- Izimiso eziyisisekelo zokwakha ukuqinisekisa ukuthembeka, ukuphepha, kanye nokwenza ngcono izindleko emisebenzini ye-AI.
- Ukuhlaziywa okuphelele kwamaphethini okuklama ama-ejenti, kusukela ezinhlelweni ezilula zama-ejenti eyodwa kuya kubaxhumanisi abayinkimbinkimbi kanye nama-swarms.
- Umthelela obalulekile wekhwalithi yedatha, ukuphathwa, kanye nokutholakala kokunemba kanye nokuziphatha kwamamodeli obuhlakani bokwenziwa.
Uma sikhuluma ngokwakha izinhlelo zobuhlakani bokwenziwa, ngezinye izikhathi siyathatheka yi-hype bese sikhohlwa ukuthi ukuzinza kohlelo yikho okuhlukanisa ngempela ithoyizi lobuchwepheshe nethuluzi lebhizinisi elibalulekile. Akusekho nje nge-AI ekwazi ukubhala inkondlo noma ukukhiqiza isithombe esihle, kodwa mayelana nokuba nokwethenjelwa, okubikezelwayo, nokuphephile ezindaweni lapho iphutha elilodwa lingabiza imali eningi noma lithinte izinkulungwane zabasebenzisi.
Ngalo mqondo, ukugxila kuguqukela ekudalekeni nje kuye ekusebenzeni kahle kanye nokunciphisa izithiyo zokusungula izinto ezintsha. Ngenkathi i-AI yokukhiqiza ngezinye izikhathi ingafiki ezingeni elilindelekile, i-AI yokukhiqiza , ekwazi ukucabanga nokusebenzisa amathuluzi ngokuzimela, ivula amathuba amaningi kakhulu okwenza imisebenzi eyinkimbinkimbi ngokuzenzakalela.
Izinsika Zokwethembeka Ekwakhiweni Kwe-AI
Ukuze kuvinjelwe ipulatifomu ye-AI ukuthi ingawi lapho ithrafikhi iqala ukwanda, kubalulekile ukusebenzisa izinhlaka eziqinile. Isici esibalulekile ukunciphisa amaphuzu okuhluleka okukodwa ; asikwazi ukukhokhela ukuthembela esibonelweni esisodwa sengxenye ebalulekile. Isixazululo sisekudaleni ukuphindaphinda kuwo wonke ama-node nokusebenzisa ukutholakala okuphezulu kwefu.
Kubalulekile futhi ukwenza ukuhlaziywa okujulile kokwehluleka okungenzeka. Ukusebenzisa amaphethini afana nomklamo we-Bulkhead kukuvumela ukuthi uhlukanise amaphutha ukuze angasakazeki kulo lonke uhlelo, kuyilapho izindlela zokuzama kabusha zisiza ekuphatheni lawo maphutha esikhashana avame kakhulu kumakholi we-API.
Ukuthembeka akukhona nje ukuthi uhlelo lukhona ku-inthanethi; kumayelana nokuvumelana kwezimpendulo zalo. Lokhu kusho ukulinganisa imigomo yokutholakala phakathi kwemodeli yokunquma kanye nesizindalwazi. Uma indawo yokugcina idatha iwa, i-AI ayisebenzi. Ngaphezu kwalokho, kubalulekile ukuklama ulwazi lomsebenzisi oluthembekile , ukwazisa abasebenzisi nge-interface mayelana nezikhathi zokulinda ezingaba khona ukuze kuphathwe okulindelwe amakhasimende.
Ukuphepha, Izindleko kanye Nokusebenza Okuhle Kakhulu
Ukuphepha kwe-AI kuyibhizinisi eliyinkimbinkimbi ngoba sibhekene nedatha ebucayi. Kubalulekile ukusebenzisa ukulinganisela kokuqukethwe kuzo zombili izinhlangothi nokuqinisekisa ukuthi ukubethela kukhona kokubili ngesikhathi sokuphumula kanye nesikhathi sokuthutha. Ukuze kuvinjelwe abahlaseli ekukhipheni idatha yokuqeqesha, amasu athuthukile njengokubethela kwe-homomorphic angacatshangelwa.
Ngokombono wezezimali, umgomo akukhona nje ukunciphisa izindleko, kodwa ukwandisa ukutshalwa kwezimali . Kubalulekile ukwenza imodeli yezindleko ngokusekelwe kumthamo wedatha kanye nokuvama kombuzo. Isu elihlakaniphile ukusebenzisa amazinga aqondile okuqeqesha okusekela ukuphazamiseka kanye nokubala okunwebekayo ukuze kugwenywe ukukhokhela izinsiza ezingasebenzi.
Ukuze sifinyelele ukusebenza kahle, kumele samukele imiqondo ye -MLOps kanye ne-GenAIOps . Lokhu kusho ukwenza ngokuzenzakalelayo ukutholakala kokuguquguquka kwemodeli kanye nokusungula izilinganiso zekhwalithi ezicacile kusukela ekuqaleni. Ukukhetha izixazululo ze-PaaS kune-self-hosting ngokuvamile kwenza imisebenzi yansuku zonke ibe lula futhi kunciphisa umthwalo womsebenzi wezobuchwepheshe wethimba.
Amaphethini Okuklama Ama-ejenti E-AI
Lapho sikhetha indlela yokuhlela ubuhlakani besistimu yethu, sinezindlela eziningana kuye ngokuthi buyinkimbinkimbi kangakanani. Uhlelo lwe-ejenti eyodwa luyindawo yokuqala efanele; imodeli iyacabanga, ihlela, futhi isebenzisa amathuluzi ukuxazulula isicelo. Kulula, kodwa kungaba kancane noma kunganembile uma siyicela ukuthi yenze izinto eziningi kakhulu ngesikhathi esisodwa.
Uma umsebenzi uba mkhulu kakhulu, sithuthela ezinhlelweni zama-ejenti amaningi , lapho sihlukanisa khona umgomo ube yimisebenzi emincane enikezwe ochwepheshe. Lapha sithola amaphethini amaningana athakazelisayo:
- Iphethini Elilandelanayo: Ama-ejenti asebenza ngochungechunge; umphumela wesinye uwukufaka kwesinye. Lokhu kulungele izinqubo eziqinile neziphindaphindwayo.
- Iphethini Ehambisanayo: Ama-ejenti amaningana asebenza ngasikhathi sinye emisebenzini ezimele, bese umphumela uhlanganiswa, okuyinto kunciphisa kakhulu ukubambezeleka.
- Iphethini ye-Loop: Uchungechunge luyaphindwa kuze kube yilapho kuhlangatshezwana nesimo, okuwusizo kakhulu ku- ukucwengwa okuphindaphindayo kokuqukethwe.
- Ukubuyekezwa Nokugxekwa: I-ejenti eyodwa ikhiqiza umsebenzi kanti enye isebenza njengomhloli wamabhuku, iwulahla noma iwuvumela ukuqinisekisa ukuthi ikhwalithi ephezulu.
Ezimweni ezingacacile, iphethini yomxhumanisi isebenzisa imodeli ephakathi enquma ngokuguquguqukayo ukuthi iyiphi i-ejenti okufanele inikezwe umsebenzi. Uma ubunzima bukhulu kakhulu, ukuwohloka kwesigaba noma ngisho nephethini yokuhlanganisa kungasetshenziswa , lapho ama-ejenti ebambisana futhi ephikisana khona ngaphandle komholi ophakathi, yize lokhu kwamuva kukhulisa kakhulu izindleko zokusebenza kanye nokubambezeleka.
Asikwazi ukukhohlwa iphethini ye -ReAct (Reasoning and Action) , evumela umenzi ukuthi abonise, enze, futhi abuke ngomjikelezo oqhubekayo, alungise uhlelo lwakhe ngokushesha. Futhi, vele, ezinqubweni ezibalulekile, iphethini yokungenelela komuntu ibalulekile , lapho uhlelo luyeka khona ukuze umuntu akwazi ukuqinisekisa isinqumo ngaphambi kokuqhubeka.
Ukubaluleka Okubalulekile Kwekhwalithi Yedatha
Singaba nemodeli ye-ejenti engcono kakhulu, kodwa uma siyinika idatha yokulahla, sizothola imiphumela yokulahla. Ikhwalithi , ukuphelela, kanye nokufaneleka kolwazi yizinsika ezisekela noma iyiphi imodeli ye-Machine Learning noma i-Generative AI. Idatha ebandlululayo ingaholela ezinqumweni ezibandlululayo , njengoba kwenzekile ezimweni zangempela ngama-algorithms okuqasha noma okukhangisa.
Ukuze kugwenywe lezi zinhlekelele, kubalulekile ukusebenzisa ukuphathwa kwedatha okuqinile . Lokhu kuhlanganisa konke kusukela ekuhlanzweni kwedatha kuya ekuqedeni ukufana kuya ekusetshenzisweni kwezakhiwo ezifana ne -Data Fabric noma i-Data Mesh , okuvumela umbono ohlangene noma ohlukaniswe ngokomthetho wolwazi kuye ngezidingo zenkampani.
Ngaphezu kwalokho, kumelwe sivikele ekufakweni kwemininingwane , lapho abahlaseli bethula khona ulwazi olunonya kudatha yokuqeqesha ukuze bonakalise imodeli. Ukusebenzisa izilawuli zobuqotho kanye nokwenza ukuhlolwa okuvamile kuyindlela kuphela yokuqinisekisa ukuthi i-AI ayibi yingozi yokuphepha.
Ezingeni elihlelekile, izinkampani ziyashintsha ziye kumodeli ye-AI egxile kudatha . Akusekho nje ukulungisa imodeli, kodwa kumayelana nokwenza ngcono umthombo wedatha. Ukutshala imali kumathuluzi okuthola idatha nokucebisa kuvumela amamodeli ukuthi abe nobulungiswa, anembe kakhudlwana, futhi asebenze kahle kakhudlwana , kuvimbele uhlelo ekukhiqizeni idatha engamanga noma eyenziwe.
Yonke le ngqalasizinda, kusukela ekukhetheni iphethini ye-ejenti kanye nokuqina kwamafu kuya ekuhlanzweni kwedatha okungapheli, yakha isisekelo se-AI ekhiqizayo. Ngokuhlanganisa ukuqina kwamapulatifomu anekhodi ephansi kanye nokuqina kwezakhiwo kanye nokuphepha okuqinile, izinhlangano zingaguqula i-AI isuke ekubeni nelukuluku lobuchwepheshe ibe yinjini yangempela neqhubekayo yenani.
