Some things cost more depending on their situational advantage. For example a run-down Jeep sitting in a garage and thought of as 'worthless' would be worth a fortune at a Jeep fair and seen as a collectible.
Well, some stuff can be centralized, like burger production, or ordering million gallons of Coke. Some stuff, however, has to remain local, like labor, or real estate costs.
Honestly, that's the only reason I'd ever go there (and even then only very rarely). Not because it was "good," but because I knew what to expect. Although... I should probably qualify that bit about expectations: Last time I was there was probably early '22 and only because my dad was in hospice with a craving for one of their menu items (and fries). I bought a BigMac for myself, got home, and saw that the bun was moldy. No thanks!
> More specifically, I thought Snapchat would be different
I briefly tried Snapchat in the early days, and got my jollies from it. I stopped using it when the novelty wore off, and the constant updates and changes to the UI/UX made me disband. Every new update ruined my posting habits and I had to relearn the whole UI/UX over and over. It smelled of 'trying too hard' by the developers.
Same here. I used it back in 2011/2012 if I remember right. It was fairly minimal back then. Now a days, the app has so many buttons and the UI/UX is so complex that it overwhelms the user.
Good writers know everything's already been said before in different ways, but not in different ways /by them/. In other words, we all have a unique voice and style, and it's useful for humanity if people hear that voice and style. So blog. Get out of your own way and share your voice.
Generative AI tweaks the original material such that it's modified beyond recognition, and non verbatim. A bit like how artists tweak other artist's work, put their own spin on it, and then pass it off as 'original'.
GenAI CAN do that, but it also can regenerate training sources as-is. The way LLMs work makes it quite likely that once it has started copying a training sample it will continue to do so (after copying/generating N consecutive words of a training sample, the most statistically likely next word will be often be the N+1th word of that same sample).
The same thing happens for images - the more an output looks like an input, the more likely (as diffusion-based generation proceeds) it is to look more like it. There are recent examples of Dune posters being recreated essentially as-is.
Or produces the watermark from the copyright holder which even Getty can see it is theirs [0], implying that Stability AI trained on Getty's images without their permission and tried to commercialize it via DreamStudio.
Generative AI algorithmically processes the inputs such that they can be roughly recreated after decoding. A bit like how jpeg encodes images "beyond recognition"(aka lossy).
> Every business plan has the word “AI” in it, even if the business itself has no AI in it
I agree. A product needs at least an LLM under the hood, or Bayesian inference, or machine learning, or neural nets to be deemed 'AI'. Otherwise it's just a bunch of if...else statements.
https://ko-fi.com/
https://github.com/sponsors
https://www.patreon.com/
https://www.buymeacoffee.com/
https://www.paypal.com/paypalme/
Any others, let me know