Overview
Snowflake Arctic ndiyo yakavhurika yakakura mutauro modhi yakavakwa nedata-gore kambani Snowflake, yakarongedzerwa mabasa ebhizinesi senge SQL chizvarwa uye coding. Yakanga yakagadzirirwa kuve yakachipa zvisingaite kudzidzisa uye nekugona kumhanya.
Snowflake Arctic Models inonzwisiswa zvakanyanya mumamiriro ehurongwa, kuwana modhi, sarudzo dzepuratifomu, uye ecosystem kudyidzana.
Deep Dive
Snowflake, inozivikanwa neyayo yegore data warehouse, yakaburitsa Arctic muna Kubvumbi 2024 seyakavhurika-sosi LLM (Apache 2.0 rezinesi) yakanangwa zvakaenzana kune bhizinesi zvinodiwa kwete chatbots. Arctic inoshandisa 'Dense-MoE Hybrid' dhizaini: ine 480 bhiriyoni yakazara paramita asi inongo shandisa mabhiriyoni gumi nenomwe pa tokeni, saka inomhanya zvakachipa zvakanyanya kupfuura saizi yayo. Snowflake yakashuma kuidzidzisa nemari isingasviki mamirioni maviri emadhora mukombuta - chikamu chiduku chemhando dzakafanana. Arctic yakanangana ne 'enterprise intelligence': kunyora mibvunzo yeSQL, kugadzira kodhi, uye kutevera mirairo, kwainoti kuenzanirana nemhando dzakasimba dzakasimba. Padivi payo, Snowflake yakaburitsa embedding modhi (Arctic Embed) yekutsvaga uye kudzoreredza, ichisimbisa zano rayo rekuisa AI yakananga padivi pe data revatengi.
Technical Insight
Kubudirira kweArctic kunobva kuMusanganiswa-we-Nyanzvi (MoE) dhizaini ine akawanda madiki 'nyanzvi' sub-network. Pachiratidzo chega chega, router inotora vashoma chete venyanzvi kuti vashande, saka modhi inoshandisa 17B ye480B yayo paramita panguva. Yakasanganiswa nedense base, iyi 'Dense-MoE Hybrid' inopa yakakwirira kugona kudzidza uchichengeta per-tokeni komputa - uye nekudaro mutengo wekufungidzira - wakaderera kumabhizinesi.
Kubata Snowflake Arctic Models
Snowflake Arctic ndiyo yakavhurika yakakura mutauro modhi yakavakwa nedata-gore kambani Snowflake, yakarongedzerwa mabasa ebhizinesi senge SQL chizvarwa uye coding. Yakanga yakagadzirirwa kuve yakachipa zvisingaite kudzidzisa uye nekugona kumhanya. Snowflake Arctic Models inonzwisiswa zvakanyanya mumamiriro ehurongwa, kuwana modhi, sarudzo dzepuratifomu, uye ecosystem kudyidzana. Kuvaka kunzwisisa kwakadzama, bata Snowflake Arctic Models semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura zvinodikanwa, jekesa fungidziro, uye patsanura izvo zvingaitwe nehurongwa hwakavimbika kubva kune zvichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa Snowflake Arctic Models zvinoongorora zano revatengesi, kuvimbika kwemepu yemugwagwa, uye njodzi yekuvhara isati yaita. Ivo vanonyora zvakajeka maitiro ebudiriro, bvunzo vachipokana ne data rechokwadi uye mafambiro ebasa, uye iterate zvichibva pane zvakacherechedzwa maitiro ekutadza kwete kuhwina-nguva imwe chete yebhenji. Apa ndipo apo kunzwisisa kwe theoretical kunoshanduka kuve kugona kwakasimba pane chigadzirwa, mutemo, uye mashandiro.
Mamepu emigwagwa emutengesi anopesvedzera izvo izvo timu yako inogona kugadzira inotevera. Panguva imwecheteyo, zviziviso zveLaunch zvinogona kupfuura kugadzikana mune chaiyo yekugadzira workflows. Nzira yakatsiga ndeyekubatanidza kukurumidza kuyedza nekutonga: mhanyisa vatyairi vendege, tora humbowo, buritsa matanda esarudzo, uye urambe uchivandudza chengetedzo semaitiro emuenzaniso, zvinotarisirwa nemushandisi, uye zvinodikanwa zvekutonga.
Strategic Impact
Mamepu emigwagwa emutengesi anopesvedzera izvo izvo timu yako inogona kugadzira inotevera.
Mamepu emigwagwa emutengesi anopesvedzera izvo izvo timu yako inogona kugadzira inotevera. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Mamiriro ezvekutengeserana uye sarudzo dzekuendesa dzinokanganisa mutengo wenguva refu uye njodzi.
Mamiriro ezvekutengeserana uye sarudzo dzekuendesa dzinokanganisa mutengo wenguva refu uye njodzi. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Kambani inokurudzira inogadzirisa kusarudzika kwechigadzirwa, mamiriro ekuchengetedza, uye kuvhurika.
Kambani inokurudzira inogadzirisa kusarudzika kwechigadzirwa, mamiriro ekuchengetedza, uye kuvhurika. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Real-World Implementation
Kugadzira chaiyo SQL mibvunzo kubva pachena-chiRungu mibvunzo pamusoro pekambani yekuchengetedza data
Kusimbisa bhizinesi kodhi-chizvarwa vabatsiri mukati meSnowflake's Cortex sevhisi
Kushandisa Arctic Embed modhi kuvandudza kutsvaga kwegwaro uye kudzoreredza-yakawedzera chizvarwa
Kumhanyisa yakavhurika, yeApache-ine rezinesi modhi pane-nzvimbo kana mune yakavanzika gore kuchengetedza data rakajeka richitongwa.
Maitiro Ekuita
Snowflake Arctic Models mukuita
Kugadzira chaiyo SQL mibvunzo kubva pachena-chiRungu mibvunzo pamusoro pekambani yekuchengetedza data.
Kugadzira chaiyo SQL mibvunzo kubva pachena-chiRungu mibvunzo pamusoro pekambani yekuchengetera data Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Snowflake Arctic Models mukuita
Kusimbisa bhizinesi kodhi-chizvarwa vabatsiri mukati meSnowflake's Cortex sevhisi.
Kusimbaradza bhizinesi kodhi-chizvarwa vabatsiri mukati meSnowflake's Cortex sevhisi Matimu anowanzo kuwana mhedzisiro iri nani kana ivo vachitsanangudza zvemhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Snowflake Arctic Models mukuita
Kushandisa Arctic Embed modhi kuvandudza kutsvaga kwegwaro uye kudzoreredza-yakawedzera chizvarwa.
Kushandisa Arctic Embed modhi kuvandudza kutsvaga kwegwaro uye kudzoreredza-yakawedzera chizvarwa Matimu anowanzo kuwana mhedzisiro irinani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Snowflake Arctic Models mukuita
Kumhanyisa yakavhurika, yeApache-ine rezinesi modhi pane-nzvimbo kana mune yakavanzika gore kuchengetedza data rakajeka richitongwa.
Kumhanyisa yakavhurika, yeApache-ine rezinesi modhi pane-nzvimbo kana mune yakavanzika gore kuchengetedza data inodzorwa Matimu anowanzo kuwana mibairo iri nani kana vachinge vatsanangura zvemhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Njodzi & Guardrails
Zviziviso zvekutanga zvinogona kupfuura kugadzikana mune chaiyo yekugadzira workflows.
Mitengo yeAPI kana shanduko yepolicy inogona kukanganisa fungidziro husiku.
Kutsamira kune mumwe-mutengesi kunowedzera kukiya-mukati uye mari yekufambisa.
Implementation Roadmap
Ongorora vanopa uchishandisa ako ega mabasa uye dataset.
Ongorora vanopa uchishandisa ako ega mabasa uye dataset. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Wongorora zvakavanzika, chengetedzo, uye mazwi emutemo usati wabatanidzwa.
Wongorora zvakavanzika, chengetedzo, uye mazwi emutemo usati wabatanidzwa. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Chengetedza chirongwa chekudzokera kumashure kune mamodheru kana vatengesi.
Chengetedza chirongwa chekudzokera kumashure kune mamodheru kana vatengesi. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Tarisa zvinyorwa zvekuburitsa kuitira kuti shanduko yemigwagwa isashamise zvikwata.
Tarisa zvinyorwa zvekuburitsa kuitira kuti shanduko yemigwagwa isashamise zvikwata. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.