Overview
Covariant ikambani yemarobhoti-AI yakavaka hombe 'nheyo modhi' yemarobhoti, ichisiya maoko emarobhoti kuona, kufunga nezvazvo, uye kutora zvinhu zvavasati vambosangana nazvo. Izvo zvine basa nekuti yakaunza mutauro-modhi resipi yeyakakura pretraining pakubata kwemuviri mumatura.
Covariant Robotic Foundation Models inonzwisiswa zvakanyanya mumamiriro ehurongwa, kuwana modhi, sarudzo dzepuratifomu, uye ecosystem kudyidzana.
Deep Dive
Yakatangwa muna 2017 nevatsvakurudzi veAI vanosanganisira Pieter Abbeel, Peter Chen, naRocky Duan vanobva kuUC Berkeley uye OpenAI midzi, Covariant yakavaka Covariant Brain, AI software inopa simba robhoti rokunhonga uye kuronga. Chigadzirwa chayo chakanakisa, RFM-1 (Robotics Foundation Model 1), chakaunzwa muna 2024, chakadzidziswa pahuwandu hukuru hwekunhonga data repasirese pamwe nemavara nemifananidzo kuitira kuti marobhoti akwanise kubata mabhini akashata ezvinhu zvaasingazivi uye kunyange kupindura kune mirairo yemutauro wechisikigo. Pane kuronga chinhu chimwe nechimwe, sisitimu yacho inowanza kubva muruzivo senge modhi yemutauro muhombe inokonzeresa pane zvinyorwa. Muna 2024 chikamu chikuru chechikwata cheCovariant, kusanganisira vavambi vayo, chakahaiwa neAmazon muchibvumirano cherezinesi-uye-tarenda, zvichiratidza kuti maitiro erobhoti hwaro hwaro hwaive hwaita sei.
Technical Insight
RFM-1 is a multimodal transformer yakadzidziswa pane zvinyorwa, mifananidzo, vhidhiyo, robhoti sensor kuverenga, uye mota zviito, uchivabata sezviratidzo mune imwe nhevedzano. Nekufanotaura chiratidzo chinotevera pane idzi modalities, inodzidza chikonzero chemuviri-uye-mhedzisiro, saka inogona kukurudzirwa nemutauro uye chikonzero chekuti kubata kuchaita sei usati waita. Izvi zvinoita kuti modhi imwe chete idzore marobhoti akasiyana uye kubata zvinhu zvitsva pasina per-imeinjiniya, kuratidzira kuti kudzidzira kwakadzama kwakadii kwakagadzira kugona mutauro wakajairwa.
Mastering Covarian Robotic Foundation Models
Covariant ikambani yemarobhoti-AI yakavaka hombe 'nheyo modhi' yemarobhoti, ichisiya maoko emarobhoti kuona, kufunga nezvazvo, uye kutora zvinhu zvavasati vambosangana nazvo. Izvo zvine basa nekuti yakaunza mutauro-modhi resipi yeyakakura pretraining pakubata kwemuviri mumatura. Covariant Robotic Foundation Models inonzwisiswa zvakanyanya mumamiriro ehurongwa, kuwana modhi, sarudzo dzepuratifomu, uye ecosystem kudyidzana. Kuti uvake kunzwisisa kwakadzama, bata Covariant Robotic Foundation Models semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura zvinodikanwa, kujekesa fungidziro, uye patsanura izvo zvinogona kuitwa nehurongwa hwakavimbika kubva kune izvo zvichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa Covariant Robotic Foundation Models inoongorora 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
Kutora zvinhu zvakasiyana-siyana, zvisati zvamboonekwa kubva kumabhini ekuchengetedza e-commerce
Kuronga mapasuru nekwaunoenda pamitsetse yekupinza zvinhu pasina per-chimwe chinhu programming
Uchishandisa rurimi rwechisikigo kuudza ruoko rwemarobhoti zvokubata kana mabatirwo echinhu
Kupa simba rechitatu-bato rekuchengetera marobhoti kuburikidza neCovariant Brain software chikuva
Maitiro Ekuita
Covariant Robotic Foundation Models mukuita
Kunhonga zvinhu zvakasiyana-siyana, zvisati zvamboonekwa kubva kune akazara mabhini ekuchengetera e-commerce maodha.
Kutora zvinhu zvakasiyana-siyana, zvisati zvamboonekwa kubva kumabhini akazara e-e-commerce maodha Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura mhando yekumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa nemitengo yekukanganisa nekufamba kwenguva.
Covariant Robotic Foundation Models mukuita
Kuronga mapasuru nekwaunoenda pamitsetse yekupinza zvinhu pasina per-chimwe chinhu programming.
Kuronga mapasuru nekwaunoenda pamitsetse yekupinza zvinhu pasina per-chimwe chinhu hurongwa 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.
Covariant Robotic Foundation Models mukuita
Uchishandisa rurimi rwechisikigo kuudza ruoko rwemarobhoti zvokubata kana mabatirwo echinhu.
Uchishandisa mitauro-yechisikigo kukurudzira kuudza ruoko rwerobhoti zvekubata kana mabatiro echinhu Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura mhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Covariant Robotic Foundation Models mukuita
Kupa simba rechitatu-bato rekuchengetera marobhoti kuburikidza neCovariant Brain software chikuva.
Kupa simba rechitatu-bato rekuchengetera marobhoti kuburikidza neCovariant Brain software papuratifomu Matimu anowanzo kuwana mhedzisiro iri nani paanotsanangura emhando 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.