<prompt> Taba ea mantlha ke efe ka Adversarial Machine Learning?nan  <response>: Instruction in English: What is the main issue with Adversarial Machine Learning? . Response in English: Adversarial Machine Learning is a technique used to manipulate or mislead machine learning models by feeding them intentionally crafted deceptive input. The main issue with this type of attack is that it can significantly degrade model performance, cause incorrect outputs, and compromise the security and reliability of the system. For instance, an attacker can use adversarial machine learning to evade detection by a security system, manipulate a recommendation engine, or compromise the accuracy of a facial recognition system. This is a growing concern as machine learning models become ubiquitous and increasingly used in critical decision-making processes. Despite the efforts of researchers to understand and develop defenses against adversarial attacks, the problem remains complex and is still an active area of research. . Response in Sesotho: Adversarial Machine Learning ke mokhoa o sebelisoang ho thetsa kapa ho khelosa mefuta ea ho ithuta ea mochini ka ho e fepa ka mokhoa o thetsang o entsoeng ka boomo. Taba e ka sehloohong ea tlhaselo ea mofuta ona ke hore e ka senya tsebetso ea mohlala haholo, ea baka liphello tse fosahetseng, me ea senya tsireletso le botšepehi ba tsamaiso. Mohlala, mohlaseli a ka sebelisa ho ithuta ka mochini oa mohanyetsi ho qoba ho bonoa ke sistimi ea tsireletso, ho thetsa enjine ea likhothaletso, kapa ho senya ho nepahala ha sistimi ea ho lemoha sefahleho. Ena ke taba e ntseng e hola ha mekhoa ea ho ithuta ka mochini e ntse e ata hohle me e sebelisoa le ho feta mekhoeng ea ho etsa liqeto tse bohlokoa. Ho sa tsotellehe boiteko ba bafuputsi ba ho utloisisa le ho ntlafatsa tšireletso khahlanong le litlhaselo tsa bahanyetsi, bothata bo ntse bo le thata me e ntse e le sebaka se sebetsang sa lipatlisiso. 