3 ms·
Maybe a side-note or off-topic. But am I the only one that's shocked/confused why these giant tech companies have huge models, so much compute to run them on, a
by zo1 3y ago
Maybe a side-note or off-topic. But am I the only one that's shocked/confused why these giant tech companies have huge models, so much compute to run them on, and they still can't get certain basic things right. Something as simple, for Facebook, as detecting a fake profile that's super-obvious to any human that's been on the net for any appreciable amount of time.
- mrtranscendence 3y agoOr how it took Google ages to address the scam "You Win!" YouTube comments disguised as if coming from the videos' posters. How hard could that be, exactly?
- noiseinvacuum 3y agoDetecting a fake profile is a very hard problem and in a very different domain than LLMs. What makes it so difficult is goal to minimize false positives, ideally you do not want to delete profiles of genuine users. Meta has said in the past that their ML models observe how users use their platform like FB to detect is they are bots. Another challenge is that most spammers that slip through these AI systems are not always automated bots like you see on Twitter, there are sometimes paid humans behind these accounts. The sheer scale of this problem is astounding, this stat is from 2019 (https://phys.org/news/2019-05-fake-facebook-accounts-never-ending-bots.html https://phys.org/news/2019-05-fake-facebook-accounts-never-e...). Even if 0.01% of these slip through then it becomes very visible. > Facebook said this week it "disabled" 1.2 billion fake accounts in the last three months of 2018 and 2.19 billion in the first quarter of 2019.
- runeb 3y agoIf you’re measured on number of users, why would you remove lots of them?