were launched years later -- Uber (2010), Snapchat (2011), and TikTok (2016) -- and those winners took several more years to even start to gain true traction in the market.
I don't think a lot of people back in 2007 could have predicted that the biggest thing to come from mobile would be an app that let teens remix music videos and share with their friends.
This is why I think it is a little pointless to try and create mental models for what products and features to build to capitalize on AI (though it can be fun). It's so early that we're not capable of understanding what's possible yet. If anything, we're probably at the viral "fart app" stage that mobile was in for its first few years.
>I don't think a lot of people back in 2007 could have predicted that the biggest thing to come from mobile would be an app that let teens remix music videos and share with their friends.
I think that the biggest thing to come from mobile was always available location, exemplified by Google Maps which already existed before mobile happened. Many of the most successful apps relied on this.
TikTok is different, in that it could have existed on desktop (but would have looked very different) whereas Uber (for example) definitely couldn't.
I don't use TikTok so maybe I'm offbase, but I tihnk while technically it could've existed without mobile, socially I'm not so sure.
I wouldn't under estimate the amount of friction reduced in having an app on your phone which a) is always with you, b) can also record top quality video and c) has a data plan good enough to upload there and then.
> To take it a notch further, it's the video editing simplicity that really blew TikTok up.
Yup, definitely. Effective mobile editing was a big driver of it's success.
That being said, while it's definitely more effective and popular on mobile how much of that is just down to more people using the internet on mobile relative to desktop.
This is unlike Maps or Uber which only make sense with mobile and always available location.
Not exactly tiktok, but something similar was tried on desktop - Dailybooth was a YC startup which enabled users to take a photo from the desktop website and post it.
> I wouldn't under estimate the amount of friction reduced in having an app on your phone which
I wish I could do software development from my phone the way people casually watch tiktok videos. The least unproductive thing I can currently do when trapped with only a phone is read HN.
I don't think that Uber through SMS would be strong enough to compete with taxi services.
One of the core features that made me use Uber was the map - I could see where the driver is going and how far away is he. Also, the app is localised into language that I can understand and I can see the price upfront without having to worry about getting scammed. Recently I had to book a taxi over the phone at the end of the world (literally - Ushuaia) in a language that I can barely speak and the experience was rather stressful in comparison with using an app.
Seeing a price up front is just a different business model and localization could be easily handled with a setting on your account. Neither is tech-dependent, both could have worked over SMS too.
Real-time mapping would be tricker if that's really a killer feature for you.
For Uber though there's the driver side experience as well as the customer side. I don't know if you could've made something seemless enough for drivers to use from an old feature phone
TikTok's success is primarily about the creator tools, not the viewing experience. Making video editing mobile-friendly and accessible to more people is what enabled the proliferation of short-form content.
I am constantly surprised of how prescient my Media studies professor was back in 2007 about how everything has shaking out since then. "Your data is valuable don't give it away" is ringing in my ears as I give all my data away to openai
Individual data is extremely valuable, they wouldn't collect and store it individually if all they wanted was the aggregate.
Identity-specific data is sold all the time for everything from advertising to credit scores and what would otherwise be called social credit scores of they were run by the government instead of private companies.
I'm not really sure what would be considered cheap vs valuable here so I don't have a great answer there. My point was only that individusl data is collected and sold often, it must be valuable or there wouldn't be a market.
I'd be curious to see how the price compares when selling 10k individuals' data versus aggregate data the 10k people. Presumably if it was cheaper to buy all the individual data I would do that and aggregate it myself.
The data is only useful in aggregate, but different people/use cases require different types of aggregations. Using pre-aggregated data is difficult, because it almost certainly hasn't been aggregated in the way that's convenient for whatever analysis you're trying to do with it.
The aggregate data is often more useful in commercial use cases, but plenty of use cases need the indivual data as well.
Private investigators, three letter agencies, and any company wanting to send mailers to my new address when I move all need the individual data to target me specifically.
I totally agree the aggregate data is given more value in a commercial market heavily focused on advertising and now training LLMs, my only point was that there are markets that highly value individual data as well.
Sure, it is fractionally "valuable" in the sense that it is worth some tiny percentage of the large datasets it belongs to that get purchased for significant amounts.
I think the point stands that it wouldn't be easy to sell your individual data, and even if you could, it would be for a pittance from someone who is looking to build a large dataset. They certainly wouldn't be giving you an amount that justifies advice like "hold on to your data".
>What if I want to keep my history on but disable model training?
We are working on a new offering called ChatGPT Business that will opt end-users out of model training by default. In the meantime, you can opt out from our use of your data to improve our services by filling out this form. Once you submit the form, new conversations will not be used to train our models
Sure it does. A secret stops becoming a secret once you give it away to enough people. I feel like you're trying to justify piracy but picked the wrong argument.
I'm talking about personal data. Piracy is rarely a concern here.
(And btw, piracy only makes the data less valuable, because you lose the ability to sell it to someone who already has it. Not because the game or movie etc would become less enjoyable.)
> But I think it's interesting to remember how slow that took. The iPhone was released in 2007, but the real winners of mobile were launched years later -- Uber (2010), Snapchat (2011), and TikTok (2016)
And really something more like 2010 is probably a better date for when the iPhone really took off with the 3GS generation. There were obviously earlier smartphones as well (Blackberry, Treo) but they weren't really mainstream devices and didn't especially enable third-party apps.
So, yeah, there was a maybe five year (and certainly less than ten) period when smartphones went from a fairly niche thing to ubiquity which is very fast compared to technology adoption generally.
Might be worth looking at the limiting factors that caused the delay between iPhone (2007) and the advent of Uber, et al.
Then overlay that with the limiting factors for AI/LLMs.
I had a third-party logistics startup in 2007 that I would have loved to turn into Uber for shipping, but it would be at least a few years before the cell networks and ownership of smartphones reached a point where it was possible.
I don't know if there are limiting factors that will delay LLMs potential to disrupt the status quo.
> I don't think a lot of people back in 2007 could have predicted that
the biggest thing to come from mobile would be an app that let teens
remix music videos and share with their friends.
That's funny for me to read almost 15 years after rjdj [0] There is a
difference between an idea that is possible, and an idea whose time
has come.
I don't think a lot of people back in 2007 could have predicted that the biggest thing to come from mobile would be an app that let teens remix music videos and share with their friends.
This is why I think it is a little pointless to try and create mental models for what products and features to build to capitalize on AI (though it can be fun). It's so early that we're not capable of understanding what's possible yet. If anything, we're probably at the viral "fart app" stage that mobile was in for its first few years.