Mukupisa kwekutanga ChatGPT kupenga, ndakawana mameseji kubva kune aimbova wandaishanda naye. Aida kumhanya zano neni. Nguva yese munhu arikunakirwa nebrainstorming, we hopped on a call and he started off with “Remember how you used to always ask me to pull data for you? Ko dai wangozviita wega?" Uye ipapo anoenderera mberi nekundipa zano rekuti zviuru (makumi ezviuru?) Zvevamwe vanhu vaifunga panguva imwe chete: maLLM anogona kushandiswa kunyorwa-ku-SQL kubatsira vashoma tekinoroji vanhu kupindura mibvunzo yavo yedata.
Ndakabatikana nepfungwa iyi, asi ndisati ndanyura mumusoro kutanga, ndakaudza Lei (zvino CTO yangu) kuti taifanira kuita kumwe kusimbiswa. Takataura neshamwari uye vataimboshanda navo kubva mumaindasitiri akasiyana-siyana. Paiva nechido chakasimba mu "self-service analytics" chaiyo. Taiziva kuti zvaizonyanya kuomarara kupfuura zvazvairatidzika, asi mukana wacho wakanzwa wakanyanya kunaka kuti urege. Saka ini naLei takabva paShire tikatanga rwendo rwedu rwekugadzira chiono chedu:
Iyi positi haisi yechigadzirwa chedu pachayo (zvisinei, kana iwe uchida kuziva, unogona kuverenga zvakawanda nezve mamwe mazano ari pazasi akazivisa basa redu rekupedzisira chigadzirwa.
Ongorora: Rwendo urwu rwuri kushomeka zvinosiririsa muvaroyi uye epic Middle-earth hondo. 🧙
Hatizorambi tichiti “nei” nguva refu. Kana uri kuverenga izvi, ungangowira mune rimwe remapoka maviri:
Kusava nehanya nebasa revanoongorora data uye masayendisiti, pfungwa yeAI inoziva zvese inogona kupindura chero mibvunzo nezve data yesangano inonzwika zvakanaka. Kana zvirinani, zvinonzwika zvakanaka kusangano uye vatungamiriri varo vebhizinesi vane hunyanzvi hwekuita nzira nyowani dzekubvunza mibvunzo hapana chinosungirwa. Iyi AI inogona kunge iri mhinduro yekugadzira "data-inotyairwa" sangano apo mutungamiri wese anotsamira pane humbowo hwesimba kuita sarudzo dzavo. Uye zvese pachidimbu chemutengo wazvaizowanzotora. Pakupedzisira! Masangano anogona kuita mari pa "mafuta matsva" avanga vachinzwa nezvawo kubva 2010.
Asi kana iri riri dambudziko rakakosha kugadzirisa uye AI yave yakanaka kudaro, nei pasina chigadzirwa chakanyatso kuigadzirisa kusvika pari zvino?
Ongororo dzichangoburwa dzeindasitiri dzinopenda mufananidzo wakaoma wekutorwa kweAI mubhizinesi.
MaAdopters eAI-kunyanya mubhizinesi-ane bhawa yakakwira kana zvasvika kune zvinotarisirwa tekinoroji. Muchirevo che data analytics uye yekuzvishandira kurota, isu tinotarisira yedu AI tooling ku:
Zvinosuruvarisa, mhinduro zhinji dzazvino dzinoshandisa chinyakare monolithic AI framework, iyo inowanzotadza kuzadzisa zvinotarisirwa. Mumakore mashoma apfuura, boka reFabi.ai neni takashanda nesimba panyaya iyi. Isu takavaka prototypes yebhizinesi uye takaongorora akawanda sarudzo. Mukupedzisira, takaona kuti kana Retrieval Augment Generation (RAG) kana kunyatso-tuning yaigona kugadzirisa dambudziko iri neino monolithic framework.
Patakaedza nzira iyi, zvinhu zvishoma zvakava pachena kwatiri:
Mushure mekutarisa nyaya idzi, takafunga nezve maitiro ekuita AI kugadzirisa zvirinani kumatambudziko. Ndipo pakapinda maAI vamiririri uye vakasimbisa iyi pfungwa kwatiri.
Iyo miniti yatakaisa maziso kune agentic frameworks, takaziva kuti yaizochinja mutambo. Takaerekana tanzwa kuti taigona kurega AI ichifunga mapinduriro emibvunzo. Inogona kushanda nematanho uye kugadzirisa yega. Kana iyo AI ikanyora SQL query inopotsa nhando mu "Account type" ndima, inogona kuomesa-mubvunzo, kuona kukanganisa, uye kugadzirisa iyo pachayo. Asi ko kana tikakwanisa kutora danho iri mberi torega iyo AI ichishanda zvakanyanya muPython uye kuwedzera maLLM? Zvino, iyo AI inoita zvinopfuura kudhonza data. Inogona kushandisa Python mapakeji kana maLLM kuti uwane kunze, mafambiro, kana yakasarudzika njere, iyo yaunowanzo tsvaga pamaoko.
Asi isu takanga tichine dambudziko rimwe chete: iyo yakashata bhizinesi data. Isu taitenda kuti masangano anogona kugadzirisa izvi nekushandisa yakasimba data engineering maitiro, senge a
Sezvo makambani anokura, anobata data rakawanda uye ane vashandisi vakawanda. Iyo agent mesh pfungwa inobatsira kuenzanisa nekukurumidza kuita sarudzo nekutonga kunodiwa mukutonga. Specialized agents vanobatsira kuseta miganhu yakajeka uye mabasa kune yega yega AI. Ivo zvakare vanogadzira scalable nzira yekuti vamiririri vataure. Uyezve, ivo vanogona kubatsira kubata zviwanikwa zvakanaka muzvikwata nemakambani.
Pfungwa iri kuseri kweanyanzvi nderekuti mumiriri uyu anogona uye anongopindura mibvunzo pane dataset rakanyatsotsanangurwa. Semuenzaniso, unogona kugadzira uye kuvhura mumiriri weAI anopindura mibvunzo nezve mishandirapamwe yekushambadzira. Kana iwe unogona kuvaka imwe yekupindura mibvunzo nezve pombi yekushambadzira, zvichingodaro uye zvichingodaro.
Pane chikanganiso chimwe chete: Vashandisi vanofanirwa kuziva kuti ndeupi mumiririri wekuenda kumubvunzo upi. Zvakafanana nekuda kuziva muongorori wekutengesa kuti abvunze mubvunzo we vs. kungobvunza mubvunzo wakajairika. Nemubvunzo wakajairika, mumwe munhu ari muchikwata anogona kuitungamira kune munhu akakodzera. Apa ndipo panopinda pfungwa ye "agent mesh".
Kana mumiririri mumwe chete achigona kupindura akavimbika mibvunzo yakanangana nedomasi, saka wadii kurega vamiririri vachitaurirana? Sei usingakwanise, semuenzaniso, mumiriri wekushambadzira anongobvunza mumiriri wepombi zvakananga kana vachigona kupindura mubvunzo zviri nyore? Tinotenda kuti inofanira kukwanisa. Sezvineiwo, isu tinofunga kuti mune ramangwana kuchava nema network evamiririri vane hierarchical structure. Unogona kufungidzira "GTM agent" inodana "Marketing agent." Mumiririri uyu anobva adaidza vese "Pipeline agent" uye "Marketing campaign agent."
Pfungwa iyi yakafanana nepfungwa yakajairika inotenderera ichitenderedza AI inozivikanwa se "
Iyi mesh nzira inopa mashoma akakosha mabhenefiti pamusoro pe monolithic AI (pane pristine semantic layer):
Pakupera kwezuva, iyi pfungwa ye mesh haisi novel. Izvi zvinoratidzira pfungwa yemusanganiswa wenyanzvi uyo wakaratidzwa kuvandudza humbowo hweLLMs. Iko kungotora iyo pfungwa imwe chete uye kuiunza kune AI vamiririri.
PaFabi.ai, tine rwendo rurefu rwekufamba sezvatinovaka Analyst Agent mesh. Asi, isu takatokunda mamwe ematambudziko makuru ehunyanzvi hwekuvaka munzira.
AI data analyst agents vanoda yakasarudzika dhizaini. Iyi dhizaini inofanirwa kuvabvumira kushandisa Python kana LLMs kupindura mibvunzo, kugara mukuwirirana nedata masosi, uye kukwana mumapuratifomu anodyidzana, vachiri kugara vakachengeteka uye scalable. Mumwe nemumwe mumiririri anofanirwa kushanda muPython kernel yake, iyo inoda kukurumidza kukwizwa kumusoro kana pasi kuti ideredze mitengo uye irambe yakabatana neyekunobva data.
Mavakirwo asingapi kernels ega kune mumiririri wega wega anogona kupinda mune imwe yeinotevera njodzi:
Dambudziko rekuvaka rudzi urwu rwepuratifomu idambudziko reAI sezvo iri DevOps dambudziko.
Sezvo makambani emabhizinesi achitarisira mamwe maAI maapplication mukushanda kwavo, vanoda nzira dzakanyanya uye dzakanyatsotongwa. Iyo mumiriri mesh chimiro inoshandisa nyanzvi yeAI data vamiririri senzira yekuyera AI mune data analytics. Iyi nzira inochengetedza chengetedzo, kuvimbika, uye kuita kwakasimba.
Tinogona kunge takatarisira kuti AI ichave kwese kwese ikozvino, ichipindura mibvunzo yakawanda yedata. Asi, kana tikanyatsotarisisa, kufambira mberi mumakore maviri chete kubva pakatangwa ChatGPT kunoshamisa. Tichine zvakawanda zvekudzidza murwendo urwu. Mupfungwa dzangu, zvisinei, vamiririri uye agent mesh masisitimu anozove akakosha kune bhizinesi AI.