{"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\/it\/2023\/08\/ibm-announces-brain-like-ai-chip-with-lower-power-demands\/","title":{"rendered":"IBM annuncia un chip per l'intelligenza artificiale simile a un cervello con minori esigenze di potenza"},"content":{"rendered":"

IBM ha sviluppato un chip bio-ispirato con il potenziale di rendere l'intelligenza artificiale pi\u00f9 verde e pi\u00f9 efficiente dal punto di vista energetico.\u00a0<\/b><\/p>\n

Mentre modelli di IA super potenti come ChatGPT diventano onnipresenti nella societ\u00e0, i grandi rivali tecnologici come Google, Microsoft, Meta e startup come Anthropic e Inflection hanno iniziato ad accumulare grandi quantit\u00e0 di potenza di calcolo.\u00a0<\/span><\/p>\n

L'hardware necessario per l'addestramento dell'IA \u00e8 affamato di energia, contribuendo alla gi\u00e0 vasta <\/span>impatto ambientale dei data center<\/span><\/a>.\u00a0<\/span><\/p>\n

Questo ha dato il via agli sforzi di ricerca e sviluppo per costruire chip AI innovativi in grado di gestire carichi di lavoro pesanti con un consumo energetico ridotto. L'ultima novit\u00e0 di Nvidia <\/span>Chip GH2000<\/span><\/a> ha gi\u00e0 raggiunto una maggiore efficienza energetica rispetto ai suoi predecessori e l'azienda dichiara che render\u00e0 i data center 12 volte pi\u00f9 economici e utilizzer\u00e0 20 volte meno energia.\u00a0<\/span><\/p>\n

IBM <\/span>nuovo chip analogico bio-ispirato<\/span><\/a> \u00e8 modellato sul cervello biologico e sar\u00e0 efficace nei carichi di lavoro portatili come automobili, telefoni e macchine fotografiche.\u00a0<\/span><\/p>\n

Thanos Vasilopoulos, scienziato del laboratorio di ricerca IBM di Zurigo, <\/span>ha dichiarato alla BBC<\/span><\/a>Rispetto ai computer tradizionali, il cervello umano raggiunge prestazioni notevoli con un consumo energetico minimo\".<\/span><\/p>\n

La maggior parte dei chip esistenti sono digitali e utilizzano valori binari (0 e 1) per la memorizzazione dei dati. Il nuovo chip di IBM si distingue perch\u00e9 utilizza componenti analogici noti come memristori (resistenze di memoria), in grado di memorizzare valori numerici variabili. <\/span><\/p>\n

La natura analogica dei memristori rispecchia le funzioni sinaptiche. Non \u00e8 il primo chip bio-ispirato: un gruppo di ricerca indiano \u00e8 riuscito con successo a <\/span>progettato nel 2022<\/span><\/a>.\u00a0<\/span><\/p>\n

Il prof. Ferrante Neri dell'Universit\u00e0 del Surrey ha spiegato: \"I memristori interconnessi possono creare una rete che rispecchia un cervello biologico\".\u00a0<\/span><\/p>\n

Sebbene sia principalmente analogico, il chip di IBM mantiene alcuni componenti digitali, garantendo la compatibilit\u00e0 con gli attuali sistemi di intelligenza artificiale.\u00a0<\/span><\/p>\n

Questi chip leggeri sarebbero particolarmente utili per gadget, veicoli e hardware IoT.\u00a0<\/span><\/p>\n

Il nuovo chip analogico di IBM per il deep learning<\/span><\/h2>\n

I chip di IBM riducono il consumo energetico e offrono prestazioni impressionanti in un pacchetto leggero. <\/span><\/p>\n

Questi chip sono modellati sul cervello umano, che consuma circa gli stessi watt di una lampadina.<\/span><\/p>\n

Ecco i punti chiave:<\/span><\/p>\n

    \n
  • Limiti attuali dell'hardware dell'IA<\/b>: La maggior parte delle architetture di intelligenza artificiale separa la memoria dalle unit\u00e0 di elaborazione, il che significa che devono continuamente scambiare dati tra le due, rallentando il calcolo e compromettendo l'efficienza energetica.<\/span><\/li>\n
  • Chip analogici<\/b>: Rispecchiando le funzioni del cervello umano, l'approccio di IBM impiega la memoria a cambiamento di fase (PCM), che registra il suo stato come uno spettro di valori piuttosto che come 0 e 1. Questo riduce la necessit\u00e0 di trasmissione dei dati tra memoria e processore. Questo riduce la necessit\u00e0 di trasmissione dei dati tra memoria e processore.<\/span><\/li>\n
  • La parte tecnica<\/b>: Il progetto di IBM prevede 64 core di calcolo analogici in memoria, ognuno dei quali contiene un array sinaptico di 256 per 256. Ogni core pu\u00f2 calcolare un livello di modello di rete neurale profonda (DNN). Ogni core pu\u00f2 calcolare un livello del modello di rete neurale profonda (DNN). Un'unit\u00e0 di elaborazione digitale centrale sul chip gestisce altre operazioni complesse.<\/span><\/li>\n
  • Metriche di prestazione<\/b>: Il chip ha raggiunto un'eccellente precisione di 92,81% in un test di benchmark di computer vision (CV). \u00c8 oltre 15 volte pi\u00f9 efficiente di diversi chip esistenti.<\/span><\/li>\n<\/ul>\n

    Una volta perfezionati, questi chip bio-ispirati affiancheranno i chip digitali in architetture ibride. Ci\u00f2 consentir\u00e0 di realizzare sistemi di intelligenza artificiale leggeri ed efficienti dal punto di vista energetico, in grado di gestire carichi di lavoro elevati.\u00a0<\/span><\/p>\n

    Alla fine, questi chip diventeranno abbastanza leggeri da poter essere impiegati nella tecnologia autonoma intelligente, dando vita a una nuova generazione di robot che camminano, parlano e interagiscono con l'ambiente circostante senza un eccessivo consumo di energia.<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    IBM ha sviluppato un chip bio-ispirato con il potenziale di rendere l'IA pi\u00f9 verde e pi\u00f9 efficiente dal punto di vista energetico. Man mano che modelli di IA super potenti come ChatGPT diventano onnipresenti nella societ\u00e0, i grandi rivali tecnologici come Google, Microsoft, Meta e startup come Anthropic e Inflection hanno iniziato ad accumulare grandi quantit\u00e0 di potenza di calcolo. L'hardware necessario per l'addestramento dell'IA \u00e8 affamato di energia e contribuisce all'impatto ambientale gi\u00e0 elevato dei data center. Questo ha dato il via agli sforzi di ricerca e sviluppo per costruire chip AI innovativi in grado di gestire carichi di lavoro pesanti con un consumo energetico ridotto. L'ultimo chip GH2000 di Nvidia ha gi\u00e0 raggiunto una maggiore efficienza energetica rispetto ai suoi predecessori.<\/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\/it\/2023\/08\/ibm-announces-brain-like-ai-chip-with-lower-power-demands\/\" \/>\n<meta property=\"og:locale\" content=\"it_IT\" 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