What’s with social media companies trying to destroy themselves recently? ( kbin.social )

theinspectorst , 11 months ago

I know the common answer is something around the lines of “because companies only care about making money”, but I still don’t get why it seems like all these social media companies have suddenly agreed to screw themselves during pretty much the period of March-June.

It seems like the proximate trigger for many of these decisions has been the rise of ChatGPT at the end of last year. Before this, they saw the best way to monetise their platforms as being about encouraging new content to create new clicks for advertising revenue. Since ChatGPT, they realised they're all sitting on goldmines of old content that could be used to train their own AI models - so suddenly they're prepared to take a range of seemingly-mad actions that will harm the quality and quantity of new content being created, because they think they've got enough revenue-generating potential from the existing content.

Of course the problem here is that a) they're killing the golden goose - monetising the back book while degrading the new content means they can only do this once, so they better hope it works and makes them a shit load of money, whilst b) although there's loads of potential in AI, we're yet to see someone actually make money through it and it has the potential to be a huge bubble where the hype eventually dissipates and the market collapses upon itself, with only a handful of players making it through unscathed to become the big success story.

All of these social media companies are betting the future of their platforms on them being the one that makes it through the AI bubble. Most of them will fail.

FaceDeer , 11 months ago

Another potential problem with trying to monetize off the back of AI is that AI is such a rapidly developing technology that there's no guarantee that their stashes of data will actually be all that vital. There's been a tendency lately toward training AI with a smaller but more highly refined and curated data set rather than just shoveling vast quantities of text at them, for example.