Comment by wlesieutre
21 hours ago
I miss the pre-LLM days when you could make a decent argument that having any unnecessary data was just a liability. Now all anybody thinks is “more data for the AI!”
21 hours ago
I miss the pre-LLM days when you could make a decent argument that having any unnecessary data was just a liability. Now all anybody thinks is “more data for the AI!”
10+ years ago companies were hoovering up data for ML - trying to find correlations in high-dimensionality data. Mostly the results were garbage but occasionally you hit on a real, unexpected phenomenon.
Nowadays you just throw all the data into a black box and believe whatever it says blindly.
Were you not around for the Big Data heyday a decade ago?
Until thumb drives became large enough to fit most datasets it stopped becoming Big Data. Just normal data.
We have thumb drives that can store petabytes of data?
Or did you mean the "big data" crowd which thought 500GB was noteworthy? I don't think anyone took those serious, neither in 2010s nor now. That was always "small" data
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To some degree IMO big data is still a mindset when it might take a day to process your data in a normal SQL query. Some tech doesn't scale to the data size for all use cases, and you need different solutions.
Hell you mean a decade ago? I still see businesses running losses left right and center saying that they're gonna monetize user data, any day now.
Related "monetizing user data" seems to just mean ads. Ads on everything, forever, until the userbase gets fed up and moves to a new service that definitely won't do that, and the cycle repeats about every 3 years.
Data hoarding predates LLMs. There where other machine learning methods which also needed data for training.
“Before LLM’s there was_____”
I see this whenever an LLM’s impact is assessed. We know. The issue is scale and the ability for smaller and smaller groups (down to individuals) to execute at scale.
Fake news always existed. Now one dude in India can flood multiple sock puppet media accounts with right wing content/images (actual example) at a scale previously unimaginable.
Do LLMs require that much more data than the tradional ML approaches we've seen over the years?
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I really hate this when it's something negative that humans also do. It's like, yeah, people do do that, but why are we automating {negativeTrait}?
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> Now one dude in India can flood multiple sock puppet media accounts with right wing content/images (actual example) at a scale previously unimaginable.
I have the faintest possible hope that such things are going to be the death knell of social media. Yeah a lot of credulous idiots are happily giving AI thirst traps their money for stroking their confirmation bias, but that's just who's left at this point. It feels like every social media app I use is gradually bleeding users who aren't hopelessly addicted to the dopamine treadmill, because what's left is just plain unappealing to them, which selects for the people who are most vulnerable to AI shit, which is far from ideal, but also means those platforms are comprised ever more of that vulnerable population and nobody else. And the problem with all these businesses going through that is without a diverse, growing audience, you just become InfoWars, slinging the same slop to the same people every day, and every ounce of said slop is great for what's left of your audience, but absolute garbage for getting anyone new in it. And it just goes on that way until you sputter out and die (or harass the wrong group of parents I guess).
I wish all social media sites a very haha die in a fire.
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