{"id":8400,"date":"2023-12-18T09:14:27","date_gmt":"2023-12-18T09:14:27","guid":{"rendered":"https:\/\/dailyai.com\/?p=8400"},"modified":"2023-12-18T09:14:27","modified_gmt":"2023-12-18T09:14:27","slug":"openai-releases-first-results-from-superalignment-project","status":"publish","type":"post","link":"https:\/\/dailyai.com\/nb\/2023\/12\/openai-releases-first-results-from-superalignment-project\/","title":{"rendered":"OpenAI lanserer de f\u00f8rste resultatene fra Superalignment-prosjektet"},"content":{"rendered":"

Dagens AI-modeller er i stand til \u00e5 gj\u00f8re mange usikre eller u\u00f8nskede ting. Menneskelig tilsyn og tilbakemeldinger holder disse modellene p\u00e5 linje, men hva vil skje n\u00e5r disse modellene blir smartere enn oss?<\/strong><\/p>\n

OpenAI sier at det er mulig at vi i l\u00f8pet av de neste ti \u00e5rene kan f\u00e5 en kunstig intelligens som er smartere enn mennesker. Med den \u00f8kte intelligensen f\u00f8lger ogs\u00e5 risikoen for at mennesker ikke lenger er i stand til \u00e5 overv\u00e5ke disse modellene.<\/p>\n

OpenAIs Superalignment-forskerteam fokuserer p\u00e5 \u00e5 forberede seg p\u00e5 en slik eventualitet. Teamet ble lansert i juli i \u00e5r og ledes av Ilya Sutskever, som har v\u00e6rt i skyggen siden Sam Altman oppsigelse og p\u00e5f\u00f8lgende gjenansettelse<\/a>.<\/p>\n

Begrunnelsen for prosjektet ble satt inn i en tankevekkende kontekst av OpenAI, som erkjente at \"for \u00f8yeblikket har vi ingen l\u00f8sning for \u00e5 styre eller kontrollere en potensielt superintelligent AI, og hindre den i \u00e5 bli useri\u00f8s\".<\/p>\n

Men hvordan forbereder du deg p\u00e5 \u00e5 kontrollere noe som ikke finnes enn\u00e5? Forskerteamet har nettopp lansert sin f\u00f8rste eksperimentelle resultater<\/a> mens den pr\u00f8ver \u00e5 gj\u00f8re nettopp det.<\/p>\n

Svak-til-sterk generalisering<\/h2>\n

Forel\u00f8pig er mennesker fortsatt i en sterkere intelligensposisjon enn AI-modeller. Modeller som GPT-4 styres eller justeres ved hjelp av Reinforcement Learning Human Feedback (RLHF). N\u00e5r en modells resultater er u\u00f8nskede, sier den menneskelige treneren til modellen \"Ikke gj\u00f8r det\", og bel\u00f8nner modellen med en bekreftelse p\u00e5 \u00f8nsket ytelse.<\/p>\n

Dette fungerer forel\u00f8pig fordi vi har en god forst\u00e5else av hvordan dagens modeller fungerer, og fordi vi er smartere enn dem. N\u00e5r fremtidens menneskelige dataforskere skal trene opp en superintelligent AI, vil intelligensrollene v\u00e6re ombyttet.<\/p>\n

For \u00e5 simulere denne situasjonen bestemte OpenAI seg for \u00e5 bruke eldre GPT-modeller som GPT-2 til \u00e5 trene opp kraftigere modeller som GPT-4. GPT-2 skulle simulere den fremtidige menneskelige treneren som pr\u00f8ver \u00e5 finjustere en mer intelligent modell.<\/p>\n

\"\"
Scenarier for AI-trening: Dagens, fremtidens og OpenAIs simulering. Kilde: OpenAI OpenAI<\/figcaption><\/figure>\n

I forskningsrapporten forklares det at \"Akkurat som problemet med mennesker som overv\u00e5ker overmenneskelige modeller, er v\u00e5rt oppsett et eksempel p\u00e5 det vi kaller weak-to-strong learning-problemet\".<\/p>\n

I eksperimentet brukte OpenAI GPT-2 til \u00e5 finjustere GPT-4 p\u00e5 NLP-oppgaver, sjakkoppgaver og bel\u00f8nningsmodellering. Deretter testet de GPT-4s ytelse p\u00e5 disse oppgavene og sammenlignet den med en GPT-4-modell som hadde blitt trent p\u00e5 \"grunnsannheten\" eller korrekte svar p\u00e5 oppgavene.<\/p>\n

Resultatene var lovende, for n\u00e5r GPT-4 ble trent opp av den svakere modellen, var den i stand til \u00e5 generalisere kraftig og gj\u00f8re det bedre enn den svakere modellen. Dette viste at en svakere intelligens kunne gi veiledning til en sterkere intelligens, som s\u00e5 kunne bygge videre p\u00e5 denne treningen.<\/p>\n

Tenk p\u00e5 det som om en tredjeklassing skulle l\u00e6re en veldig smart gutt litt matte, og s\u00e5 skulle den smarte gutten gj\u00f8re matte p\u00e5 12. klassetrinn basert p\u00e5 den f\u00f8rste oppl\u00e6ringen.<\/p>\n

Prestasjonsgap<\/h2>\n

Forskerne fant ut at fordi GPT-4 ble trent opp av en mindre intelligent modell, begrenset denne prosessen ytelsen til det som tilsvarte en riktig trent GPT-3.5-modell.<\/p>\n

Dette skyldes at den mer intelligente modellen l\u00e6rer noen av feilene eller de d\u00e5rlige tankeprosessene fra den svakere veilederen. Dette tyder p\u00e5 at det \u00e5 bruke mennesker til \u00e5 trene opp en superintelligent AI vil hindre AI-en i \u00e5 prestere til sitt fulle potensial.<\/p>\n

\"\"
Sammenligning av ytelsen til GPT-2, GPT-4 trent av GPT2, GPT-4 mer effektivt trent av GPT-2, og GPT-4 trent p\u00e5 riktige svar.<\/figcaption><\/figure>\n

Forskerne foreslo \u00e5 bruke mellommodeller i en bootstrapping-tiln\u00e6rming. I artikkelen forklarte de at \"i stedet for \u00e5 justere veldig overmenneskelige modeller direkte, kan vi f\u00f8rst justere en litt overmenneskelig modell, bruke den til \u00e5 justere en enda smartere modell, og s\u00e5 videre.\"<\/p>\n

OpenAI bruker mye ressurser p\u00e5 dette prosjektet. Forskerteamet sier at de har dedikert \"20% av databehandlingen vi har sikret oss hittil i l\u00f8pet av de neste fire \u00e5rene til \u00e5 l\u00f8se problemet med superintelligenstilpasning\".<\/p>\n

De tilbyr ogs\u00e5 $10 millioner i stipend til enkeltpersoner eller organisasjoner som \u00f8nsker \u00e5 bist\u00e5 med forskningen.<\/p>\n

De b\u00f8r finne ut av dette snart. En superintelligent AI kan potensielt skrive en million linjer med komplisert kode som ingen menneskelig programmerer kan forst\u00e5. Hvordan kan vi vite om den genererte koden er trygg \u00e5 kj\u00f8re eller ikke? La oss h\u00e5pe vi ikke finner ut av det p\u00e5 den harde m\u00e5ten.<\/p>","protected":false},"excerpt":{"rendered":"

Dagens AI-modeller er i stand til \u00e5 gj\u00f8re mange usikre eller u\u00f8nskede ting. Menneskelig tilsyn og tilbakemeldinger holder disse modellene p\u00e5 linje, men hva vil skje n\u00e5r disse modellene blir smartere enn oss? OpenAI sier at det er mulig at vi kan komme til \u00e5 se en AI som er smartere enn mennesker i l\u00f8pet av de neste ti \u00e5rene. Med \u00f8kt intelligens f\u00f8lger ogs\u00e5 en risiko for at mennesker ikke lenger er i stand til \u00e5 overv\u00e5ke disse modellene. OpenAIs forskningsteam Superalignment fokuserer p\u00e5 \u00e5 forberede seg p\u00e5 en slik mulighet. Teamet ble lansert i juli i \u00e5r og ledes av Ilya Sutskever<\/p>","protected":false},"author":6,"featured_media":8404,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[163,118,93],"class_list":["post-8400","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-ai-risks","tag-llms","tag-openai"],"yoast_head":"\nOpenAI releases first results from Superalignment project | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/nb\/2023\/12\/openai-releases-first-results-from-superalignment-project\/\" \/>\n<meta property=\"og:locale\" content=\"nb_NO\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"OpenAI releases first results from Superalignment project | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Current AI models are capable of doing a lot of unsafe or undesirable things. 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