<prompt> Ngola mathata a mang a ho sebelisa pono ea komporo litsebetsong tsa bohlale tsa maiketsetso.nan  <response>: Instruction in English: List some disadvantages of using computer vision in artificial intelligence applications. . Response in English: 1. Difficulty Recognizing Objects in Images: Computer vision systems are often limited in their ability to accurately recognize objects in images, especially if those objects are partially obscured, in motion, or in low light.2. High Resource Consumption: Computer vision algorithms can consume a significant amount of computational resources, requiring powerful processors, large amounts of memory, andor specialized hardware such as GPUs.3. Limited Recognition In Complex Scenes: In complex scenes, where there may be a large number of objects and a lot of activity, computer vision algorithms may struggle to accurately recognize and label all of the relevant elements.4. Expensive Development and Maintenance: Developing and maintaining a computer vision system can be an expensive and time-consuming process, requiring specialized expertise in both computer vision and the specific application domain.5. Lack of Robustness: Computer vision systems can sometimes be brittle, failing to function as expected when faced with inputs that differ from those seen during training or when operating in challenging environments.6. Bias in Training Data: If a computer vision system is trained using biased data, it may reproduce and even amplify those biases in its outputs, potentially leading to inaccurate or unfair results.7. Vulnerability to Adversarial Attacks: Computer vision systems can be vulnerable to adversarial attacks, where inputs are manipulated in order to produce incorrect or misleading outputs. . Response in Sesotho: 1. Bothata ba ho Lemoha Lintho Tse Litsoantsong: Hangata lisebelisoa tsa khomphutha tsa ho bona li na le moeli oa bokhoni ba tsona ba ho lemoha ka nepo lintho tse setšoantšong, haholo-holo haeba lintho tseo li patehile ka mokhoa o itseng, ha li sisinyeha kapa li le khanya e tlaase. 2. Tšebeliso e Phahameng ea Lisebelisuoa: Li-algorithms tsa pono ea khomphieutha li ka sebelisa lisebelisoa tse ngata tsa computational, tse hlokang li-processor tse matla, mohopolo o moholo, le kapa lisebelisoa tse khethehileng tse kang GPUs. 3. Kamohelo e Lekanyelitsoeng Libakeng Tse Ratang: Litšoantšong tse rarahaneng, moo ho ka nang ha e-ba le lintho tse ngata tse ngata le mesebetsi e mengata, li-algorithms tsa pono ea khomphieutha li ka na tsa thatafalloa ho lemoha ka nepo le ho tšoaea lintlha tsohle tse amehang. 4. Ntlafatso le Tlhokomelo e Theko e Chesang: Ho theha le ho boloka sistimi ea pono ea khomphutha e ka ba tsebetso e theko e boima le e jang nako, e hlokang tsebo e khethehileng ponong ea komporo le sebaka se ikhethileng sa kopo. 5. Ho hloka Matla: Ka linako tse ling mekhoa ea pono ea khomphieutha e ka senyeha, ea hlōleha ho sebetsa kamoo ho neng ho lebeletsoe kateng ha e tobane le lintlha tse fapaneng le tse bonoang nakong ea koetliso kapa ha li sebetsa libakeng tse thata. 6. Leeme ka Boitsebiso ba Koetliso: Haeba tsamaiso ea pono ea khomphieutha e koetliselitsoe ho sebelisa lintlha tse leeme, e ka na ea hlahisa le ho eketsa leeme leo liphethong tsa eona, e leng se ka lebisang liphellong tse sa nepahalang kapa tse sa lokang. 7. Kotsi ea Litlhaselo Tsa Bahanyetsi: Mekhoa ea pono ea khomphieutha e ka ba kotsing ea ho hlaseloa ke bahanyetsi, moo ho kenngoa ho etsoang ka bolotsana e le ho hlahisa liphello tse fosahetseng kapa tse khelosang. 