with
Joined 1 year ago
Joined 1 year ago
It's just a hobby for me (just $100/month in IAP revenue rn) but I really don't understand their system at all.
it's a real issue but I'm not sure it's the mass mobilization problem the article makes it out to be. pretty sure it's growing extremely fast, and it's a new field in general. the models will keep growing in capability because of human game theory (I need to make my model better because my competitors are). it's not practical to expect millions in headcount to move from frontier capability research to safety
I’m so tired of all this BS. Why did this become normal? and how do we not read this as cheap advertising?
They have been proven to: https://www.anthropic.com/research/small-samples-poison
The “bundle” or “context” is the value.
still, i use it every day and i don't see what replaces it. every "docker killer" solves one problem while ignoring the 50 things docker does well enough.
That said, their accuracy claims have been disputed before. Inside Higher Ed [1] reported that Turnitin's real-world false positive rate was higher than originally asserted, and the company declined to disclose the updated number. And, USD also noted that while Turnitin claimed <1% false positives, a Washington Post investigation found a 50% rate on a smaller sample, and that non-native English speakers / neurodivergent students get flagged at higher rates [2].
Now, those are from 2023 and the product (and AI in general) has been updated drastically since. But the broader incentive problem holds even if the detector itself is conservatively tuned. The product is a black box. And the downstream cost of errors falls entirely on students, not on Turnitin's renewal rate. You don't need aggressive tuning for the incentive structure to be broken.
[1] https://www.insidehighered.com/news/quick-takes/2023/06/01/t...
[2] https://lawlibguides.sandiego.edu/c.php?g=1443311&p=10721367