{"id":5143,"date":"2023-09-07T11:38:29","date_gmt":"2023-09-07T11:38:29","guid":{"rendered":"https:\/\/dailyai.com\/?p=5143"},"modified":"2023-09-07T11:38:29","modified_gmt":"2023-09-07T11:38:29","slug":"microsofts-algorithm-of-thoughts-will-make-ai-even-smarter","status":"publish","type":"post","link":"https:\/\/dailyai.com\/nb\/2023\/09\/microsofts-algorithm-of-thoughts-will-make-ai-even-smarter\/","title":{"rendered":"Microsofts tankealgoritme vil gj\u00f8re kunstig intelligens enda smartere"},"content":{"rendered":"<p><strong>Microsoft-forskere har utviklet en Algorithm of Thoughts (AoT), som er et paradigmeskifte i hvordan AI l\u00f8ser problemer.<\/strong><\/p>\n<p>AoT ble utviklet for \u00e5 f\u00e5 LLM-er til \u00e5 tenke mer som mennesker og bli mer effektive n\u00e5r det gjelder probleml\u00f8sning. Microsoft hevder at dens <a href=\"https:\/\/arxiv.org\/pdf\/2308.10379.pdf\">ny tiln\u00e6rming<\/a> kombinerer \"nyansene i menneskelig resonnering og den disiplinerte presisjonen i algoritmiske metoder\".<\/p>\n<p>Den n\u00e5v\u00e6rende Chain of Thought-prosessen som LLM-er som ChatGPT bruker, baserer seg p\u00e5 statistiske m\u00f8nstre for \u00e5 g\u00e5 fra prompt til output. Det er en veldig line\u00e6r progresjon fra problem til l\u00f8sning, ettersom LLM-en deler l\u00f8sningen opp i mindre trinn.<\/p>\n<p>Problemet med denne tiln\u00e6rmingen er at oppl\u00e6ringsdataene ikke alltid er tilstrekkelige, s\u00e5 noen ganger mangler det noen trinn. N\u00e5r dette skjer, blir LLM kreativ og <a href=\"https:\/\/dailyai.com\/nb\/2023\/07\/is-chatgpt-getting-worse-heres-everything-we-know-so-far\/\">hallusinerer<\/a> til \u00e5 fylle ut hullene med feil svar.<\/p>\n<p>En mer avansert teknikk som noen LLM-er bruker, er \u00e5 finne en l\u00f8sning ved hjelp av en \"Tree of Thought\"-tiln\u00e6rming. LLM-en f\u00f8lger flere line\u00e6re veier fra problem til l\u00f8sning og stopper n\u00e5r den treffer en l\u00f8sning som ikke er levedyktig.<\/p>\n<p>Men dette inneb\u00e6rer mange sp\u00f8rringer og krever mye minne og dataressurser.<\/p>\n<h2>Hva gj\u00f8r AoT bedre?<\/h2>\n<p>Med AoT evaluerer algoritmen de f\u00f8rste stegene i en potensiell l\u00f8sning og avgj\u00f8r tidlig om en tiln\u00e6rming er verdt \u00e5 forf\u00f8lge eller ikke. P\u00e5 den m\u00e5ten unng\u00e5r man at algoritmen hardnakket sl\u00e5r inn p\u00e5 en \u00e5penbart feil vei, for s\u00e5 \u00e5 m\u00e5tte finne p\u00e5 noe nytt.<\/p>\n<p>I stedet for en line\u00e6r tiln\u00e6rming gir AoT LLM muligheten til \u00e5 s\u00f8ke gjennom flere potensielle l\u00f8sninger og til og med g\u00e5 tilbake der det er n\u00f8dvendig. I stedet for \u00e5 starte fra begynnelsen igjen n\u00e5r den st\u00f8ter p\u00e5 en blindvei, kan den g\u00e5 tilbake til forrige trinn og fortsette \u00e5 utforske.<\/p>\n<p>Den n\u00e5v\u00e6rende tiln\u00e6rmingen LLM-ene bruker, er som \u00e5 kj\u00f8re fra hjemmet til destinasjonen, kj\u00f8re seg vill og deretter dra hjem igjen for \u00e5 pr\u00f8ve en annen rute. SUT-tiln\u00e6rmingen er \u00e5 kj\u00f8re tilbake til den siste feilkj\u00f8ringen og pr\u00f8ve en ny rute fra det punktet.<\/p>\n<p>Denne \"l\u00e6ring i kontekst\"-tiln\u00e6rmingen gj\u00f8r modellen mye mer strukturert og systematisk i m\u00e5ten den l\u00f8ser problemer p\u00e5. Det er mye mindre ressurskrevende og kan potensielt eliminere problemet LLM-er har med \u00e5 hallusinere.<\/p>\n<p>Selv med denne nye tiln\u00e6rmingen er AI fortsatt et stykke unna \u00e5 faktisk tenke og resonnere slik mennesker gj\u00f8r. Med AoT ser det imidlertid ut til at det er tatt et betydelig skritt i den retningen.<\/p>\n<p>En av konklusjonene forskerne trakk av eksperimentene sine, var at \"resultatene tyder p\u00e5 at det \u00e5 instruere en LLM ved hjelp av en algoritme kan f\u00f8re til en ytelse som overg\u00e5r algoritmens egen.\"<\/p>\n<p>Det er akkurat det hjernen v\u00e5r gj\u00f8r. Vi har en iboende evne til \u00e5 l\u00e6re nye ferdigheter som vi ikke kunne fra f\u00f8r. Tenk om et verkt\u00f8y som ChatGPT kunne l\u00e6re gjennom resonnementer uten behov for ytterligere oppl\u00e6ring.<\/p>\n<p>Denne nye tiln\u00e6rmingen kan ogs\u00e5 f\u00f8re til at AI blir mer transparent i sin \"tankeprosess\", slik at vi f\u00e5r et innblikk i hva som faktisk skjer bak koden.<\/p>","protected":false},"excerpt":{"rendered":"<p>Microsoft-forskere har utviklet en Algorithm of Thoughts (AoT), som er et paradigmeskifte i hvordan AI l\u00f8ser problemer. AoT ble utviklet for \u00e5 f\u00e5 LLM-er til \u00e5 tenke mer som mennesker og bli mer effektive i probleml\u00f8sning. Microsoft hevder at den nye tiln\u00e6rmingen kombinerer \"nyansene i menneskelig resonnement og den disiplinerte presisjonen i algoritmiske metoder\". Den n\u00e5v\u00e6rende Chain of Thought-prosessen som LLM-er som ChatGPT bruker, baserer seg p\u00e5 statistiske m\u00f8nstre for \u00e5 g\u00e5 fra prompt til output. Det er en veldig line\u00e6r progresjon fra problem til l\u00f8sning, ettersom LLM-en bryter l\u00f8sningen opp i mindre trinn. Problemet med<\/p>","protected":false},"author":6,"featured_media":2181,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[207,105,121],"class_list":["post-5143","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-llm","tag-machine-learning","tag-microsoft"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Microsoft\u2019s Algorithm of Thoughts will make AI even smarter | 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\/09\/microsofts-algorithm-of-thoughts-will-make-ai-even-smarter\/\" \/>\n<meta property=\"og:locale\" content=\"nb_NO\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Microsoft\u2019s Algorithm of Thoughts will make AI even smarter | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Microsoft researchers have developed an Algorithm of Thoughts (AoT) which is a paradigm shift in how AI solves problems. The AoT was developed to make LLMs think more like humans do and to become more efficient at problem-solving. Microsoft claims that its new approach combines the &#8220;nuances of human reasoning and the disciplined precision of algorithmic methodologies.&#8221; The current Chain of Thought process that LLMs like ChatGPT use, relies on statistical patterns to go from prompt to output. It\u2019s a very linear progression from problem to solution as the LLM breaks the solution up into smaller steps. 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