<prompt> Hlalosa hore na hobaneng Molao oa Hebb o le bohlokoa ho marang-rang a maiketsetso a methapo ea kutlo.nan  <response>: Instruction in English: Explain why Hebbs Rule is important in artificial neural networks. . Response in English: Hebbs Rule, also known as Hebbian Learning, is an important concept in the field of artificial neural networks, as it provides a fundamental mechanism by which these networks can learn and adapt over time. The rule, which was first proposed by Canadian psychologist Donald Hebb in 1949, is based on the idea that the strength of the connection between two neurons is increased when they fire together. This means that if a particular input consistently leads to a particular output, the strength of the connections between the neurons associated with that inputoutput pair will become stronger, making it more likely that the same output will be produced in the future when the same input is encountered. In other words, neurons that fire together, wire together. This simple principle enables neural networks to learn and adapt, by strengthening the connections for frequently used pathways, while weakening those for infrequently used ones.Hebbs Rule is important because it provides a simple and biologically plausible mechanism for how neurons in a network can change their connection strengths in response to experience or stimuli. This enables the network to learn, by adjusting the connection weights to improve performance over time. As a result, it has been widely adopted as the basis for many learning algorithms in neural networks, and continues to play a central role in the field of artificial intelligence today. . Response in Sesotho: Molao oa Hebb, o tsejoang hape e le Hebbian Learning, ke mohopolo oa bohlokoa lefapheng la marang-rang a maiketsetso, kaha o fana ka mokhoa oa mantlha oo marang-rang ana a ka ithutang le ho ikamahanya le maemo ha nako e ntse e ea. Molao ona, o ileng oa hlahisoa ka lekhetlo la pele ke setsebi sa kelello sa Canada Donald Hebb ka 1949, o thehiloe khopolong ea hore matla a kamano pakeng tsa li-neuron tse peli a eketseha ha li thunya hammoho. Sena se bolela hore haeba kenyeletso e itseng e lula e lebisa tlhahisong e itseng, matla a likhokahano lipakeng tsa li-neurone tse amanang le paramente eo ea ho kenya letsoho e tla ba matla, e leng se etsang hore ho be bonolo hore tlhahiso e tšoanang e hlahisoe nakong e tlang ha e tšoanang. ho fihleloa. Ka mantsoe a mang, li-neurone tse tukang hammoho, li hokahana hammoho. Molao-motheo ona o bonolo o nolofalletsa marang-rang a methapo ea kutlo ho ithuta le ho ikamahanya le maemo, ka ho matlafatsa likhokahano tsa litsela tse sebelisoang khafetsa, ha a ntse a fokolisa a sa sebelisoeng khafetsa. Molao oa Hebb o bohlokoa hobane o fana ka mokhoa o bonolo le o utloahalang oa baeloji hore na li-neurone marang-rang li ka fetola matla a tsona a khokahanyo ho latela boiphihlelo kapa tšusumetso. Sena se nolofalletsa marang-rang ho ithuta, ka ho lokisa boima ba khokahanyo ho ntlafatsa tsebetso ka nako. Ka lebaka leo, e amohetsoe ka bophara e le motheo oa li-algorithms tse ngata tsa ho ithuta marang-rang a methapo ea kutlo, me e ntse e tsoela pele ho bapala karolo ea mantlha lefapheng la bohlale ba maiketsetso kajeno. 