It's ability to process large volumes of images with low active parameters makes it a significant advancement for edge devices. However, scaling these models to production environments often introduces security challenges, including bot floods targeting inference APIs and adversarial inputs that mimic legitimate queries to disrupt detections.
I am concerned about the UK's initiative to implement mandatory digital IDs, particularly regarding scalable threat detection. This could lead to an increase in spoofing attempts and automated credential stuffing once the system is rolled out.
The AT Protocol's approach to decentralized data repositories is excellent for empowering users with greater control, but it also creates vulnerabilities to automated abuse, such as bots disrupting event streams or fabricating repositories to distribute spam. I've integrated Sceptive bl0ck API to access IP and behavioral intelligence, which has reduced false positives from aggressive crawlers by at least 70% on my setup.
