 Boyeba bokeseni ya minene kati na makanisi mibale.
Intelligence artificielle (AI) mpe Machine Learning (ML) ezali makanisi mibale oyo ezali na boyokani, kasi ezali na mwa bokeseni ya ntina kati na yango mibale. Na niveau ya likolo, Intelligence Artificielle elakisi makoki ya ordinateur to machine ya ko imiter to ko reproduire ba fonctions cognitives ya esprit ya mutu, lokola koyekola pe ko résoudre ba problèmes. Nzokande, Machine Learning ezali sous-ensemble ya AI oyo esangisi kosalela ba algorithmes mpe ba modèles statistiques mpo na ko permettre ba machines e améliorer performance na yango na mosala moko spécifique na tango na koyekola na ba données na esika ya programmation explicite. Moko ya bokeseni monene kati na AI mpe ML ezali bonene na yango. AI esɛngaka kotonga bamasini oyo ekoki kosala misala ndenge na ndenge ya mayele, kobanda na kososola elobeli ya bozalisi tii na koyeba ba modèles mpe kozwa bikateli. Nzokande, Machine Learning etali mingi kopesa nzela na ba machines koyekola mpe kobongisa performance na yango na misala ya sikisiki, mingi mingi na ko analyser ba ensembles ya ba données ya minene. Bokeseni mosusu ya ntina kati na makanisi yango mibale ezali ndenge oyo ekokisaka mikano na yango. Ba systèmes AI ekoki kosalela ba techniques ndenge na ndenge, na kati na yango ba systèmes basé na mibeko, ba systèmes ya expert, mpe logique floue, mpo na ko permettre ba machines emekola mayele ya bato. Nzokande, Machine Learning etali mingi kosala ba algorithmes oyo ekoki koyekola na ba données, koyeba ba modèles, mpe kosala ba prédictions. Na bokuse, Intelligence Artificielle ezali likanisi ya monene oyo esangisi ba machines kozala na makoki ya kosala misala oyo normalement elingaki kosenga mayele ya moto, alors que Machine Learning ezali sous-ensemble ya AI oyo etali mingi kosalela ba algorithmes mpe ba modèles statistiques mpo na ko permettre ba machines e apprendre na ba données mpe kobongisa ya bango kosala na misala ya sikisiki.