{"id":4233,"date":"2023-08-12T14:19:47","date_gmt":"2023-08-12T14:19:47","guid":{"rendered":"https:\/\/dailyai.com\/?p=4233"},"modified":"2023-08-17T17:26:18","modified_gmt":"2023-08-17T17:26:18","slug":"ibm-announces-brain-like-ai-chip-with-lower-power-demands","status":"publish","type":"post","link":"https:\/\/dailyai.com\/de\/2023\/08\/ibm-announces-brain-like-ai-chip-with-lower-power-demands\/","title":{"rendered":"IBM k\u00fcndigt gehirn\u00e4hnlichen KI-Chip mit geringerem Energiebedarf an"},"content":{"rendered":"

IBM hat einen bio-inspirierten Chip entwickelt, der das Potenzial hat, KI umweltfreundlicher und energieeffizienter zu machen.\u00a0<\/b><\/p>\n

Da superstarke KI-Modelle wie ChatGPT in der Gesellschaft allgegenw\u00e4rtig sind, haben gro\u00dfe Tech-Konkurrenten wie Google, Microsoft, Meta und Start-ups wie Anthropic und Inflection begonnen, riesige Mengen an Rechenleistung zu horten.\u00a0<\/span><\/p>\n

Die zum Trainieren von KI ben\u00f6tigte Hardware ist sehr stromhungrig und tr\u00e4gt zu den bereits enormen <\/span>Umweltauswirkungen von Rechenzentren<\/span><\/a>.\u00a0<\/span><\/p>\n

Dies hat zu Forschungs- und Entwicklungsanstrengungen gef\u00fchrt, um innovative KI-Chips zu entwickeln, die schwere Arbeitslasten bei geringerem Stromverbrauch bew\u00e4ltigen k\u00f6nnen. Nvidias neueste <\/span>GH2000-Chip<\/span><\/a> hat bereits eine h\u00f6here Energieeffizienz als seine Vorg\u00e4nger erreicht. Das Unternehmen behauptet, dass es Rechenzentren 12 Mal billiger macht und 20 Mal weniger Energie verbraucht.\u00a0<\/span><\/p>\n

IBM's <\/span>neuer bio-inspirierter analoger Chip<\/span><\/a> ist dem biologischen Gehirn nachempfunden und eignet sich f\u00fcr tragbare Arbeitsger\u00e4te wie Autos, Telefone und Kameras.\u00a0<\/span><\/p>\n

Thanos Vasilopoulos, Wissenschaftler im IBM-Forschungslabor in Z\u00fcrich, <\/span>sagte der BBC<\/span><\/a>Im Vergleich zu herk\u00f6mmlichen Computern erreicht das menschliche Gehirn eine bemerkenswerte Leistung bei minimalem Stromverbrauch.<\/span><\/p>\n

Die meisten bestehenden Chips sind digital und verwenden Bin\u00e4rwerte (0 und 1) zur Datenspeicherung. Der neue Chip von IBM unterscheidet sich davon, da er analoge Komponenten, so genannte Memristoren (Speicherwiderst\u00e4nde), verwendet, die unterschiedliche Zahlenwerte speichern k\u00f6nnen. <\/span><\/p>\n

Diese analoge Natur der Memristoren spiegelt die synaptischen Funktionen wider. Es ist nicht der erste bio-inspirierte Chip - ein indisches Forscherteam hat erfolgreich <\/span>eine im Jahr 2022 entworfen<\/span><\/a>.\u00a0<\/span><\/p>\n

Professor. Ferrante Neri von der University of Surrey erkl\u00e4rte: \"Miteinander verbundene Memristoren k\u00f6nnen ein Netzwerk bilden, das ein biologisches Gehirn widerspiegelt.\"\u00a0<\/span><\/p>\n

Obwohl der IBM-Chip in erster Linie analog ist, enth\u00e4lt er auch einige digitale Komponenten, die die Kompatibilit\u00e4t mit aktuellen KI-Systemen gew\u00e4hrleisten.\u00a0<\/span><\/p>\n

Diese leichten Chips w\u00e4ren besonders n\u00fctzlich f\u00fcr Gadgets, Fahrzeuge und IoT-Hardware.\u00a0<\/span><\/p>\n

IBMs neuer analoger Chip f\u00fcr Deep Learning<\/span><\/h2>\n

Die Chips von IBM reduzieren den Stromverbrauch und bieten gleichzeitig eine beeindruckende Leistung in einem leichten Paket. <\/span><\/p>\n

Diese Chips sind dem menschlichen Gehirn nachempfunden, das etwa so viel Watt verbraucht wie eine Gl\u00fchbirne.<\/span><\/p>\n

Hier sind die wichtigsten Punkte:<\/span><\/p>\n

    \n
  • Aktuelle Einschr\u00e4nkungen der AI-Hardware<\/b>: Die meisten KI-Architekturen trennen den Speicher von den Verarbeitungseinheiten, was bedeutet, dass sie st\u00e4ndig Daten zwischen den beiden austauschen m\u00fcssen, was die Berechnungen verlangsamt und die Energieeffizienz beeintr\u00e4chtigt.<\/span><\/li>\n
  • Analoge Chips<\/b>: In Anlehnung an die Funktionen des menschlichen Gehirns verwendet IBM einen Phasen\u00e4nderungsspeicher (PCM), der seinen Zustand als ein Spektrum von Werten und nicht als 0 und 1 registriert. Dadurch wird der Bedarf an Daten\u00fcbertragung zwischen Speicher und Prozessor reduziert.<\/span><\/li>\n
  • Der technische Teil<\/b>: Das Design von IBM verf\u00fcgt \u00fcber 64 analoge In-Memory-Rechenkerne, von denen jeder ein 256 x 256 gro\u00dfes synaptisches Array enth\u00e4lt. Jeder Kern kann eine Modellschicht eines tiefen neuronalen Netzes (DNN) berechnen. Eine zentrale digitale Verarbeitungseinheit auf dem Chip f\u00fchrt weitere komplexe Operationen durch.<\/span><\/li>\n
  • Leistungsmetriken<\/b>: Der Chip erreichte eine hervorragende Genauigkeit von 92,81% bei einem Computer-Vision (CV)-Benchmark-Test. Er ist mehr als 15-mal effizienter als mehrere bestehende Chips.<\/span><\/li>\n<\/ul>\n

    Sobald sie verfeinert sind, werden diese biologisch inspirierten Chips digitale Chips in hybriden Architekturen begleiten. Dies wird leichtgewichtige, energieeffiziente KI-Systeme erm\u00f6glichen, die auch schwere Arbeitslasten bew\u00e4ltigen k\u00f6nnen.\u00a0<\/span><\/p>\n

    Mit der Zeit werden diese Chips leicht genug sein, um in intelligenten autonomen Technologien eingesetzt zu werden und m\u00f6glicherweise eine neue Generation von Robotern hervorzubringen, die laufen, sprechen und mit ihrer Umgebung interagieren, ohne \u00fcberm\u00e4\u00dfig viel Strom zu verbrauchen.<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    IBM hat einen bio-inspirierten Chip entwickelt, der das Potenzial hat, KI umweltfreundlicher und energieeffizienter zu machen. Da superstarke KI-Modelle wie ChatGPT in der Gesellschaft allgegenw\u00e4rtig sind, haben gro\u00dfe Tech-Konkurrenten wie Google, Microsoft, Meta und Start-ups wie Anthropic und Inflection begonnen, gro\u00dfe Mengen an Rechenleistung zu horten. Die zum Trainieren von KI ben\u00f6tigte Hardware ist sehr stromhungrig und tr\u00e4gt zu den bereits enormen Umweltauswirkungen von Rechenzentren bei. Dies hat zu Forschungs- und Entwicklungsanstrengungen gef\u00fchrt, um innovative KI-Chips zu entwickeln, die schwere Arbeitslasten bei geringerem Stromverbrauch bew\u00e4ltigen k\u00f6nnen. Der neueste GH2000-Chip von Nvidia hat bereits eine h\u00f6here Energieeffizienz als seine Vorg\u00e4nger erreicht, wobei das Unternehmen behauptet<\/p>","protected":false},"author":2,"featured_media":4234,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[],"class_list":["post-4233","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry"],"yoast_head":"\nIBM announces brain-like AI chip with lower power demands | DailyAI<\/title>\n<meta name=\"description\" content=\"IBM has developed a bio-inspired chip with the potential to make AI greener and more energy-efficient.\u00a0\" \/>\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\/08\/ibm-announces-brain-like-ai-chip-with-lower-power-demands\/\" \/>\n<meta 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