HelloImSteven
Joined 3 years ago
Joined 3 years ago
For the record, Apple notes that the DSA requirements only impact developers distributing through the App Store, not through alternative distribution [1].
[1]: https://developer.apple.com/help/app-store-connect/manage-co...
Technically, CVEs are meant to only affect one codebase, so a vulnerability in a shared library often means a separate CVE for each affected product. It’s only when there’s no way to use the library without being vulnerable that they’d generally make just one CVE covering all affected products. [1]
Even ignoring all that, people are incorporating Copilot into their development process, which makes it a common dependency.
Other countries have similar issues, of course, but often (not always) they have more cultural factors keeping third spaces alive. In my experience traveling Europe and Africa, community and familial ties generally have a more active role, so there’s just more opportunities for stable third places to develop. It’s not that the spaces are different, imo, but they do seem more common.
Perhaps requiring support for bill capping is the right way to go, but honestly I don’t see why providers don’t compete at all here. Customers would flock to any platform with something like “You set a budget and uptime requirements, we’ll figure out what needs to be done”, with some sort of managed auto-adjustment and a guarantee of no overage charges.
Ah well, one can only dream.
This seems more like a model-specific issue, where it’s consistently generating flawed output every time the cache gets invalid. If that’s the case, there’s not much Google can do on a case-by-case level, but we should see improvements over time as the model gets incrementally better / it becomes more financially viable to run better models at this scale.
[1]: https://www.apple.com/legal/intellectual-property/trademark/...
In any case, clearly the prevailing understanding is wrong in one way or another, and that should be reflected in curriculums alongside this new evidence.
By asking follow-up questions and establishing an in-context vocabulary, users can steer output toward a more complete description. For example, “Let’s call that tool and ‘axe’. How might I hold it?”; the model’s learned associations with holding sharp knives carefully can make “by the handle, with the blade facing away from you” a likely response.
I’m confident you could arrive at a near perfect description of an axe this way without any references or depictions of an axe in the training data. I’d imagine the same applies to many cybsecurity/cyber offense concepts (but probably not all).