- Amamodeli amakhulu olimi ayizinhlelo zokufunda ezijulile ezibikezela amathokheni ngokomongo, zisebenzisa izakhiwo ze-transformer kanye nokuzinaka esikhundleni sezindlela ezindala ze-n-gram noma eziphindaphindayo.
- Umjikelezo wokuphila we-LLM uhlanganisa ukuqeqeshwa kwangaphambi kokuqeqeshwa okukhulu okuqondiswa nguwe, ukulungiswa okuqondiwe kanye nokuqagela okwenziwe ngcono, kuncike kakhulu kuma-GPU kanye namasu afana nokulinganisa kanye ne-LoRA.
- Ukusesha ngamandla kwe-LLM, ukukhiqiza umbhalo, abasizi bokubhala amakhodi kanye ne-AI yengxoxo kuzo zonke izimboni, kodwa futhi kwethula izingozi zokubona izinto ezingekho, ukucwasa, izinkinga zobumfihlo kanye nokusetshenziswa kabi kwezokuphepha.
- Intuthuko yesikhathi esizayo izogxila ekuqondeni okuphezulu, amakhono amaningi kanye nokuqondanisa okungcono, okwenza ukubambisana kwabantu ne-AI kube namandla kakhulu ngenkathi kukhulisa izinselele zokuziphatha nezokulawula.
Amamodeli olimi asuke ekubeni ngumqondo obalulekile kwisayensi yamakhompyutha aya enjinini engabonakali ngemuva kwamathuluzi afana ne-ChatGPT, i-Gemini, i-Claude noma i-Copilot asetshenziswa yizigidi zabantu nsuku zonke. Uma ucela i-AI ukuthi ifingqe isihloko, ibhale i-imeyili, ichaze umqondo oyinkimbinkimbi noma ngisho nokubhala ikhodi, uxhumana nemodeli yolimi, futhi ngokuvamile nemodeli yolimi enkulu (i-LLM). Ukuqonda ukuthi ayini, ukuthi asebenza kanjani nokuthi imingcele yawo ikuphi manje kubalulekile njengokwazi ukusebenzisa isiphequluli noma injini yokusesha.
Ngisho noma ungeyena umhleli wezinhlelo, intatheli noma usosayensi wedatha, ukuqonda izisekelo ze-LLM kukusiza ukuthi uzisebenzise ngempumelelo, ngokuziphatha nangokuphepha. Lezi zinhlelo zingazizwa sengathi "zihlakaniphile" engxoxweni, kodwa ngaphansi kwazo kunemishini eyinkimbinkimbi yokucabanga eqeqeshwe ekuqoqweni kwemibhalo emikhulu. Zingaba usizo olukhulu emsebenzini nasekufundeni, kodwa futhi ziveza imibono engalungile, ziphinde ziveze ubandlululo futhi ziphakamise imibuzo mayelana nobumfihlo, ilungelo lobunikazi kanye nekusasa lemisebenzi eminingi.
Iyini imodeli yolimi futhi yini eyenza ibe “nkulu”?
Imodeli yolimi uhlelo lwe-AI oluqeqeshwe ukulinganisa ukuthi kungenzeka kangakanani ukuthi ithokheni (igama, igama elingaphansi noma uhlamvu) livele ngokulandelana, uma kubhekwa umongo ozungezile. Empeleni, lokho kusho ukuthi lifunda amaphethini ezibalo mayelana nokuthi izingcezu zombhalo zivame ukulandelana kanjani. Uma ubona okungenalutho emshweni onjengokuthi “Uma ngizwa imvula ophahleni lwami, ngi-____ ekhishini lami”, imodeli yolimi inika amathuba okuqedwa okuhlukene njengokuthi “isobho lokupheka”, “ukushisa ikettle”, “ukuthatha ubuthongo” noma “ukuphumula”. Inketho enamathuba aphezulu kakhulu, noma ethathwe ngokungahleliwe phakathi kwabantu abanamathuba aphezulu, iba yisibikezelo semodeli.
Amamodeli olimi lwanamuhla anweba lo mbono oyisisekelo kusukela ezikhaleni ezimfushane kuya emishweni ephelele, izigaba noma imibhalo. Indlela efanayo egcwalisa umusho ongekho ingasetshenziswa ukukhiqiza izindinyana ezinde zombhalo, ukufingqa izihloko, ukuhumusha phakathi kwezilimi noma ukuphendula imibuzo: imodeli ihlala ibikezela amathokheni alandelayo anengqondo ngokusekelwe kulokho esekubonile kakade.
Imodeli Yolimi Olukhulu (i-LLM) imane nje iyimodeli yolimi esebenzisa ukufunda okujulile, amasethi edatha amakhulu kanye nenani elikhulu lamapharamitha angaphakathi. Lawa mapharamitha asebenza “njengezinkinobho” ezilungisekayo inqubo yokuqeqesha ezilungisa ukuze imodeli ibambe uhlelo lolimi, amaqiniso, isitayela kanye namaphethini okucabanga. Ama-LLM amanje avame ukuba namapharamitha ayizigidigidi noma ngisho nezigidigidi, okuyilokho igama elithi “elikhulu” elibhekisela kukho. Amamodeli olimi amancane, anamapharamitha ambalwa kakhulu, nawo akhona futhi kulula ukuwasebenzisa kumadivayisi anezisetshenziswa ezilinganiselwe, kodwa ngokuvamile anikeza amakhono alinganiselwe kakhulu.
Njengengxenye encane yobuhlakani bokwenziwa, ama-LLM agxila ngqo ekuqondeni nasekukhiqizeni ulimi lwemvelo. Angaphakathi kwensimu ebanzi ye-AI, ehlanganisa nezinhlelo zezithombe, amavidiyo, amarobhothi, izincomo, ukubikezela kanye neminye imisebenzi eminingi. Ama-LLM angenye yezinhlobo ezivelele kakhulu ze-AI yokukhiqiza: amamodeli adala okuqukethwe okusha (umbhalo, ikhodi, izithombe, umsindo noma ividiyo) kunokuba nje ahlukanise noma abeke idatha ekhona ezingeni.
I-AI Ekhiqizayo, ama-LLM kanye nencazelo ye-GPT
I-AI Ekhiqizayo yigama elihlanganisa amamodeli angakhiqiza okuqukethwe okusha, kanti ama-LLM ayigatsha elikhethekile lombhalo lalowo mndeni. Imodeli yesithombe ekhiqizayo efana ne-DALL‑E noma i-Midjurney idala izithombe kusukela ekubonisweni; imodeli yomculo ibhala umsindo; imodeli yolimi ikhiqiza noma iguqula umbhalo. Wonke ama-LLM ayi-AI ekhiqizayo, kodwa akuwona wonke amamodeli ekhiqizayo angamamodeli olimi.
Isifinyezo esithi “GPT” osibona kumathuluzi afana ne-ChatGPT simelela “i-Generative Pre‑trained Transformer”. Igama elithi “Transformer” libhekisela ekwakhiweni kwenethiwekhi ye-neural eyethulwe ephepheni lika-2017 elithi “Attention Is All You Need”, eliye laba indinganiso yangempela yamamodeli olimi. Igama elithi “Pre‑trained” lisho ukuthi imodeli iqeqeshwa kuqala kumasethi edatha amakhulu ombhalo ojwayelekile ngaphambi kokuba ivumelane nemisebenzi ethile. Igama elithi “Generative” liqokomisa ukuthi ingadala umbhalo omusha, hhayi nje ukuwubeka ilebula noma ukuwubeka ezingeni.
Amamodeli amakhulu njenge-GPT‑4, i-Claude, i-Gemini noma i-Llama aqale aqeqeshwe kusengaphambili ngendlela yokuziqondisa bese kamuva ehlungwa. Endabeni ye-GPT‑4, isibonelo, i-LLM eyisisekelo ilungiswa ngokwengeziwe kusetshenziswa ukufunda okugadiwe kanye nokufunda kokuqinisa okuvela kumpendulo yabantu kanye ne-AI ukuze izimpendulo zayo zibe usizo kakhulu, zingalimazi futhi zihambisane nemiyalelo yomsebenzisi.
Kusukela kuma-n-gram kuya kumanethiwekhi e-neural: indlela ukumodela ulimi okwavela ngayo
Amamodeli okuqala olimi ayesekelwe kuma-n-gram: ukulandelana kobude obungaguquki bamagama akhishwe ku-corpus yokuqeqesha. Imodeli ye-bigram (2-gram) ibheka amabhangqa amagama afana nokuthi “ukhona”; imodeli ye-trigram (3-gram) icubungula ama-triplets afana nokuthi “ulungile”. Uma inikezwe okokufaka okufana nokuthi “u-orange is”, imodeli ye-trigram ihlola ukuthi kuvela kangaki “u-orange uvuthiwe” uma kuqhathaniswa nokuthi “u-orange ujabule” kudatha yayo yokuqeqesha bese ikhetha ukuqhubeka okuvamile.
Nakuba ama-n-gram amakhulu ebamba umongo owengeziwe, asheshe ahlangane nokwahlukana kwedatha. Njengoba u-N ekhula, ukulandelana ngakunye kwamathokheni e-N kuba yinto engavamile noma eyingqayizivele, ngakho-ke imodeli inezibonelo ezimbalwa kakhulu zokulinganisa amathuba athembekile kuzo. Lokho kwenza ukubikezela kube nzima, ikakhulukazi emibhalweni emide noma ehlukahlukene. Amamodeli e-N-gram nawo alwela ukufaka umongo oqhelelene kakhulu nendawo yamanje emshweni noma esigabeni.
AmaNethiwekhi Emizwa Aphindaphindayo (ama-RNN) ayeyisinyathelo esilandelayo esikhulu, esenzelwe ukuphatha ukulandelana kwethokheni ngethokheni ngenkathi egcina inkumbulo ethile yalokho okwafika ngaphambili. I-RNN ifunda umusho igama negama, ibuyekeza isimo sangaphakathi esifingqa umongo wangaphambilini. Lokhu kuyivumela ukuthi ifake ulwazi oluningi kune-n-grams elula futhi ibonise ukuxhomekeka okude, ngendlela efana nendlela umuntu alandela ngayo umusho okhulunywayo ngokuhamba kwesikhathi.
Kodwa-ke, ama-RNN asenemikhawulo ngezimo ezinde kakhulu ngenxa yenkinga yokunyamalala kwe-gradient ngesikhathi sokuqeqeshwa. Ithonya lamathokheni okuqala livame ukuphela njengoba ukulandelana kukhula, okwenza kube nzima ngemodeli ukufunda ubudlelwano phakathi kwamagama akude noma ukugcina umongo emishweni eminingi noma ezigabeni. Ukuqeqesha ama-RNN ngezimo ezinde nakho kuyadinga ukubalwa futhi kunzima ukufanisa.
Ama-Transformers kanye nokuzinaka: umongo wama-LLM anamuhla
Ama-Transformers ashintshe indlela yokumodela ulimi ngokufaka esikhundleni sokucubungula okulandelanayo ngendlela ebizwa ngokuthi ukuzinaka okungabheka wonke amathokheni ngokulandelana ngasikhathi sinye. Esikhundleni sokufunda umusho osuka kwesobunxele uye kwesokudla, ungqimba lwe-transformer luvumela ithokheni ngayinye "inake" kunoma iyiphi enye ithokheni, kungakhathaliseki ukuthi ibanga lingakanani. Lo mklamo uhambisana kakhulu, okwenza ukuqeqeshwa kumasethi edatha amakhulu kusebenze kangcono kunezindlela ezindala.
Isinyathelo sokuqala ku-transformer yi-tokenization, lapho umbhalo uhlukaniswa khona ngama-token (amagama, amagama angaphansi noma izinhlamvu) imodeli engazisingatha. I-token ngayinye ibe isifakwa ku-vector yezinombolo eyaziwa ngokuthi i-embedding. Lawa ma-embedding ayindlela yemodeli yokumelela incazelo: amagama noma amagama angaphansi avela ezimweni ezifanayo agcina enama-vector afanayo esikhaleni esiphezulu.
Ama-Transformers engeza ama-encoding esikhundla ukuze ithokheni ngayinye ithwale ulwazi mayelana nokuthi ivela kuphi ochungechungeni. Ngenxa yokuthi ukuzinaka akwazi ngokwemvelo ukuthi ithokheni iza kuqala noma ekugcineni, lezi zimpawu zesikhundla zisiza imodeli ukuhlukanisa "inja yaxosha ikati" nokuthi "ikati laxosha inja" nokuqonda ukuhleleka kwamagama, okubalulekile kuhlelo lolimi nencazelo.
Ngaphakathi kwekhanda ngalinye lokunaka, ukushumeka kwethokheni kulinganiselwa kumavekhtha amathathu ahlukene: umbuzo, ukhiye kanye nenani. Lokhu kukhiqizwa yi-matrix yesisindo esifundiwe ngesikhathi sokuqeqeshwa. Ngokwemvelo, umbuzo umelela lokho ithokheni "elikufunayo" kwamanye amathokheni; ukhiye uchaza uhlobo lolwazi "olunikezwa" ithokheni; inani liphethe okuqukethwe okuzohlanganiswa ngempela lapho ukunaka kubalwa.
Imodeli ibala amaphuzu okunaka ngokulinganisa ukuthi umbuzo ngamunye ufana kangakanani nokhiye ngamunye bese ilungisa la maphuzu. Isisindo sokunaka esiphumelayo sinquma ukuthi ivektha ngayinye yenani inikela kangakanani ekumelelweni okubuyekeziwe kwethokheni ethile. Amathokheni anokubaluleka okuphezulu kunalena yamanje athola izinsimbi ezinkulu, kuyilapho amathokheni angasizi ngalutho (njengamanye amagama okumisa) ehliswa.
Ngale nqubo, ukuzinaka kudala ukuxhumana okunesisindo phakathi kwawo wonke amathokheni, kubamba kokubili ukuncika kwendawo kanye nokwesikhathi eside ngendlela eguquguqukayo. Ezingqimbeni eziningi ze-transformer ezihlanganisiwe, ukushumeka kuhlungwa ngokuphindaphindiwe, kuguqula ama-vector okuqala angavuthiwe abe izethulo ezicebile zomongo ezifaka uhlelo lolimi, i-semantics, isitayela ngisho namathiphu olwazi lomhlaba kanye namaphethini okucabanga.
I-LLM evamile iqukethe izendlalelo eziningi ezinjalo kanye nenani elikhulu lezinsimbi eziqeqeshwayo (amapharamitha) ezisakazeke kuzo zonke. Lezi zinhlaka ziyizinto eziguquguqukayo zokucushwa kwangaphakathi ezinquma ukuthi okokufaka kucutshungulwa kanjani nokuthi yikuphi okuphumayo okukhiqizwayo. Amamodeli amakhulu angaba nezigidigidi zamapharamitha, kuyilapho “amamodeli olimi amancane” esebenzisa ambalwa kakhulu, ehweba ngomthamo oluhlaza ukuze kube lula ukuwasebenzisa kumadivayisi anezinsiza eziphansi noma ihadiwe enqenqemeni.
Indlela ama-LLM aqeqeshwa futhi alungiswa ngayo
Umjikelezo wokuphila we-LLM uhilela izigaba eziningana ezihlukene: ukulungiswa kwedatha, ukuqeqeshwa kwangaphambi kwesikhathi, ukulungiswa kahle kanye nokucabanga. Isigaba ngasinye sakha amakhono kanye nokulinganiselwa kwemodeli ngezindlela ezahlukene futhi sinemiphumela ebalulekile ngekhwalithi, ukubandlulula, ubumfihlo kanye nezindleko.
Ukulungiswa kwedatha kuqala ngokuqoqa, ukuhlanza nokuhlela umbhalo ongahluziwe ngezinga elikhulu. Lokhu kuhilela ukuphinda amadokhumenti, ukususa okuqukethwe okonakele noma okusekhwalithini ephansi, ukuhlunga ubuthi obukhulu noma izinto ezingekho emthethweni kanye nokusingatha izinkinga ze-copyright lapho kungenzeka khona. Umbhalo ube usubekwa uphawu ukuze unikezwe imodeli ngendlela yezinombolo ehambisanayo.
Ukuqeqeshwa kwangaphambi kokuqeqeshwa kuvame ukusebenzisa ukufunda okuqondiswa nguwe, lapho imodeli ifunda embhalweni ongenamalebula ngokubikezela amathokheni anemaski noma alandelayo. Idla amakhulu ezigidigidi zamagama avela emithonjeni efana namawebhusayithi, izincwadi, izihloko, izindawo zokugcina amakhodi kanye namanye ama-corpora. Phakathi nalesi sigaba, imodeli ithola ukujwayela kwezibalo mayelana nesakhiwo solimi, izincazelo zamagama kanye namaphethini avamile ngaphandle kwanoma yimaphi amalebula abantu acacile.
Ngemva kokuqeqeshwa kwangaphambi kokuqeqeshwa, ama-LLM avame ukuhlungwa ngokufunda okuqondisiwe kanye nokufunda kokuqinisa. Ekulungiseni kahle okuqondisiwe, imodeli ibona izibonelo zokufaka ezihambisana nemiphumela esezingeni eliphezulu (isibonelo, imibhangqwana yemibuzo nezimpendulo noma imiboniso yokuziphatha okuhle) futhi ilungisa imingcele yayo ukuze ilingise. Ekufundeni kokuqinisa, imodeli inikezwa izimpawu zempendulo—imivuzo noma izinhlawulo—ngokusekelwe ekutheni izimpendulo zayo ziwusizo kangakanani, ziphephile noma ziqondaniswe kangakanani, kancane kancane ziyishukumisela ekuziphatheni okufiselekayo.
Amasu asekelwe ku-Prompt njengokufunda kwe-shot encane kanye nokufunda kwe-zero shot kwandisa ukuguquguquka kwemodeli ngaphandle kokuqeqesha kabusha amapharamitha ayo ayinhloko. Ekukhuthazeni kwe-shot encane, ufaka izibonelo ezimbalwa zokufaka-ukuphuma ku-prompt yakho (njengokubuyekezwa kwamakhasimende kanye namalebula athi “Positive/Negative”) ukuze imodeli iqonde iphethini futhi iyisebenzise ezimweni ezintsha. Ekukhuthazeni kwe-zero shot, umane uchaze umsebenzi ("Hlela umuzwa walesi sibuyekezo") bese uthembele ekuqeqeshweni kwangaphambi kwemodeli ukunquma ukuthi yini okufanele yenziwe, ngisho nangaphandle kwezibonelo ezicacile ku-prompt.
Ukuqagela yisigaba sokufakwa, lapho imodeli eqeqeshwe ithola khona okokufaka okubukhoma futhi ikhiqize okuphumayo ngesikhathi sangempela. Ukusebenzisa ukuqagela kwemodeli enkulu kudinga ukubalwa okubanzi: isicelo ngasinye sihilela izendlalelo eziningi ze-transformer kanye nemisebenzi yokunaka. Ihadiwe ekhethekile njenge-GPU ivame ukusetshenziswa ukuphatha imisebenzi yezibalo ezifanayo ngempumelelo.
Ukuze benze ukuqagela kube wusizo ngezinga, onjiniyela basebenzisa amasu okwenza ngcono kanye namaseva okuqagela azinikele. Amaseva aphatha ukwabiwa kwezinsiza, aqoqe izicelo eziningi ndawonye, futhi asebenzise izindlela ezifana nokulinganisa noma ukuzivumelanisa nezimo eziphansi (i-LoRA, i-QLoRA) ukucindezela amamodeli, ukunciphisa ukulandelwa kwememori kanye nokubambezeleka ngenkathi kulondolozwa ukunemba okwamukelekayo. Izinhlaka ezifana ne-vLLM zithuthukisa ukusetshenziswa kwememori kanye nokusetshenziswa kwayo ngamasu afana nokuhlanganiswa okuqhubekayo kanye nokuphathwa kwememori yokunaka okuthuthukisiwe.
Izingxenye ezibalulekile nezinhlobo zamamodeli ezilimi ezinkulu
Nakuba ukwakheka kwe-LLM kuhluka, amamodeli amaningi asekelwe ku-transformer abelana ngesethi efanayo yezingxenye eziyinhloko. Phansi kukhona izendlalelo zokushumeka eziguqula amathokheni abe ama-vector ezinombolo aminyene athatha ulwazi lwe-syntactic kanye ne-semantic. Ngaphezulu kwazo kunezendlalelo eziningi zokuzinaka kanye namanethiwekhi okudlulisela phambili aguqula lezi zishumeko zibe izethulo ezihambisana nomongo.
Isendlalelo sokushumeka sihlanganisa ithokheni noma igama elingaphansi ngalinye endaweni yesikhala sevektha esinobukhulu obuphezulu. Ngokuqeqeshwa, amagama asetshenziswe ezimweni ezifanayo asondelana kakhulu kulesi sikhala, ngakho-ke amagama anjengelithi “bark” kanye nelithi “inja” ahlangana kakhulu endabeni ehlobene nenja kunelithi “bark” kanye nelithi “tree”. Lezi zimelelwano zivumela imodeli ukuthi ibambe ubudlelwano obucashile phakathi kwamagama ngale kwezincazelo ezilula zesichazamazwi.
Indlela yokunaka ivumela imodeli ukuthi igxile ngokuguquguqukayo ezingxenyeni ezifanele kakhulu zokufaka kwethokheni ngayinye eyicubungulayo. Ngokunikeza izisindo eziphakeme kumathokheni anolwazi kanye nezisindo eziphansi kwezingabalulekile, ukunaka kungabamba ukuncika kwebanga elide (njengezinkomba zesabizwana noma izixhumanisi zezihloko kuzo zonke izigaba) izakhiwo ezindala ezazilwa nazo.
Ngaphezu kokunaka, izendlalelo zokuphakelayo zisebenzisa ukuguqulwa okungekho emgqeni ukuze kuthuthukiswe ulwazi. Lawa manethiwekhi axhumene ngokugcwele acubungula amavektha acebile ngokunaka futhi asiza imodeli ukuthi ifunde imisebenzi eyinkimbinkimbi ehlanganisa amaphethini okufaka nokusatshalaliswa kokukhipha ngaphezu kwesilulumagama.
Ngokombono osebenzayo, singahlukanisa izigaba eziningana zama-LLM kuye ngokuthi aqeqeshwa futhi asetshenziswa kanjani. Amamodeli olimi “ayisisekelo” noma ajwayelekile aqeqeshwa kuphela ekubikezelweni kwethokheni elilandelayo futhi ikakhulukazi ahlose ukwenza imodeli yombhalo ongahluziwe. Amamodeli alungiselelwe imiyalelo aqeqeshwa ngokwengeziwe ukulandela imiyalelo yolimi lwemvelo (isibonelo, “fingqa lesi sihloko” noma “uhumushele olimini lwesiSpanishi”), okwenza abe usizo kakhulu kubasebenzisi bokugcina. Amamodeli alungiselelwe ingxoxo agxile ezingxoxweni ezingemuva nangemuva, efunda ukugcina umongo futhi akhiqize izimpendulo ezihambisanayo neziphephile eziphendulayo ngezikhathi eziningi.
Izibonelo ezidumile zifaka phakathi i-GPT (kusukela ku-OpenAI), i-PaLM kanye ne-BERT (kusukela ku-Google), i-XLNet kanye nezinhlobo ezithile zesizinda ezifana ne-BloombergGPT noma i-EinsteinGPT. Amamodeli esitayela se-GPT ngokuvamile angama-transformer kuphela agxile ekukhiqizeni, i-BERT iyimodeli ye-encoder kuphela eyenzelwe ngokuyinhloko ukuqonda imisebenzi efana nokuhlukaniswa, kanti amanye ahlanganisa izingxenye ze-encoder kanye ne-decoder zemisebenzi ehilela kokubili ukuqonda kanye nokukhiqiza.
Lokho okwenziwa yi-LLM: izinhlelo zokusebenza kanye namacala okusetshenziswa
Ukuguquguquka kwama-LLM kuvela eqinisweni lokuthi imisebenzi eminingi yolimi ingahlelwa njengokubikezela noma ukuguqula umbhalo. Uma imodeli isifunde ukumelwa kwangaphakathi kolimi okunamandla, ingashintshwa—ngokulungisa kahle noma ukukhuthaza—ukuze ibhekane nohlu oluhlaba umxhwele lwezinhlelo zokusebenza zomhlaba wangempela kuzo zonke izimboni.
Ekutholeni ulwazi, ama-LLM asetshenziswa kakhulu ukuthuthukisa usesho lwewebhu kanye nezinhlelo zokusesha amabhizinisi. Izinjini zendabuko zithembele kakhulu ekuqhathaniseni amagama angukhiye kanye nokubeka ezingeni, kanti izinhlelo ezisebenzisa i-LLM zingachaza inhloso ngemuva kombuzo futhi zikhiqize izimpendulo eziningi zengxoxo, ngokuvamile zihlanganisa amadokhumenti atholiwe nezimpendulo ezikhiqizayo. Lona umqondo ngemuva kokukhiqiza okungeziwe kokubuyisa.
Ukuze kuqondwe ulimi lwemvelo, ama-LLM ayazigqaja ngemisebenzi yokuhlukanisa njengokuhlaziya imizwa noma ukulebula izihloko. Amabhizinisi angahlaziya ukubuyekezwa kwamakhasimende, okuthunyelwe ezinkundleni zokuxhumana noma amathikithi okusekela ukuthola imizwa emihle noma emibi, izinkinga ezivelayo noma izingqikithi ezivamile ngaphandle kokwakha imodeli yangokwezifiso kusukela ekuqaleni.
Ukukhiqiza umbhalo yikhono elibonakala kakhulu: amamodeli afana ne-ChatGPT angakhiqiza iphrozi ehambisanayo, ehambisana nomongo cishe kunoma yisiphi isihloko. Abasebenzisi bangabakhuthaza ukuthi babhale ikhophi yokumaketha, okuthunyelwe kwebhulogi, izincazelo zomkhiqizo, imibiko, izikripthi, izinkondlo noma ngisho nezingxoxo zokudlala indima ngamathoni noma izitayela ezithile. Ngokukhuthaza ngokucophelela kanye nokubuyekezwa komuntu, bangasheshisa kakhulu ukuhamba komsebenzi kokudala okuqukethwe.
Ama-LLM nawo angabakhi bekhodi abanamandla uma eqeqeshwa ezindaweni zokugcina amakhodi ezinkulu. Amathuluzi afana ne-GitHub Copilot noma abanye abasizi bekhodi afunda amaphethini kuzo zonke izilimi eziningi zokuhlela futhi angaphakamisa imisebenzi, alungise amaphutha noma ahumushe ikhodi kusukela kolunye ulimi aye kolunye. Nakuba engashintshi onjiniyela abanamakhono, angakhuphula umkhiqizo futhi anciphise i-boilerplate.
I-AI yengxoxo kanye nama-chatbot kungenye indawo enkulu yohlelo lokusebenza. Ama-LLM anganika amandla abasizi ababonakalayo abahumusha imibuzo yabasebenzisi ngolimi lwemvelo, balondoloze umongo ngokujikajika futhi bakhiqize izimpendulo ezizwakala zifana nezomuntu kunama-robot abhalwe phansi. Asetshenziswa ekusekelweni kwamakhasimende, kuma-helpdesk angaphakathi e-IT, kuma-triage ezempilo, kubasizi bamabhange nokuningi, ngokuvamile ngokuqapha komuntu ngezimo eziyingozi kakhulu.
Ngaphandle kobuchwepheshe kanye nenkonzo yamakhasimende, ama-LLM athola izindima kwezempilo, isayensi, umthetho, ukumaketha kanye nezezimali. Kwezokwelapha kanye ne-biology, amamodeli angasiza ekuhlaziyeni umbhalo ohlobene namaprotheni, ama-molecule, i-DNA kanye ne-RNA, asize ekubuyekezweni kwezincwadi, noma asekele ama-chatbot okuqala (ngodokotela abanolwazi). Ochwepheshe bezomthetho bawasebenzisa ukuhlunga amaqoqo amakhulu amadokhumenti, ukubhala izinkontileka noma ukukhiqiza izifinyezo, kuyilapho abathengisi bethembele kuwo ngemibono yomkhankaso, ukuhlukaniswa kwezilaleli kanye nemiyalezo evumelaniswe nethoni.
Kungani ama-LLM ezizwa ehlakaniphile kangaka (nokuthi ahluleka kuphi)
Ingxenye yokuthakazelisa ngama-LLM ukuthi angabonakala ehlakaniphile kangakanani engxoxweni noma ekuxazululeni izinkinga. Ngemva kokuqeqeshwa ngezigidigidi zemisho evela ezincwadini, ezihlokweni, kumawebhusayithi kanye nasekhodini, athuthukisa ikhono elimangalisayo lokulingisa izitayela eziningi zokubhala, aphendule imibuzo eyinkimbinkimbi futhi achaze ngisho namahlaya noma izifaniso. Kubasebenzisi abaningi, ukuxhumana ne-LLM kuzwakala njengokuxoxa nomuntu onolwazi.
Lokhu kuhlakanipha okubonakalayo kuwumphumela ohlangothini wokuqashelwa kwephethini okucebile kakhulu kunokuqonda kweqiniso noma ukuqonda. Imodeli ayazi ukuthi isitatimende sinembile yini ngokweqiniso; imane ikhiqiza ukulandelana kwamathokheni okungenzeka ngokwezibalo uma kunikezwa okufakiwe kanye nomlando wayo wokuqeqeshwa. Ayiqinisekisi imithombo yangaphandle ngesikhathi sangempela ngaphandle kokuthi ihlanganiswe ngokusobala namathuluzi anikeza lelo khono.
Esinye sezivimbelo ezingathi sína kakhulu ukubona izinto ezingekho: izimo lapho imodeli ikhiqiza ngokuqiniseka ulwazi olungamanga noma olungenangqondo. Ingase isungule izingcaphuno, iqambe izingcaphuno, ihlanganise imiqondo engahlobene noma iveze izitatimende eziqagelayo njengamaqiniso. Ngenxa yokuthi amagama avame ukuzwakala enegunya, abasebenzisi bangadukiswa kalula uma bengahloli izimangalo ezibalulekile.
Ukucwasa kungenye inselelo ebalulekile, ngoba ama-LLM afunda ngqo embhalweni owenziwe ngabantu ophethe imibono yamasiko, yezepolitiki kanye neyezenhlalo. Ngaphandle kokuhlelwa kwemininingwane ngokucophelela kanye namasu okuvumelanisa, imodeli ingasakaza noma ikhulise ukucwasa okulimazayo emiphumeleni yayo. Lokhu kungathinta ubulungisa ezicelweni ezifana nokuqasha, ukubolekisa, ukulinganisela noma ukwesekwa komthetho.
Ukukhathazeka ngokuphepha nobumfihlo kuvela endleleni idatha yokuqeqesha eqoqwa ngayo kanye nendlela amamodeli asetshenziswa ngayo. I-Cooperative yokuqeqesha ingaqukatha izinto ezinelungelo lobunikazi noma idatha yomuntu siqu ekhishwe ngaphandle kwemvume ecacile. Kukhona impikiswano eqhubekayo kanye necala mayelana nokuthi amamodeli akhiqizayo aphula yini impahla yobuhlakani ngokukhiqiza kabusha noma ukulingisa okuqukethwe eduze. Ngesikhathi sokuphetha, uma engahlelwanga kahle, amamodeli angase aveze ulwazi olubucayi olwaluyingxenye yedatha yawo yokuqeqesha noma olwabiwe ngabasebenzisi ezingxoxweni zangaphambilini.
Ukwandisa nokusabalalisa nakho kucindezela imikhawulo yezobuchwepheshe neyezomnotho. Ukuqeqesha nokukhonza amamodeli amakhulu kakhulu kudinga izinsizakusebenza zokubala ezinkulu, ihadiwe ekhethekile kanye nezinhlelo eziyinkimbinkimbi ezisatshalaliswayo. Ukuzigcina zivuselelwe, ukuqapha ukuziphatha kwazo nokuvimbela ukusetshenziswa kabi kudinga umzamo wobunjiniyela oqhubekayo kanye nokuphathwa.
Ama-LLM, ukufunda okujulile kanye nendima yama-GPU
Ngaphansi kwe-hood, ama-LLM ayizibonelo zokufunda okujulile: amanethiwekhi e-neural anezingqimba eziningi aphefumulelwe kancane indlela ama-neurons ahlelwe ngayo ebuchosheni bomuntu. Ama-neurons e-biological axhumana ngezibonakaliso ze-electrochemical; ama-neurons okwenziwa angama-node esofthiwe axhumana ngokubala kwezinombolo. Izingqimba zala ma-node zakha amanethiwekhi e-neural okwenziwa (ama-ANN), angalinganisa imisebenzi eyinkimbinkimbi kakhulu.
Ama-Transformers ayisakhiwo sokufunda okujulile esenzelwe ukuphatha ukulandelana okufana nombhalo. Izigidi noma izigidigidi zamapharamitha azo zihlanganisa ubudlelwano kanye nokuncika phakathi kwamathokheni futhi abuyekezwa ngesikhathi sokuqeqeshwa ngokusebenzisa i-backpropagation kanye ne-gradient desccent. Ukujula nobubanzi balezi nethiwekhi kuzenza zikwazi ukubamba amaphethini olimi kanye nomongo alula kakhulu.
Ngenxa yokuthi ukuqeqeshwa kwe-LLM kanye nokucabanga kuhilela inani elikhulu lokuphindaphindwa kwe-matrix, kuncike kakhulu kuma-Graphics Processing Units (ama-GPU) noma ama-accelerator afanayo. Ama-GPU alungiselelwe ukusebenza okufanayo kuma-array amakhulu, okwenza abe afanelekela ukusebenzisa i-algebra eqondile enhliziyweni yokufunda okujulile. Imisebenzi yokuqeqesha emikhulu ingadinga amaqoqo ezinkulungwane zama-GPU asebenza amasonto amaningi.
Ukuze kugcinwe izindleko zilawuleka, ochwepheshe basebenzisa kakhulu izindlela zokucindezela imodeli kanye nezindlela zokulungisa kahle amapharamitha. Amasu afana nokulinganisa anciphisa ukunemba kwezisindo zezinombolo ukuze kulondolozwe inkumbulo; izindlela ezifana ne-LoRA kanye ne-QLoRA zivumelanisa izingxenye ezincane zenethiwekhi ezisezingeni eliphansi kuphela ngenkathi zishiya ezinye ziqandisiwe. Lokhu kuvumela izinhlangano ukuthi zenze ngokwezifiso amamodeli ayisisekelo anamandla ezizindeni ezithile noma imisebenzi ngaphandle kokuwaqeqesha kabusha kusukela ekuqaleni.
Indlela ama-LLM asekela ngayo umsebenzi wolwazi kanye nobuntatheli
Kubabhali, abahleli kanye nezintatheli, ama-LLM aba abasizi ababalulekile kunokuba bathathe indawo yabo. Bangasiza ekuhleleni imibono, babhale izinhlaka, baphakamise izihloko ezihlukile, bafingqe imibiko emide noma bakhiqize ukuhumusha kokuqala. Ngokuzenzakalela imisebenzi ephindaphindwayo noma ephansi, bakhulula ochwepheshe abangabantu ukuba bagxile ekuphenyweni, ekwahluleleni, ekuqinisekiseni nasekulandiseni izindaba.
Kodwa-ke, ukusebenzisa ama-LLM ngokuzibophezela emikhakheni yokuxhumana kudinga ukuqonda okucacile kwemikhawulo yawo. Njengoba amamodeli engakwazi ukubona imininingwane ngendlela engaqondakali, ukuqhathanisa izingcaphuno noma ukuxuba imithombo, noma yikuphi okuqukethwe okukhiqizwe yi-AI okubalulekile ngokokuziphatha, ngokomthetho noma ngokwedumela kumele kuhlolwe ngokucophelela. Umthwalo wemfanelo wokugcina wokunemba nokungakhethi usesekuchwepheshe abangabantu.
Inani langempela livela ekubambisaneni okucatshangelwe kahle: abantu banikeza umongo, ukuziphatha kanye nokucabanga okubucayi, kuyilapho amamodeli enikeza isivinini, ububanzi kanye nokuguquguquka kwezilimi. Amagumbi ezindaba kanye namaqembu okuqukethwe amukela lobu budlelwano angathola ukusebenza kahle ngaphandle kokulahlekelwa ikhwalithi, uma nje ethuthukisa iziqondiso ezicacile zokudalula, ukuqinisekisa kanye nokunciphisa ukucwasa.
Ikusasa lamamodeli amakhulu ezilimi
Ukwamukelwa okukhulu kwamathuluzi afana ne-ChatGPT, i-Claude, i-Gemini nabanye kudale ingxoxo ejulile mayelana nokuthi ama-LLM azowubumba kanjani kabusha umsebenzi, imfundo kanye nomphakathi. Njengoba amamodeli eqhubeka nokuthuthuka, asondela ekusebenzeni kwezinga lomuntu emisebenzini eminingi yolimi, yize kusekhona izikhala ezibalulekile ekucabangeni, esisekelweni kanye nasekuqondeni okuvamile.
Intuthuko yesikhashana cishe izogxila ekuthuthukiseni ukunemba kwamaqiniso, ukunciphisa imibono engekho kanye nokwenza amamodeli alawuleke futhi abe sobala. Amaqembu ocwaningo ahlola ukuqeqeshwa okungcono kokuhlelwa kwedatha, izindlela zokuvumelanisa, izinhlelo zokubuyisa ezihlanganisiwe namathuluzi angachaza noma avimbele ukuziphatha kwemodeli. Ngesikhathi esifanayo, kuyaqhubeka imizamo yokunciphisa ukucwasa okulimazayo nokuqinisekisa ukuthi imiphumela iphephile futhi ifaka phakathi.
Ukuqeqeshwa kwezindlela eziningi kungenye indawo ebalulekile, lapho amamodeli efunda khona ngokuhlanganyela embhalweni, kumsindo nakuvidiyo esikhundleni sombhalo wodwa. Lokhu kungenza izinhlelo ezifana ne-LLM zikwazi ukucabanga ngezigcawu ezibonakalayo, ziqonde ingxoxo ekhulunywayo futhi zihlanganise ulimi nokuqonda kanye nesenzo. Amakhono anjalo angaba usizo ezizindeni ezifana ne-robotics, izimoto ezizimele, izithombe zezokwelapha noma imfundo exhumanayo.
Ngasohlangothini lwezomnotho, ama-LLM kulindeleke ukuthi aguqule izindawo eziningi zokusebenza ngokushintsha imisebenzi ejwayelekile nokwandisa abasebenzi abanolwazi. Izindlela zokusebenza zokuphatha, ukwesekwa kwamakhasimende, ukubhalwa kwezomthetho okuyisisekelo, ukukopisha okulula kokumaketha kanye nokubhala ikhodi njalo konke kungenziwa ngokuzenzakalelayo ngokwengxenye. Esikhundleni sokuqeda imisebenzi ngokushesha, ama-LLM angase ahlele kabusha imisebenzi, andise ikhwalithi yokudala, ukucabanga okubucayi kanye nobuchwepheshe besizinda.
Izingxoxo zokuziphatha nezokulawula zizoqhubeka zikhula njengoba lezi zinhlelo ziba namandla futhi zingena empilweni yansuku zonke. Imibuzo mayelana nemvume yedatha, ilungelo lobunikazi, ukuzibophezela kokuqukethwe okukhiqizwe yi-AI, kanye nomthelela womphakathi wokwenziwa ngokuzenzakalela okukhulu kuzobumba indlela ama-LLM athuthukiswa futhi asetshenziswa ngayo. Izinhlangano ezihlanganisa ukusungula izinto ezintsha kwezobuchwepheshe nokuphatha okuqinile kanye nemfundo yabasebenzisi zizoba sesimweni esingcono sokuvula izinzuzo ngenkathi zinciphisa izingozi.
Ekugcineni, amamodeli amakhulu olimi aqondwa kangcono njengabafundi abanekhono elingavamile lokufunda, ukubhala nokuxoxa ngezinga elikhulu, kodwa kusadinga ukuphathwa ngabantu, umongo kanye nezindinganiso ukuze kusetshenziswe ngokuhlakanipha. Ukwazi ukuthi zakhiwe kanjani, ukuthi zingenzani kahle, nokuthi zihluleka kuphi kukunika amandla okuziguqula zibe amathuluzi asebenzayo athuthukisa umsebenzi wakho, ukufunda kanye nobuciko esikhundleni sokushintsha ukwahlulela kwakho.
Unjiniyela. I-Tech, isofthiwe nesithandi sehadiwe kanye ne-tech blogger kusukela ngo-2012
