Umhlahlandlela Wobunjiniyela Be-Loop: I-'autoresearch' kanye ne-'Bilevel Autoresearch' Ziwaguqula Kanjani Ama-AI Agents Awenze Umshini Ozimele Wokufunda Izihibe Zokucwaninga zeML

Iningi labantu lisasebenzisa i-AI njengebhokisi lokusesha lango-2015. Uyabhala, uyafunda, uyathayipha futhi. Iphethini entsha imiselela leyo manuwali emuva naphambili ngeluphu. Lo mhlahlandlela uyachaza ubunjiniyela be-loop usebenzisa ama-artifact amabili aqinisekisiwe. Imithombo ngeka-Andrej Karpathy autoresearch i-repository kanye ne- Bilevel Autoresearch iphepha. Uhlaka lulandela ukubhalwa ngu-@0xCodila.
Yini iLoop Engineering?
Ukuze uqale, qhathanisa izindlela ezimbili. Ukwaziswa kuwumyalelo owodwa, ngemva kwalokho unquma isinyathelo esilandelayo. Iluphu, ngokuphambene, inhloso imodeli ephishekelayo ize ifike. Imodeli ihlela, yenza, ihlole umphumela wayo, bese iphinda. Uchaza inhloso kanye, futhi iluphu iphatha ukuphindaphinda. Okubaluleke kakhulu, iluphu ithola izindleko zayo kuphela lapho umsebenzi ulinganiseka.
Izingxenye Ezintathu Ezenza Iluphu Isebenze
Ngakho-ke yini ehlukanisa iluphu yangempela ku-chatbot ngokuphinda? Yonke iluphu ethembekile inezingxenye ezintathu.
- A isiqinisekisi amamaki umzamo ngamunye. Lelo sheke lingaba ukuhlolwa okuphasayo, imethrikhi ehambayo, noma ibhilidi. Ngaphandle kwesiqinisekisi, i-ejenti ivele ivumelane nayo ngokwayo ngokuphinda.
- Izwe ibhala lokho okwazanywa, okwahluleka, nalokho okusele. Ifayela elincane eliseceleni livumela ukuqalisa okulandelayo kuqalise esikhundleni sokuqala kabusha.
- A isimo sokumisa ivimbela izindleko zokubaleka. Iluphu iyama lapho umgomo ufinyelelwa, noma ngemva kwemizamo ka-N.
I-Karpathy Loop: Ngaphakathi kwe-'autoresearch'
Lezi zingxenye ezintathu azizona ithiyori. NgoMashi 7, 2026, uKarpathy wakhululwa autoresearchinqolobane yomthombo ovulekile ngaphansi kwelayisensi ye-MIT. Ithumela amafayela amathathu ayisisekelo kanye nemigqa yekhodi engaba ngu-630. Le phrojekthi yanda ezinsukwini ezimbalwa futhi manje isiseduze nezinkanyezi ze-GitHub ezingu-90,000. Yabuye yethulwa njengephethini “i-Karpathy Loop.”
Umklamo mncane ngamabomu, kodwa uqinile. I-ejenti ihlela kuphela train.pyephethe imodeli ye-GPT, i-optimizer (i-Muon ne-AdamW), ne-loop yokuqeqesha. Ayikwazi ukuthinta izinsiza zokuhlola ku prepare.py. Lokho kuhlukaniswa kumisa i-ejenti ekwenzeni ukuhlolwa kube lula esikhundleni semodeli ibe ngcono. Phakathi naleso sikhathi, umuntu uyabhala program.mdimiyalelo umenzeli okufanele ayihloniphe.
Umjikelezo ngamunye uqhuba isilingo esisodwa. I-ejenti ifunda ikhodi, iphakamise ushintsho, iqeqeshe imizuzu emihlanu, bese igcina noma ihlehle. Imethrikhi yamaphuzu ithi val_bpbizingcezu zokuqinisekisa ibhayithi ngayinye, lapho okuphansi kungcono khona. Leso sabelomali sikhiqiza cishe izivivinyo eziyi-12 ngehora, ngakho-ke cishe eziyi-100 zisebenza ngobusuku obubodwa.
Imiphumela ebikiwe iqinile. U-Karpathy ukhombe kokwakhe osekulungiselelwe nanochat Ikhodi yokuqeqesha ye-GPT-2. Ithathe izinsuku ezimbili futhi yaqeda ukuhlola okungaba ngu-700, igcina ukuthuthuka kwangempela okungu-20. Kuhlanganiswe ndawonye, lokho kulungiswa kunqamula isikhathi sokuqeqeshwa sekhwalithi ye-GPT-2 ngo-11%, sisuka ku-2.02 siye emahoreni angu-1.80. Okunye okutholakele kwaba a QK-Norm ukuqaliswa kushoda isiphindaphindi se-scalar, ebesishiye ukunaka kusabalele kakhulu kuwo wonke amakhanda.
Ngokuphawulekayo, abantu bayakhathala ngemva kokuhlolwa cishe kweshumi nambili, kuyilapho iluphu ayikhathali. Ngokuhlukana, isikhulu esiphezulu sakwaShopify uTobi Lütke wagijima autoresearch ubusuku bonke kumodeli yangaphakathi. Ubike ukuthuthuka okungu-19% ngemuva kokuhlolwa okungu-37. I-Karpathy's takeaway: uma unemethrikhi ephokophelwe, uyibhodlela.
I-Prompt vs Loop vs Bilevel Loop
Umehluko uya ucaca ngokuhlanganyela.
| Isici | Umyalo wesibhamu esisodwa | I-Karpathy loop (autoresearch) |
I-Bilevel Autoresearch |
|---|---|---|---|
| Uyachaza | Isinyathelo ngasinye | Igoli, kanye | Igoli, kanye |
| Ophindaphindayo | Wena | I-ejenti yangaphakathi | I-ejenti yangaphakathi + yangaphandle |
| Isiqinisekisi | Wena, ngokwenza | prepare.py (val_bpb) |
Imethrikhi efanayo, amaleveli amabili |
| Izwe | Xoxa kuphela | Ilogi yokuhlola | Ilogi kanye nekhodi ejovwe |
| Iqhaza lomuntu | Injini | Umbhali we program.md |
Umbhali we program.md |
| Umphumela obikiwe | Iyahlukahluka | 700 ugijima → 20 ukulungiswa, 11% speedup | 5x ukwehla okukhulu kwe-val_bpb |
Amabhulokhi Wokwakha Amahlanu
Ngenxa yalokho, amaqembu onjiniyela be-AI manje ahlanganisa izihibe zokusebenza kusuka izingcezu ezinhlanu ezingasetshenziswa kabusha:
- Okuzenzakalelayo ivula iluphu kushejuli, umcimbi, noma i-trigger.
- A ikhono igcina ulwazi lwephrojekthi efayeleni lokumaka, elifundwa kukho konke ukugijima.
- Ama-sub-ejenti hlukanisa umbhali kumbuyekezi, njengoba imodeli eyodwa ifaka amamaki ngokuphana kakhulu.
- Izixhumi vumela iluphu isebenze ngaphakathi kwamathuluzi wangempela, njenge-tracker yenkinga noma i-Slack.
- Ekugcineni, a isiqinisekisi kusasele isango elenqaba umsebenzi omubi. UClaude Code kanye ne-Codex manje sezithumela zonke ezinhlanu.
I-Bilevel Autoresearch: Iluphu Phezulu Kweluphu
Ngokulandelayo, abacwaningi babuza umbuzo obukhali. Uma i-autoresearch ingucwaningo, ungacwaninga ngokuzenzakalelayo ucwaningo? Iphepha locwaningo Bilevel Autoresearch: Meta-Autoresearching Itself uphendula yebo.
I iluphu yangaphakathi ihambisana nokwasekuqaleni kukaKarpathy: phakamisa, qeqesha, hlaziya, gcina noma ulahle. I iluphu yangaphandle ubuka iluphu yangaphakathi futhi ifunde ikhodi yayo kanye nemikhondo. Ikhomba lapho ukusesha ngokwako kuhlala kumile. Bese ibhala izindlela ezintsha zePython, izijove ngesikhathi sokusebenza, bese iphinda isebenzise iluphu yangaphakathi.
Umphumela ubambe ibhentshimakhi ye-Karpathy's GPT pretraining. Iluphu yangaphandle isikiwe val_bpb 5x ngaphezu kweluphu eyodwa (-0.045 vs -0.009). Ngokuphawulekayo, amalophu womabili asebenzise i-LLM efanayo, ngakho-ke inzuzo iqhamuke ekwakhiweni kwezakhiwo, hhayi imodeli ehlakaniphile. Ngokwenza umklamo uhlukana ube amazinga amathathu. Ileveli 1 isebenzisa iluphu eyisisekelo. Izinga 1.5 zamapharamitha wokusesha njalo ekuphindaphindweni okuhlanu. Ileveli 2 ikhiqiza izindlela ngeseshini eyimizuliswano emine. Ukuhlolwa okubikiwe kusebenzise i-RTX 5090 32GB kanye nesabelomali semizuzwana engama-300.
Isizathu kufanele siphawulwe. I-loop yangaphakathi ibilokhu ibuyela kokubalulekile okufanayo, ngisho nangemva kokuyeka ukusebenza. Iluphu yangaphandle yephule lawo maphethini ngokuphoqa ukuhlola okungajwayelekile.
Sebenzisa Amacala anezibonelo
Le mibono idlulisa kahle ngaphezu kokuqeqeshwa kwangaphambili. Ngomsebenzi wemodeli, iluphu isesha ama-hyperparameter kuze kube val_bpb amaconsi. Okwesofthiwe, yenza kabusha kuze kube yilapho izivivinyo, izinhlobo, kanye nokudlula kokwakha. Kokuqukethwe, ibhala kabusha kuze kube yilapho wonke amaphuzu erubrikhi esusa umkhawulo. Ukuze uthole idatha, ishuna ipayipi kuze kube yilapho i-schema sibheka ukubanjwa. Icala ngalinye linesici esisodwa: isango elizenzakalelayo elingahluleka umsebenzi.
Zizame ngokwakho: I-Loop In One Prompt
Ithiyori eceleni, ungamuzwa umakhenikha ngaphandle kwe-Claude Code noma i-Codex. Namathisela lokhu kunoma iyiphi imodeli enekhono futhi uyibuke izilungisa yona.
You will work in a loop until the task meets the bar.
TASK:
[describe exactly what you want produced]
SUCCESS CRITERIA (be strict):
- [criterion 1]
- [criterion 2]
- [criterion 3]
LOOP PROTOCOL, repeat every turn:
1. PLAN - state the single next step.
2. DO - produce or improve the work.
3. VERIFY - score the result 1-10 on each criterion. Be honest.
4. DECIDE - if every criterion is 8+, print FINAL and stop.
Otherwise print ITERATING and fix the weakest point first.
RULES:
- Never call it done until every criterion is 8 or higher.
- Each pass must fix the weakest score from the last VERIFY.
- Do not ask questions. Make a sensible assumption and continue.
Begin.
Ngaphansi, ukugeleza kokulawula kuncane. Uhlaka lwamathambo olungezansi lubonisa lezo zingxenye ezintathu ku-Python: isiqinisekisi, isinqumo, nezimo ezimbili zokuma.
current = baseline
best = evaluate(current) # verifier: lower val_bpb is better
for step in range(MAX_STEPS): # stop condition 1: experiment budget
candidate = propose_change(current) # agent edits train.py
score = train_and_eval(candidate) # train 5 min, then verify
if score < best: # keep only real improvements
current, best = candidate, score # commit
# else: discard candidate, restore baseline
if best <= TARGET: # stop condition 2: goal met
break
Zombili izinguqulo zilinganiselwe. Useyicupha, futhi ukuvala ithebhu kusula isimo. Ukwengeza i-automation, ifayela lesimo, nesango langempela liphendulela lokhu ku-loop ezimele.
Ibone Igijima
Idemo esebenzisanayo engezansi igqwayiza iluphu eyodwa egcwele: phakamisa, qeqesha, qinisekisa, bese ugcine noma ubuyele emuva. Lungisa ithagethi kanye nomkhawulo wesinyathelo, futhi ubuke val_bpb ukuwa kuze kube yilapho isimo sokumisa sivutha.



