I-Speculative Speculative Decoding (SSD)

I-Bottleneck ye-Generative AI

Iimodeli ze-Generative AI ziye zathimba ihlabathi ngokukwazi kwabo ukubhala, ikhowudi, kunye nokudala. Nangona kunjalo, nabani na onxibelelane nemodeli enkulu yolwimi (LLM) uye wafumana i-telltale lag-ikhefu phakathi kokuthumela i-prompt kunye nokufumana amagama ambalwa okuqala empendulo. Le latency sesona sithintelo sikhulu sokwenza ulwelo, indalo, kunye namava e-AI asebenzisanayo. Undoqo wengxaki ulele kuyilo lweemodeli ngokwazo. Ii-LLMs zivelisa umqondiso wokubhaliweyo nge-token, igama ngalinye elitsha ngokuxhomekeke kulandelelwano luphela oluze phambi kwalo. Olu hlobo lolandelelwano, ngelixa lunamandla, lubanzi kwaye lucotha ngokwendalo. Njengoko amashishini efuna ukudibanisa i-AI kwizicelo zexesha lokwenyani ezifana nee-chatbots zenkonzo yabathengi, uguqulelo oluphilayo, okanye uhlalutyo olusebenzayo, oku kubambezeleka kuba yingxaki ebalulekileyo yeshishini, hayi nje umdla wobugcisa.

Isinqumli esichubekileyo: Indlela i-Decoding eQikelelayo eSebenza ngayo

I-Speculative Decoding (SD) bubuchule obuyilelwe ukwaphula lo mqobo ulandelelanayo ngaphandle kokuguqula imodeli yoyilo olusisiseko okanye umgangatho wemveliso. Ingcamango engundoqo kukusebenzisa imodeli "eyilwayo" ukuvelisa ulandelelwano olufutshane lwamathokheni ngokukhawuleza kunye nemodeli "ekujoliswe kuyo" (i-LLM enamandla ngakumbi, ecothayo) ukuqinisekisa ukuchaneka koyilo kwinqanaba elinye, elihambelanayo.

Nalu ucazululo olulula lwenkqubo:

• Isigaba esiYilwayo: Imodeli encinci, ekhawulezayo (imodeli eyidrafti) ngokukhawuleza ivelisa iithokheni ezininzi zabaviwa-uyilo oluqikelelwayo lokuba impendulo ingaba yintoni na.
• Isigaba sokuQinisekisa: I-LLM ephambili, ekujoliswe kuyo ithatha yonke idrafti yolandelelwano kwaye iyiqhube ngexesha elinye. Endaweni yokuvelisa amathokheni amatsha, yenza ukudlula phambili ukubala ukuba nokwenzeka komqondiso ngamnye kwidrafti echanekileyo.
• Isigaba soKwamkeleka: Imodeli ekujoliswe kuyo yamkela esona simaphambili side sichanekileyo kuyilo. Ukuba uyilo lwalugqibelele, ufumana amathokheni amaninzi ngexabiso lokubala elinye. Ukuba idrafti ayilunganga ngokuyinxenye, imodeli ekujoliswe kuyo ihlaziya kwakhona ukusuka kwindawo yempazamo, isagcina ixesha.

Ngokoqobo, i-Speculative Decoding ivumela imodeli enkulu ukuba "icinge ngokukhawuleza" ngokusebenzisa imodeli encinci ukwenza uqikelelo lokuqala, olukhawulezayo. Le ndlela inokukhokelela kwisantya se-2x ukuya kwi-3x ngexesha lokutsho, ukuphuculwa okumangalisayo okwenza i-AI yomgangatho ophezulu iphendule kakhulu.

Ukuguqula izicelo zeShishini nge-AI eKhawulezayo

Iimpembelelo zokunciphisa i-AI latency zinzulu kwimisebenzi yezoshishino. Isantya siguqulela ngokuthe ngqo kwimpumelelo, ukonga iindleko, kunye namava aphuculweyo omsebenzisi.

Qwalasela i-arhente yenkxaso yomthengi esebenzisa i-AI co-pilot. Nge-latency ye-LLM esemgangathweni, i-arhente kufuneka ime emva kombuzo ngamnye, idala incoko emileyo. Nge-Decoding eKhethekileyo, iingcebiso ze-AI zivela ngokukhawuleza, zivumela i-arhente ukuba igcine ukuhamba kwendalo kunye nomthengi kwaye isombulule imiba ngokukhawuleza. Kwiinkonzo zoguqulo oluphilayo, ukulibaziseka okuncitshisiweyo kuthetha ukuba iincoko zinokwenzeka kufutshane nexesha lokwenyani, zophule imiqobo yolwimi ngokusebenzayo ngakumbi kunangaphambili.

I-Decoding eqikelelwayo ayikona nje ukwenza i-AI ngokukhawuleza; imalunga nokwenza idityaniswe ngokungenamthungo kwindlela yokusebenza komntu, apho isantya siyimfuneko yokwamkelwa.

Kubaphuhlisi abakha izicelo ze-AI-powered, oku kukhawuleza kuthetha iindleko eziphantsi zokubala ngombuzo ngamnye, okubenza bakwazi ukukhonza abasebenzisi abaninzi ngesiseko esifanayo okanye banikeze iimpawu ze-AI ezinzima ngaphandle kokunyuka okuhambelanayo kwi-latency. Kulapho iqonga elifana neMewayzlibaluleka. Mewayzibonelela nge-OS ye-modular yeshishini evumela iinkampani ukuba zidibanise ezi zixhobo ze-AI zokusika kwiindlela zabo zokusebenza ezikhoyo ngaphandle komzamo. Ngokukhupha ubunzima obusisiseko, i-Mewayzivumela amashishini ukuba asebenzise i-inference ekhawulezayo kuyo yonke into ukusuka kwisizukulwana sengxelo ezenzekelayo ukuya kuhlalutyo lwexesha lokwenyani, ukuqinisekisa ukuba i-AI liqabane eliphendulayo, kungekhona i-bottleneck evilaphayo.

Ikamva likhawulezayo: Ukwamkelela iInference ekhawulezileyo

I-Decoding eqikelelweyo imele utshintsho olubalulekileyo kwindlela esijongana ngayo ne-AI. Ibonisa ukuba ubungakanani bemodeli ekrwada ayikuphela kwendlela eya kwisakhono; impumelelo kunye nobunjineli obukrelekrele zibalulekile ngokulinganayo. Njengoko uphando luqhubeka, sinokulindela ukubona ulwahlulo olukwinqanaba eliphezulu kakhulu lobu buchule, mhlawumbi sisebenzisa iindlela zoyilo eziphucukileyo okanye sizisebenzisa kwiimodeli ezininzi.

Ugqatso lwe-AI enamandla ngakumbi ngoku ludityaniswe ngokungenakuhluzwa nomdyarho okhawulezayo we-AI. Ubuchwephesha obufana ne-Speculative Decoding iqinisekisa ukuba sinokusebenzisa amandla apheleleyo eemodeli ezinkulu kwiindawo ezisebenzayo, ezithatha ixesha. Kumashishini acinga phambili, ukwamkela obu bugcisa akusakhethi; yimfuneko yokhuphiswano ukwenza iinkqubo ezikhawulezayo, ezikrelekrele, nezisebenzisana ngokwenene. Amaqonga abeka phambili kwaye enze lula ukufikelela kwezi zinto zintsha, njengeMewayz, ziya kuba phambili ekuxhobiseni isizukulwana esilandelayo sezicelo zeshishini eziqhutywa yi-AI.

Imibuzo Ebuzwa Rhoqo

I-Bottleneck ye-Generative AI

Iimodeli ze-Generative AI ziye zathimba ihlabathi ngokukwazi kwabo ukubhala, ikhowudi, kunye nokudala. Nangona kunjalo, nabani na onxibelelane nemodeli enkulu yolwimi (LLM) uye wafumana i-telltale lag-ikhefu phakathi kokuthumela i-prompt kunye nokufumana amagama ambalwa okuqala empendulo. Le latency sesona sithintelo sikhulu sokwenza ulwelo, indalo, kunye namava e-AI asebenzisanayo. Undoqo wengxaki ulele kuyilo lweemodeli ngokwazo. Ii-LLMs zivelisa umqondiso wokubhaliweyo nge-token, igama ngalinye elitsha ngokuxhomekeke kulandelelwano luphela oluze phambi kwalo. Olu hlobo lolandelelwano, ngelixa lunamandla, lubanzi kwaye lucotha ngokwendalo. Njengoko amashishini efuna ukudibanisa i-AI kwizicelo zexesha lokwenyani ezifana nee-chatbots zenkonzo yabathengi, uguqulelo oluphilayo, okanye uhlalutyo olusebenzayo, oku kubambezeleka kuba yingxaki ebalulekileyo yeshishini, hayi nje umdla wobugcisa.

Isinqumli esichubekileyo: Indlela i-Decoding eQikelelayo eSebenza ngayo

I-Speculative Decoding (SD) bubuchule obuyilelwe ukwaphula lo mqobo ulandelelanayo ngaphandle kokuguqula imodeli yoyilo olusisiseko okanye umgangatho wemveliso. Ingcamango engundoqo kukusebenzisa imodeli "eyilwayo" ukuvelisa ulandelelwano olufutshane lwamathokheni ngokukhawuleza kunye nemodeli "ekujoliswe kuyo" (i-LLM enamandla ngakumbi, ecothayo) ukuqinisekisa ukuchaneka koyilo kwinqanaba elinye, elihambelanayo.

Ukuguqula izicelo zeShishini nge-AI eKhawulezayo

Iimpembelelo zokunciphisa i-AI latency zinzulu kwimisebenzi yezoshishino. Isantya siguqulela ngokuthe ngqo kwimpumelelo, ukonga iindleko, kunye namava aphuculweyo omsebenzisi.

Ikamva liyakhawuleza: Ukwamkelela iInference ekhawulezileyo

I-Decoding eqikelelweyo imele utshintsho olubalulekileyo kwindlela esijongana ngayo ne-AI. Ibonisa ukuba ubungakanani bemodeli ekrwada ayikuphela kwendlela eya kwisakhono; impumelelo kunye nobunjineli obukrelekrele zibalulekile ngokulinganayo. Njengoko uphando luqhubeka, sinokulindela ukubona ulwahlulo olukwinqanaba eliphezulu kakhulu lobu buchule, mhlawumbi sisebenzisa iindlela zoyilo eziphucukileyo okanye sizisebenzisa kwiimodeli ezininzi.