Overview
Kuyerera kuenzanirana inzira nyowani yekudzidzisa mamodheru anogadzirwa anodzidza yakatsetseka 'velocity field' inotakura ruzha rusina kurongeka rwakananga kudata rechokwadi. Izvo zvine basa nekuti inogona kufananidza kana kurova diffusion modhi mhando uku ichigadzira mifananidzo mumatanho mashoma.
Flow Matching ndeyekombuta-kuona mafambiro anodudzira kana kugadzira midhiya yekuona yekuongorora, mashandiro, uye kugadzira.
Deep Dive
Kuyerera kuenzanirana kunodzidzisa modhi kutakura mukana mumwe chete wekugovera (ruzha rwuri nyore, seGaussian) kuenda mune imwe (mifananidzo chaiyo) munzira dzinoenderera. Panzvimbo yemheremhere, zvibodzwa-zvakavakirwa chinangwa chekuparadzira, modhi yacho inodzosera zvakananga nzvimbo yekumhanya: pane imwe neimwe nzvimbo uye nguva inofanotaura kuti ndeipi nzira uye nekukurumidza sei sampuli inofanira kufamba. Conditional kuyerera kuenzanirana kunoita kuti izvi zvifambe nekutsanangura nzira dzakareruka pa-sample nzira, kazhinji mitsara yakatwasuka, pakati pemuenzaniso weruzha uye data data, wozodzidzisa network kuti ienderane neaya mavheti. Panguva yechizvarwa iwe unotanga kubva kune ruzha uye batanidza iyo yakadzidza ndima neODE solver. Kuyerera kwakagadziridzwa, mutsauko wakakurumbira, unotwasanudza nemaune nzira idzi kuitira kuti chizvarwa chinoda mashoma matanho ekugadzirisa. Iyo inosimbisa mhando seStable Diffusion 3 uye Flux.
Technical Insight
Iyo yakakosha yehunyengeri ndeyekuyerekana kuyerera kwekuenzanisa kurasikirwa: pane komputa isingachinjike yekumisikidza kukurumidza pamusoro peiyo dataset, iwe unomira pane imwechete data point, kuvaka nzira iri nyore yekududzira (semuenzaniso, x_t = (1-t) * ruzha + t * data), uye dzosera network kune iyo nzira inozivikanwa velocity (data minus ruzha). Avhareji pamusoro pembiri dzakawanda, izvi zvinogoneka zvinodzoreredza iyo chaiyo marginal ndima. Sampling inozogadzirisa yakajairwa mutsauko equation, inova deterministic uye yakatsetseka.
Mastering Flow Matching
Kuyerera kuenzanirana inzira nyowani yekudzidzisa mamodheru anogadzirwa anodzidza yakatsetseka 'velocity field' inotakura ruzha rusina kurongeka rwakananga kudata rechokwadi. Izvo zvine basa nekuti inogona kufananidza kana kurova diffusion modhi mhando uku ichigadzira mifananidzo mumatanho mashoma. Flow Matching ndeyekombuta-kuona mafambiro anodudzira kana kugadzira midhiya yekuona yekuongorora, mashandiro, uye kugadzira. Kuti uvake kunzwisisa kwakadzama, bata Flow Matching semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura zvinodiwa, kujekesa fungidziro, uye patsanura izvo zvinogona kuitwa nehurongwa hwakavimbika kubva kune zvichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa Flow Matching chiyero kurongeka nehuchokwadi hwekushanda semhando yedata, kusiyana kwemwenje, uye kuenderana kwemazita. 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.
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero. Panguva imwecheteyo, kodzero dzeMufananidzo uye kubvumirwa kunogona kuve njodzi dzepamutemo kana hunhu husina kujeka. 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
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero.
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Zvikwata zvekugadzira zvinogona prototype pfungwa nekukurumidza nekudzokororwa kwemaoko mashoma.
Zvikwata zvekugadzira zvinogona prototype pfungwa nekukurumidza nekudzokororwa kwemaoko mashoma. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Mashandisirwo anogona kushandisa masaini emifananidzo nemavhidhiyo ayo aimbove akaoma kugadzirisa.
Mashandisirwo anogona kushandisa masaini emifananidzo nemavhidhiyo ayo aimbove akaoma kugadzirisa. 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
Kusimbisa mamiriro-e-iyo-mameseji-kune-mufananidzo modhi seStable Diffusion 3 uye Flux inoshandisa yakagadziridzwa kuyerera kudzidziswa.
Kugadzira mifananidzo mumatanho mashoma ekuenzanisira pane echinyakare kupararira, kudzikisa komputa uye latency
Robotics policy yekudzidza, uko kuyerera kunoenderana nemodheru yakatsetseka chiito trajectories kubva pakuona
Yekukurumidza vhidhiyo uye 3D chizvarwa cheasset chinobatsirwa kubva kune dzakatwasuka, shoma-nhanho sampling nzira
Maitiro Ekuita
Flow Matching mukuita
Kusimbisa mamiriro-e-iyo-mavara mavara-kune-mufananidzo mhando seStable Diffusion 3 uye Flux inoshandisa yakagadziridzwa kuyerera kudzidziswa.
Kusimbaradza mamiriro-e-iyo-mavara mameseji-kune-mufananidzo modhi seStable Diffusion 3 uye Flux anoshandisa yakagadziridzwa kuyerera kwekudzidzisa Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvinobudirira kubudirira uye kukanganisa mutengo nekufamba kwenguva.
Flow Matching mukuita
Kugadzira mifananidzo mumatanho mashoma ekuenzanisira pane echinyakare kupararira, kudzikisa komputa uye latency.
Kugadzira mifananidzo mumatanho mashoma ekuenzanisira kupfuura kupararira kwechinyakare, kudzikisa komputa uye latency Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa nemitengo yekukanganisa nekufamba kwenguva.
Flow Matching mukuita
Robotics policy yekudzidza, uko kuyerera kunoenderana nemodheru yakatsetseka chiito trajectories kubva pakuona.
Kudzidzira mutemo weRobhoti, uko kuyerera kunoenderana nemamodhi akatsetseka ekuita trajectories kubva pakuona Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa nemitengo yekukanganisa nekufamba kwenguva.
Flow Matching mukuita
Yekukurumidza vhidhiyo uye 3D chizvarwa cheasset chinobatsirwa kubva kune dzakatwasuka, shoma-nhanho sampling nzira.
Inokurumidza vhidhiyo uye 3D chizvarwa cheasset chinobatsirwa kubva kune dzakatwasuka, shoma-nhanho dzesampling nzira Matimu anowanzo kuwana zvirinani mhedzisiro kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Njodzi & Guardrails
Kodzero dzemifananidzo uye kubvumirwa kunogona kuve njodzi dzepamutemo kana provenance isina kujeka.
Kuita kwemuenzaniso kunogona kusiyanisa kupenya, huwandu hwevanhu, uye nharaunda.
Manyepo enhema anogona kusacherechedzwa kunze kwekunge zvikumbaridzo zvekuvimba zvikatariswa.
Implementation Roadmap
Tsanangura maitiro ekugamuchirwa echokwadi, kurangarira, uye mutengo wekukanganisa.
Tsanangura maitiro ekugamuchirwa echokwadi, kurangarira, uye mutengo wekukanganisa. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Edzai nedata rinoenderana nemamiriro chaiwo ekugadzira.
Edzai nedata rinoenderana nemamiriro chaiwo ekugadzira. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Wedzera ongororo yemunhu kune yakaderera-kusavimbika kana yakakwirira-inokanganisa kufanotaura.
Wedzera ongororo yemunhu kune yakaderera-kusavimbika kana yakakwirira-inokanganisa kufanotaura. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Tevera modhi kudonha uye simbisa mushure mekuchinja kwekamera kana dataset.
Tevera modhi kudonha uye simbisa mushure mekuchinja kwekamera kana dataset. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.