{"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\/de\/2023\/09\/microsofts-algorithm-of-thoughts-will-make-ai-even-smarter\/","title":{"rendered":"Microsofts Algorithmus der Gedanken wird KI noch intelligenter machen"},"content":{"rendered":"<p><strong>Microsoft-Forscher haben einen Algorithmus der Gedanken (Algorithm of Thoughts, AoT) entwickelt, der einen Paradigmenwechsel bei der L\u00f6sung von Problemen durch KI darstellt.<\/strong><\/p>\n<p>Das AoT wurde entwickelt, um LLMs dazu zu bringen, mehr wie Menschen zu denken und effizienter bei der L\u00f6sung von Problemen zu werden. Microsoft behauptet, dass sein <a href=\"https:\/\/arxiv.org\/pdf\/2308.10379.pdf\">neuer Ansatz<\/a> kombiniert die \"Nuancen des menschlichen Denkens mit der disziplinierten Pr\u00e4zision algorithmischer Methoden\".<\/p>\n<p>Der derzeitige Chain-of-Thought-Prozess, den LLMs wie ChatGPT verwenden, st\u00fctzt sich auf statistische Muster, um von der Eingabe zur Ausgabe zu gelangen. Es ist eine sehr lineare Progression vom Problem zur L\u00f6sung, da der LLM die L\u00f6sung in kleinere Schritte aufteilt.<\/p>\n<p>Das Problem bei diesem Ansatz ist, dass die Trainingsdaten nicht immer ausreichend sind, so dass manchmal einige Schritte fehlen. Wenn dies geschieht, wird der LLM kreativ und <a href=\"https:\/\/dailyai.com\/de\/2023\/07\/is-chatgpt-getting-worse-heres-everything-we-know-so-far\/\">halluziniert<\/a> die L\u00fccken mit einer falschen Antwort auszuf\u00fcllen.<\/p>\n<p>Eine fortschrittlichere Technik, die einige LLMs verwenden, ist die Suche nach einer L\u00f6sung unter Verwendung des Denkbaums. Das LLM folgt mehreren linearen Pfaden vom Problem zur L\u00f6sung und h\u00e4lt an, wenn es auf eine unrentable L\u00f6sung st\u00f6\u00dft.<\/p>\n<p>Dies erfordert jedoch eine Vielzahl von Abfragen und ist sehr speicher- und rechenintensiv.<\/p>\n<h2>Was macht AoT besser?<\/h2>\n<p>Mit AoT bewertet der Algorithmus die ersten Schritte einer m\u00f6glichen L\u00f6sung und entscheidet fr\u00fchzeitig, ob ein Ansatz verfolgt werden soll oder nicht. So wird verhindert, dass er stur einen offensichtlich falschen Weg einschl\u00e4gt und sich dann etwas einfallen lassen muss.<\/p>\n<p>Anstelle eines linearen Ansatzes gibt AoT dem LLM die M\u00f6glichkeit, mehrere potenzielle L\u00f6sungen zu durchsuchen und bei Bedarf sogar zur\u00fcckzugehen. Anstatt wieder von vorne zu beginnen, wenn es auf eine Sackgasse st\u00f6\u00dft, kann es zum vorherigen Schritt zur\u00fcckkehren und die Suche fortsetzen.<\/p>\n<p>Die derzeitige Herangehensweise der LLMs ist so, als w\u00fcrde man von zu Hause zu seinem Ziel fahren, sich verfahren und dann zur\u00fcck nach Hause fahren, um eine andere Route zu versuchen. Der AoT-Ansatz besteht darin, einfach zur letzten falschen Abzweigung zur\u00fcckzukehren und von dort aus eine neue Route zu versuchen.<\/p>\n<p>Dieser Ansatz des \"kontextbezogenen Lernens\" erm\u00f6glicht es dem Modell, viel strukturierter und systematischer an die L\u00f6sung von Problemen heranzugehen. Es ist viel weniger ressourcenhungrig und k\u00f6nnte m\u00f6glicherweise das Problem der Halluzinationen bei LLMs aus der Welt schaffen.<\/p>\n<p>Selbst mit diesem neuen Ansatz ist die KI noch weit davon entfernt, tats\u00e4chlich so zu denken und zu argumentieren wie der Mensch. Mit AoT scheint jedoch ein wichtiger Schritt in diese Richtung gemacht worden zu sein.<\/p>\n<p>Eine Schlussfolgerung, die die Forscher aus ihren Experimenten zogen, war, dass ihre \"Ergebnisse darauf hindeuten, dass die Instruktion eines LLM mit Hilfe eines Algorithmus zu einer Leistung f\u00fchren kann, die die des Algorithmus selbst \u00fcbertrifft\".<\/p>\n<p>Das ist genau das, was unser Gehirn tut. Wir haben die angeborene F\u00e4higkeit, neue F\u00e4higkeiten zu erlernen, die wir vorher nicht kannten. Stellen Sie sich vor, ein Tool wie ChatGPT w\u00e4re in der Lage, durch logisches Denken zu lernen, ohne dass eine weitere Schulung erforderlich w\u00e4re.<\/p>\n<p>Dieser neue Ansatz k\u00f6nnte auch dazu f\u00fchren, dass die KI in ihrem \"Denk\"-Prozess transparenter wird und uns einen Einblick in das gibt, was tats\u00e4chlich hinter dem Code passiert.<\/p>","protected":false},"excerpt":{"rendered":"<p>Microsoft-Forscher haben einen Algorithmus der Gedanken (Algorithm of Thoughts, AoT) entwickelt, der einen Paradigmenwechsel bei der L\u00f6sung von Problemen durch KI darstellt. Der AoT wurde entwickelt, um LLMs dazu zu bringen, mehr wie Menschen zu denken und effizienter bei der Probleml\u00f6sung zu werden. Microsoft behauptet, dass sein neuer Ansatz die \"Nuancen des menschlichen Denkens und die disziplinierte Pr\u00e4zision der algorithmischen Methoden\" kombiniert. Der derzeitige Chain-of-Thought-Prozess, den LLMs wie ChatGPT verwenden, st\u00fctzt sich auf statistische Muster, um von der Eingabe zur Ausgabe zu gelangen. Es ist eine sehr lineare Entwicklung vom Problem zur L\u00f6sung, da der LLM die L\u00f6sung in kleinere Schritte aufteilt. Das Problem mit<\/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\/de\/2023\/09\/microsofts-algorithm-of-thoughts-will-make-ai-even-smarter\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\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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