{"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\/pt\/2023\/08\/ibm-announces-brain-like-ai-chip-with-lower-power-demands\/","title":{"rendered":"IBM anuncia chip de IA semelhante ao c\u00e9rebro com menores exig\u00eancias de energia"},"content":{"rendered":"

A IBM desenvolveu um chip de inspira\u00e7\u00e3o biol\u00f3gica com potencial para tornar a IA mais ecol\u00f3gica e mais eficiente em termos energ\u00e9ticos.\u00a0<\/b><\/p>\n

\u00c0 medida que modelos de IA superpoderosos como o ChatGPT se tornam omnipresentes em toda a sociedade, grandes rivais tecnol\u00f3gicos como a Google, a Microsoft, a Meta e empresas em fase de arranque como a Anthropic e a Inflection come\u00e7aram a acumular grandes quantidades de poder de computa\u00e7\u00e3o.\u00a0<\/span><\/p>\n

O hardware necess\u00e1rio para treinar a IA consome muita energia, o que contribui para o j\u00e1 vasto <\/span>impacto ambiental dos centros de dados<\/span><\/a>.\u00a0<\/span><\/p>\n

Este facto desencadeou esfor\u00e7os de I&D para construir chips de IA inovadores capazes de cargas de trabalho pesadas com menor consumo de energia. O mais recente <\/span>Chip GH2000<\/span><\/a> j\u00e1 alcan\u00e7ou uma maior efici\u00eancia energ\u00e9tica do que os seus antecessores, com a empresa a afirmar que tornar\u00e1 os centros de dados 12 vezes mais baratos e utilizar\u00e1 20 vezes menos energia.\u00a0<\/span><\/p>\n

O programa da IBM <\/span>novo chip anal\u00f3gico de inspira\u00e7\u00e3o biol\u00f3gica<\/span><\/a> \u00e9 modelado no c\u00e9rebro biol\u00f3gico e ser\u00e1 eficaz em cargas de trabalho port\u00e1teis, como carros, telefones e c\u00e2maras.\u00a0<\/span><\/p>\n

Thanos Vasilopoulos, um cientista do laborat\u00f3rio de investiga\u00e7\u00e3o da IBM em Zurique, <\/span>disse \u00e0 BBC<\/span><\/a>Em compara\u00e7\u00e3o com os computadores tradicionais, o c\u00e9rebro humano consegue um desempenho not\u00e1vel com um consumo m\u00ednimo de energia\".<\/span><\/p>\n

A maioria dos chips existentes \u00e9 digital e usa bin\u00e1rios (0s e 1s) para armazenamento de dados. O novo chip da IBM distingue-se por utilizar componentes anal\u00f3gicos conhecidos como memristores (resist\u00eancias de mem\u00f3ria), capazes de armazenar valores num\u00e9ricos vari\u00e1veis. <\/span><\/p>\n

Esta natureza anal\u00f3gica dos memristores reflecte as fun\u00e7\u00f5es sin\u00e1pticas. N\u00e3o \u00e9 o primeiro chip bio-inspirado - uma equipa de investiga\u00e7\u00e3o indiana conseguiu <\/span>concebido em 2022<\/span><\/a>.\u00a0<\/span><\/p>\n

O Prof. Ferrante Neri, da Universidade de Surrey, explicou: \"Os memristores interligados podem criar uma rede que reflecte um c\u00e9rebro biol\u00f3gico\".\u00a0<\/span><\/p>\n

Embora essencialmente anal\u00f3gico, o chip da IBM mant\u00e9m alguns componentes digitais, garantindo a compatibilidade com os actuais sistemas de IA.\u00a0<\/span><\/p>\n

Estes chips leves seriam particularmente \u00fateis para gadgets, ve\u00edculos e hardware IoT.\u00a0<\/span><\/p>\n

O novo chip anal\u00f3gico da IBM para aprendizagem profunda<\/span><\/h2>\n

Os chips da IBM reduzem o consumo de energia ao mesmo tempo que proporcionam um desempenho impressionante numa embalagem leve. <\/span><\/p>\n

Estes chips s\u00e3o modelados no c\u00e9rebro humano, que consome aproximadamente os mesmos watts que uma l\u00e2mpada el\u00e9ctrica.<\/span><\/p>\n

Eis os pontos essenciais:<\/span><\/p>\n

    \n
  • Limita\u00e7\u00f5es actuais do hardware de IA<\/b>: A maioria das arquitecturas de IA separa a mem\u00f3ria das unidades de processamento, o que significa que t\u00eam de trocar continuamente dados entre as duas, tornando a computa\u00e7\u00e3o mais lenta e comprometendo a efici\u00eancia energ\u00e9tica.<\/span><\/li>\n
  • Chips anal\u00f3gicos<\/b>: Espelhando as fun\u00e7\u00f5es do c\u00e9rebro humano, a abordagem da IBM utiliza a mem\u00f3ria de mudan\u00e7a de fase (PCM), que regista o seu estado como um espetro de valores em vez de 0s e 1s. Isto reduz a necessidade de transmiss\u00e3o de dados entre a mem\u00f3ria e o processador.<\/span><\/li>\n
  • A parte t\u00e9cnica<\/b>: O projeto da IBM inclui 64 n\u00facleos anal\u00f3gicos de computa\u00e7\u00e3o na mem\u00f3ria, cada um contendo uma matriz sin\u00e1ptica de 256 por 256. Cada n\u00facleo pode computar uma camada de modelo de rede neural profunda (DNN). Uma unidade central de processamento digital no chip trata de outras opera\u00e7\u00f5es complexas.<\/span><\/li>\n
  • M\u00e9tricas de desempenho<\/b>: O chip obteve uma excelente precis\u00e3o de 92,81% num teste de refer\u00eancia de vis\u00e3o por computador (CV). \u00c9 mais de 15 vezes mais eficiente do que v\u00e1rios chips existentes.<\/span><\/li>\n<\/ul>\n

    Uma vez aperfei\u00e7oados, estes chips de inspira\u00e7\u00e3o biol\u00f3gica acompanhar\u00e3o os chips digitais em arquitecturas h\u00edbridas. Isto permitir\u00e1 sistemas de IA leves e eficientes do ponto de vista energ\u00e9tico que podem ainda suportar cargas de trabalho pesadas.\u00a0<\/span><\/p>\n

    Eventualmente, estes chips tornar-se-\u00e3o suficientemente leves para serem utilizados em tecnologia aut\u00f3noma inteligente, potencialmente dando in\u00edcio a uma nova gera\u00e7\u00e3o de rob\u00f4s que andam, falam e interagem com o seu ambiente sem consumo excessivo de energia.<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    A IBM desenvolveu um chip de inspira\u00e7\u00e3o biol\u00f3gica com potencial para tornar a IA mais ecol\u00f3gica e mais eficiente em termos energ\u00e9ticos. \u00c0 medida que modelos de IA superpoderosos como o ChatGPT se tornam omnipresentes em toda a sociedade, grandes rivais tecnol\u00f3gicos como a Google, a Microsoft, a Meta e empresas em fase de arranque como a Anthropic e a Inflection come\u00e7aram a acumular grandes quantidades de pot\u00eancia de computa\u00e7\u00e3o. O hardware necess\u00e1rio para treinar a IA consome muita energia, contribuindo para o j\u00e1 vasto impacto ambiental dos centros de dados. Este facto desencadeou esfor\u00e7os de I&D para criar chips de IA inovadores capazes de suportar cargas de trabalho pesadas com menor consumo de energia. O mais recente chip GH2000 da Nvidia j\u00e1 alcan\u00e7ou uma maior efici\u00eancia energ\u00e9tica do que os seus antecessores, com a empresa a afirmar<\/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\/pt\/2023\/08\/ibm-announces-brain-like-ai-chip-with-lower-power-demands\/\" \/>\n<meta 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