Musanganiswa-we-Agents Aggregation
Musanganiswa-we-maAgents (MoA) inzira iyo mhando dzemitauro yakati wandei dzinonyora mhinduro uyezve aggregator modhi inosanganisa mazano avo epamusoro kuita mhinduro imwe yakavandudzwa.
Pfupiso
It lets a team of open models rival or beat a single top-tier model.
Kudzika Kwakadzika
Yakaunzwa mubepa ra2024 kubva Together AI, Musanganiswa-we-Agents unoronga akawanda maLLM muzvikamu. Muchikamu chekutanga, akawanda 'proposer' modhi imwe neimwe yakazvimirira inopindura kukurumidza. Zvavakaburitsa zvinobva zvabatanidzwa uye zvinopihwa kune inotevera dhizaini, uko modhi zvakare inopindura, ikozvino yakarongedzwa pane ese apfuura madhizaini. Mushure menguva imwe chete kana akawanda akadai, modhi ye 'aggregator' inogadzirisa zvese kuita mhinduro imwechete. Muono mukuru, unonzi nevanyori 'kubatana kweLLMs', ndeyekuti mhando dzinoburitsa mhinduro dziri nani kana dzichiratidzwa mhinduro dzevezera, kunyangwe dzisina kukwana. Pabhenji reAlpacaEval 2.0, iyo MoA yakavakwa zvachose kubva kune yakavhurika-sosi modhi inonzi yakapfuura GPT-4 Omni chibodzwa, zvichiratidza kuti nekungwarira kuunganidzwa kweakasiyana, akachipa mamodheru anogona kurova imwe muganhu system.
Technical Insight
MoA inosiyana nekuvhota kwakapfava kwevazhinji: pane kutora mhinduro imwe, muunganidzi anoverenga mhinduro dzese dzevamiriri sezviri mukati uye inogadzira synthesis nyowani, kusanganisa masimba uye zvikanganiso zvekusefa. Kusiyana pakati pevanokurudzira kunobatsira, saka kusanganisa mhuri dzemhando dzakasiyana kwakakosha. Mamiriro acho akaturikidzana, senge network yakadzika apo imwe neimwe 'neurons' izere LLM inofona. Kutengeserana-kubvisa ndeye latency uye mutengo: imwe neimwe layer inowanza nhamba yemafoni ekufungidzira, saka MoA inoshandisa yakawanda compute kusimudza mhando.
Strategic Impact
Kumhanya uye chiyero
Mutauro workflows inogona kufamba nekukurumidza pasina kupira kuenderana.
Svika uye svika
Inopamhidzira kupinda mumitauro yese nemataera ekutaurirana.
Sarudzo dzakajeka
Zvikwata zvinogona kupedza nguva yakawanda pakutonga uku otomatiki ichibata kudzokorora.
Ramangwana reMusanganiswa-we-Agents Aggregation
Tarisira kuti MoA-style aggregation ipararire sezvo fungidziro inova yakachipa uye orchestration masimusi anokura. Mafambiro ekutsvagisa anosanganisira kudzidza izvo vanokurudzira kuvimba nemubvunzo wega wega (nzira), kudzikisa chirango chekunonoka nekumhanyisa vatsigiri pamwe nekuchekerera vasina kusimba nekukurumidza, uye kubatanidza MoA nemashandisi ekushandisa-turusi kuitira kuti muunganidzi asanganise zvinyorwa chete asi zviito uye kutora humbowo. Sezvo mamodheru akavhurika achiwanda, kuabatanidza zvine hungwaru inova nzira iri kuwedzera inoshanda kune yemuganhu-level mhando pasina imwe hofori modhi.
Real-World Implementation
Kubatanidza matatu akasiyana eakavhurika machat modhi sevamiriri, wozoshandisa yakasimba aggregator kuburitsa imwe yakakwenenzverwa-tsigiro yemutengi.
Kuwedzera kuraira-kutevera zvibodzwa paAlpacaEval-maitiro mabhenji uchishandisa chete akavhurika-sosi mhando.
Kusanganisa akasiyana kodhi mazano kubva kune akati wandei mamodheru kuita imwechete, yakasimba kwazvo kuita basa.
Kumhanyisa pombi yehuremu yakavhurika iyo inosvika kumuganhu wemhando yekuvanzika-inonzwa kutumirwa uko data risingakwanise kusiya maseva ekambani.
Njodzi & Guardrails
Chokwadi chehuroyi chinogona kupinda chinyararire mishumo, kuyerera kwetsigiro, kana tsvakiridzo.
Kunzwa nekukasira kunogona kugadzira mhedzisiro isingaenderane pane zvikumbiro zvakafanana.
Sensitive text data inogona kuburitswa kana zvidhiraivho zvisina kusimba.
Implementation Roadmap
Tsanangura chimiro chekubuda, toni, uye mhando zviyero usati waburitsa.
Mhinduro dzepasi neakavimbika masosi pese pazvine basa.
Chengetedza ongororo yekuongorora yemunhu kune yakakwira-stake zvinobuda.
Tevera maitiro ekutadza uye dzidzisazve kukurudzira kana mafambiro ebasa nguva nenguva.
Ramba Uchiongorora
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Gaidhi rinotevera
Musanganiswa Wezvakadzama
Mibvunzo inowanzo bvunzwa
What is Mixture-of-Agents Aggregation?
Musanganiswa-we-maAgents (MoA) inzira iyo mhando dzemitauro yakati wandei dzinonyora mhinduro uyezve aggregator modhi inosanganisa mazano avo epamusoro kuita mhinduro imwe yakavandudzwa. Inobvumira timu yemhando dzakavhurika kukwikwidza kana kurova imwe yepamusoro-tier modhi.
MuMisanganiswa-ye-maAgents, ndeipi basa reiyo aggregator modhi?
Iyo aggregator inoverenga mhinduro dzese dzevamiriri uye inogadzira imwe yakasanganiswa, yemhando yepamusoro mhinduro.
Ndeipi yakakosha pfuma yeLLM inotsamira bepa reMoA?
Vanyori vanocherekedza kuti mamodheru anovandudza mhinduro dzawo kana akaiswa pane mamwe mamodheru 'dhizaini, kunyangwe asina kukwana.
Ko MoA inosiyana sei nekuvhota kwakapfava kwevazhinji?
Kusiyana nekuvhota, MoA haingosarudze mhinduro imwechete iripo; inoburitsa mhinduro nyowani inosanganisa vakwikwidzi.
Sei kusiyana pakati pevaporofiti kwakakosha muMoA?
Vagadziri vakasiyana-siyana vanovhara zvakanyanya, vachipa iyo aggregator seti yakapfuma yemazano ekusefa uye kukanganisa kusefa.
Ndeupi mutengo mukuru unoshanda weMoA maitiro?
Imwe neimwe nhanho inowedzera mamwe mafoni eLLM, saka MoA inotengesa yakawedzera komputa uye nguva yekuvandudzwa mhinduro mhando.