<prompt> Etsa mohlala o thehiloeng ho AI o ka khethollang ntja le katse.nan  <response>: Instruction in English: Formulate an AI-based model that can tell the difference between a dog and a cat. . Response in English: One approach to building an AI model to distinguish between dogs and cats is to use supervised learning, specifically convolutional neural networks CNNs.Here is an outline of the steps that could be followed:1. Collect data: Collect a large number of images of dogs and cats to use as training data. These images should be labeled so that the algorithm knows which images are of dogs and which images are of cats.2. Preprocess the data: The images should be preprocessed to be of the same size and format, and optionally apply techniques like data augmentation to generate more data from the existing set. This would greatly help the model later learn and identify features that help it distinguish between dogs and cats.3. Build the model: Create a CNN model that takes in an image as input and outputs a probability of the image being of a dog or a cat. This model could be built from scratch or by using a pre-trained model like ResNet, VGG, or Inception and then fine-tune the last few layers to better fit our specific task.4. Train the model: Train the model using a supervised learning approach, feeding it the labeled images of dogs and cats. The model will learn to identify features that are associated with dogs and features that are associated with cats.5. Evaluate the model: Evaluate the models performance on a hold-out test set to ensure that it can accurately tell the difference between a dog and a cat. Fine-tune the model if necessary and re-evaluate.6. Deploy the model: Once the model is trained and performs well, it can be deployed and used to classify new images of dogs and cats. . Response in Sesotho: Mokhoa o mong oa ho aha mohlala oa AI ho khetholla lipakeng tsa lintja le likatse ke ho sebelisa thuto e hlokometsoeng, haholo-holo marang-rang a convolutional neural CNNs. Mona ke moralo oa mehato e ka lateloang: 1. Bokella lintlha: Bokella palo e kholo ea litšoantšo tsa lintja le likatse ho li sebelisa e le data ea koetliso. Litšoantšo tsena li lokela ho ngoloa e le hore algorithm e tsebe hore na ke litšoantšo life tsa lintja le hore na ke litšoantšo life tsa likatse. 2. Hlakola data esale pele: Litšoantšo li lokela ho sebetsoa esale pele hore li be tsa boholo bo lekanang le sebopeho, me ka boikhethelo li sebelise mekhoa e kang ho eketsa data ho hlahisa lintlha tse ngata ho tsoa ho sete e teng. Sena se ne se tla thusa haholo mohlala ho ithuta hamorao le ho tseba likarolo tse o thusang ho khetholla pakeng tsa lintja le likatse. 3. Haha mohlala: Theha mofuta oa CNN o nkang setšoantšo e le ho kenya le ho hlahisa monyetla oa hore setšoantšo e be sa ntja kapa katse. Moetso ona o ka hahuoa ho tloha qalong kapa ka ho sebelisa mohlala o koetlisitsoeng esale pele joalo ka ResNet, VGG, kapa Inception ebe o lokisa likarolo tse maloa tsa ho qetela hore o lekane hantle mosebetsi oa rona o ikhethileng. 4. Koetlisa mohlala: Koetlisa mohlala ka mokhoa oa ho ithuta o hlokometsoeng, o fepe litšoantšo tse ngotsoeng tsa lintja le likatse. Mohlala o tla ithuta ho khetholla likarolo tse amanang le lintja le likarolo tse amanang le likatse. 5. Hlahlobisisa mohlala: Lekola tsebetso ea mohlala ho sete ea teko ea ho tsoara ho netefatsa hore e ka tseba phapang pakeng tsa ntja le katse ka nepo. Beakanya mohlala ha ho hlokahala me u hlahlobe bocha. 6. Kenya mohlala: Hang ha mohlala o se o koetlisoa me o sebetsa hantle, o ka sebelisoa le ho sebelisoa ho arola litšoantšo tse ncha tsa lintja le likatse. 