21–30 of 35 posts
As one example, searching for „paper“ brings up dozens of hits in my library of thousands, including a fair number where it took me a while to find the paper. It somehow manages to find two portraits where the person is wearing paper-in-plastic-sleeve ID tags, but not any of the almost identical portraits with all-plastic IDs.
I have mixed feelings about this.. It sounds like a useful feature but I don't want to help Apple to train their algorithms which they're still planning to use to snoop on our computers. Their plans are only 'on hold', not cancelled. Which sounds a lot like they're waiting for the upheaval to blow over, or for some other vendor to introduce this so they can point the finger at them and say they're not doing anything…
Visual Lookup performs poorly on non-Western historical art such as the Fart Battle Scroll (including non-bowdlerized versions). [0] [1] Hopefully Visual Lookup's data set will improve with time and usage. [0] https://archive.wul.waseda.ac.jp/kosho/chi04/chi04_01029/chi... [1] https://www.tofugu.com/japan/fart-scrolls/
> Confusion between the Pissarro and Gallen-Kallela paintings above resulted from a ‘collision’, in which their Neural Hashes are sufficiently similar to result in misidentification, one of the reasons that Apple was dissuaded from using this technique to detect CSAM. So if two literal paintings made centuries ago can cause a hash collision, there's no way this ever should have been considered for matching against fi…
As apple states at the time, any action would require more than one match. For any hash value of a given size, it is trivially easy to calculate the probability of collisions and to adjust required thresholds for any arbitrary rate of false positives. If the FP rate is 1/1000, requiring three „hits“ makes it 1/1,000,000,000, or essentially zero.
Earlier quoted context omitted.
Honestly, I think possibly the biggest problem with indexing Wayback Machine is simply the size. I’m pretty sure it’s growing far faster than anyone can pull WARCs out for indexing, especially because well, it’s not exactly high throughput on the download side. I don’t blame anyone for that, but it does make the prospect of externally indexing feel a bit bleak. At this point, I’d like it if there were just tools to i…
Right, the download speed is definitely an issue (and like you say, it's quite understandable considering the volume/traffic they deal with), and the continual growth is one of many factors I didn't consider. I wonder if the IA would allow someone to interconnect directly with their storage datacenter, if one were to submit a well articulated plan to create this search index/capability. Also, what do you mean by tool…
> Confusion between the Pissarro and Gallen-Kallela paintings above resulted from a ‘collision’, in which their Neural Hashes are sufficiently similar to result in misidentification, one of the reasons that Apple was dissuaded from using this technique to detect CSAM. So if two literal paintings made centuries ago can cause a hash collision, there's no way this ever should have been considered for matching against fi…
As apple states at the time, any action would require more than one match. For any hash value of a given size, it is trivially easy to calculate the probability of collisions and to adjust required thresholds for any arbitrary rate of false positives. If the FP rate is 1/1000, requiring three „hits“ makes it 1/1,000,000,000, or essentially zero.
If it is 1/1000, it is only 1/1,000,000,000 if they have only 3 of images from a customer. They typically have thousands, though. A 1:1000 false positive rate would mean several ones in many iCloud photo databases.
On the plus side, in case of multiple hits, they would have a human look at the images.
The whole thing was intended as a way to make that human check economically viable. Instead of having people look at every picture uploaded to iCloud, they would filter out almost all of them, and only let humans look at the few remaining (where, I guess, ‘few’ still could be a lot, given their number of users)
> Confusion between the Pissarro and Gallen-Kallela paintings above resulted from a ‘collision’, in which their Neural Hashes are sufficiently similar to result in misidentification, one of the reasons that Apple was dissuaded from using this technique to detect CSAM. So if two literal paintings made centuries ago can cause a hash collision, there's no way this ever should have been considered for matching against fi…
It simply does not follow that the classifier for CSAM would have the same rate of false positives. There isn't enough information to infer that.
Earlier quoted context omitted.
As apple states at the time, any action would require more than one match. For any hash value of a given size, it is trivially easy to calculate the probability of collisions and to adjust required thresholds for any arbitrary rate of false positives. If the FP rate is 1/1000, requiring three „hits“ makes it 1/1,000,000,000, or essentially zero.
The false positive rate has to be a lot lower for this to work. If it is 1/1000, it is only 1/1,000,000,000 if they have only 3 of images from a customer. They typically have thousands, though. A 1:1000 false positive rate would mean several ones in many iCloud photo databases. On the plus side, in case of multiple hits, they would have a human look at the images. The whole thing was intended as a way to make that hu…
And it's somewhat irrelevant how the probability of collisions is specifically calulated (1/1000 already assumed 1:n comparisons), as long as we agree it's easy to calculate for a given user. The algorithm does know about the sizes of the respective image libraries, for example, and could adjust the threshold with precision.