{"id":8193,"date":"2023-12-11T20:18:10","date_gmt":"2023-12-11T20:18:10","guid":{"rendered":"https:\/\/dailyai.com\/?p=8193"},"modified":"2023-12-19T12:48:50","modified_gmt":"2023-12-19T12:48:50","slug":"researchers-perform-ai-speech-recognition-with-human-brain-cells","status":"publish","type":"post","link":"https:\/\/dailyai.com\/pt\/2023\/12\/researchers-perform-ai-speech-recognition-with-human-brain-cells\/","title":{"rendered":"Investigadores efectuam reconhecimento de fala com c\u00e9lulas cerebrais humanas"},"content":{"rendered":"

Aglomerados de c\u00e9lulas cerebrais humanas cultivadas em placas de Petri foram integrados em computadores para atingir um n\u00edvel fundamental de reconhecimento da fala.<\/b><\/p>\n

Feng Guo, da Indiana University Bloomington, explica o estudo, publicado na <\/span>Natureza Eletr\u00f3nica<\/span><\/a>Trata-se de uma demonstra\u00e7\u00e3o preliminar para mostrar a viabilidade do conceito. <\/span>H\u00e1 ainda um caminho consider\u00e1vel a percorrer\". <\/span><\/p>\n

Guo aponta dois desafios principais da IA convencional que esta forma de IA biol\u00f3gica procura resolver: o elevado consumo de energia e as limita\u00e7\u00f5es inerentes aos chips de sil\u00edcio, como as suas fun\u00e7\u00f5es distintas de processamento e armazenamento de informa\u00e7\u00e3o.<\/span><\/p>\n

A equipa de Guo, juntamente com outras, como a australiana Cortical Labs, que c\u00e9lulas cerebrais treinadas para jogar Pong em 2022<\/a>O grupo de investiga\u00e7\u00e3o \"Biocomputa\u00e7\u00e3o\" est\u00e1 a explorar a biocomputa\u00e7\u00e3o com c\u00e9lulas nervosas vivas como uma potencial solu\u00e7\u00e3o para estes desafios.\u00a0<\/span><\/p>\n

Estes organ\u00f3ides cerebrais - culturas de tecidos tridimensionais auto-organizadas, semelhantes a mini-c\u00e9rebros - emergem de c\u00e9lulas estaminais em condi\u00e7\u00f5es de crescimento espec\u00edficas.\u00a0<\/span><\/p>\n

Podem crescer at\u00e9 alguns mil\u00edmetros de di\u00e2metro e conter at\u00e9 100 milh\u00f5es de c\u00e9lulas nervosas. Em compara\u00e7\u00e3o, um c\u00e9rebro humano tem aproximadamente 100 mil milh\u00f5es de c\u00e9lulas nervosas. Os organ\u00f3ides s\u00e3o colocados sobre uma matriz de microelectrodos, que estimula o organoide e regista a atividade neuronal. A equipa de Guo chama a esta configura\u00e7\u00e3o \"Brainoware\".<\/span><\/p>\n

Essencialmente, o Brainoware \u00e9 uma nova forma de IA bastante diferente da que vemos habitualmente nos computadores e smartphones. <\/span><\/p>\n

Em vez de utilizar chips normais, os investigadores criaram um pequeno conjunto de c\u00e9lulas cerebrais humanas<\/a> - o organoide cerebral. Este min\u00fasculo \"mini-c\u00e9rebro\" \u00e9 cultivado em laborat\u00f3rio a partir de c\u00e9lulas estaminais e pode executar algumas tarefas b\u00e1sicas que normalmente associamos \u00e0 IA, como o reconhecimento de padr\u00f5es de fala.<\/span><\/p>\n

\"\"
A) Um diagrama do sistema \"Brainoware\", que mostra um organoide cerebral (um mini-c\u00e9rebro cultivado em laborat\u00f3rio) ligado a um dispositivo que regista e estimula a sua atividade el\u00e9ctrica. B) Uma imagem microsc\u00f3pica do organoide cerebral, corada para real\u00e7ar os seus diferentes tipos de c\u00e9lulas, tais como neur\u00f3nios maduros, astr\u00f3citos, neur\u00f3nios em fase inicial e c\u00e9lulas progenitoras, mostrando a sua complexa estrutura 3D. Fonte: Natureza Eletr\u00f3nica<\/a>.<\/figcaption><\/figure>\n

Como funciona<\/span><\/h2>\n

\u00a0O organoide cerebral \u00e9 colocado num dispositivo especial que pode enviar e ler sinais el\u00e9ctricos. <\/span><\/p>\n

Ao faz\u00ea-lo, os investigadores podem comunicar com o organoide, como se o ensinassem a responder a determinados padr\u00f5es ou est\u00edmulos. No estudo, treinaram-no para reconhecer diferentes vozes a partir de clips de \u00e1udio.<\/span><\/p>\n

Um dos aspectos mais not\u00e1veis do Brainware \u00e9 o facto de aprender e adaptar-se. Tal como um c\u00e9rebro humano melhora as suas tarefas com a pr\u00e1tica, o organoide melhora a sua capacidade de reconhecer vozes quanto mais for exposto a elas.\u00a0<\/span><\/p>\n

Isto aproxima-nos um pouco mais da cria\u00e7\u00e3o de uma IA que funcione mais como o c\u00e9rebro humano, que \u00e9 excecionalmente eficiente e n\u00e3o necessita de muita energia para funcionar (aproximadamente a de uma pequena l\u00e2mpada).<\/span><\/p>\n

No entanto, existem desafios. O crescimento destes organ\u00f3ides cerebrais \u00e9 complicado - s\u00e3o dif\u00edceis de criar, dif\u00edceis de replicar de forma consistente e n\u00e3o duram muito tempo, mas a equipa est\u00e1 a trabalhar em solu\u00e7\u00f5es.\u00a0<\/span><\/p>\n

Desempenho do Brainoware<\/span><\/h2>\n

Numa experi\u00eancia de reconhecimento de fala n\u00e3o supervisionada, os organ\u00f3ides foram treinados para distinguir uma \u00fanica voz a partir de 240 grava\u00e7\u00f5es \u00e1udio de oito indiv\u00edduos a emitir sons de vogais japonesas. Estes sons foram convertidos em sequ\u00eancias de sinais e padr\u00f5es espaciais para os organ\u00f3ides.<\/span><\/p>\n

Inicialmente, os organ\u00f3ides apresentavam uma taxa de precis\u00e3o de aproximadamente 30 a 40%, que melhorou para 70 a 80% ap\u00f3s dois dias de treino.\u00a0<\/span><\/p>\n

Mais informa\u00e7\u00f5es sobre o estudo<\/span><\/h2>\n

IA bio-inspirada<\/span><\/a> assume algumas formas diferentes, tais como <\/span>chips neurom\u00f3rficos<\/span><\/a> com base em neur\u00f3nios biol\u00f3gicos. Isto vai mais longe, criando uma arquitetura computacional a partir de organoides biol\u00f3gicos.\u00a0<\/span><\/p>\n

Eis mais pormenores sobre o seu funcionamento:<\/span><\/p>\n

    \n
  1. Hardware de IA bio-inspirado<\/b>: O estudo, publicado na revista Nature Electronics, apresenta o Brainoware, um novo hardware de IA que utiliza redes neuronais biol\u00f3gicas num organoide cerebral. Isto marca uma mudan\u00e7a fundamental em rela\u00e7\u00e3o aos chips de sil\u00edcio tradicionais inspirados no c\u00e9rebro, oferecendo uma emula\u00e7\u00e3o mais aut\u00eantica da fun\u00e7\u00e3o cerebral.<\/span><\/li>\n
  2. Estrutura e funcionalidade do Brainoware<\/b>: O Brainoware funciona atrav\u00e9s da interface entre um organoide cerebral, cultivado a partir de c\u00e9lulas estaminais pluripotentes humanas, e um conjunto de multielectrodos de alta densidade. Esta configura\u00e7\u00e3o permite tanto a transmiss\u00e3o de sinais el\u00e9ctricos ao organoide como a dete\u00e7\u00e3o de respostas neurais. O organoide apresenta propriedades como a din\u00e2mica n\u00e3o linear, a mem\u00f3ria e a capacidade de processar informa\u00e7\u00f5es espaciais.<\/span><\/li>\n
  3. Aplica\u00e7\u00f5es demonstradas no estudo<\/b>: A equipa aplicou com \u00eaxito o Brainoware em cen\u00e1rios pr\u00e1ticos, como o reconhecimento da fala e a previs\u00e3o de equa\u00e7\u00f5es ca\u00f3ticas n\u00e3o lineares (como o mapa de H\u00e9non). Isto mostra a capacidade do Brainoware para melhorar o seu desempenho computacional atrav\u00e9s de treino, real\u00e7ando o seu potencial para tarefas que requerem aprendizagem adaptativa.<\/span><\/li>\n
  4. Desafios e limita\u00e7\u00f5es<\/b>: Apesar da sua abordagem inovadora, o Brainoware enfrenta v\u00e1rios desafios t\u00e9cnicos, incluindo a gera\u00e7\u00e3o e manuten\u00e7\u00e3o de organoides cerebrais. Para al\u00e9m disso, a depend\u00eancia do hardware em rela\u00e7\u00e3o a equipamento perif\u00e9rico impede o seu potencial. Por outras palavras, \u00e9 necess\u00e1rio um grande n\u00famero de equipamentos de apoio para que os \u00f3rg\u00e3os cerebrais funcionem corretamente.\u00a0<\/span><\/li>\n
  5. Direc\u00e7\u00f5es futuras e potencialidades<\/b>: O estudo sugere que, com os avan\u00e7os no cultivo de organoides e a resolu\u00e7\u00e3o de problemas pr\u00e1ticos associados aos organoides, o Brainoware poder\u00e1 evoluir para um sistema mais eficiente e sofisticado. Isto poderia conduzir a um hardware de IA que imitasse mais de perto o funcionamento do c\u00e9rebro humano, reduzindo potencialmente o consumo de energia.<\/span><\/li>\n<\/ol>\n

    No futuro, estes tipos de sistemas de biocomputa\u00e7\u00e3o poder\u00e3o vir a realizar tarefas de IA com maior efici\u00eancia energ\u00e9tica do que os chips tradicionais baseados em sil\u00edcio.\u00a0<\/span><\/p>\n

    Os desenvolvimentos deste ano no dom\u00ednio da IA de inspira\u00e7\u00e3o biol\u00f3gica s\u00e3o muito promissores para ajudar a ind\u00fastria da IA a ultrapassar os limites da computa\u00e7\u00e3o de for\u00e7a bruta e a criar tecnologias energeticamente eficientes t\u00e3o elegantes como a natureza. <\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Aglomerados de c\u00e9lulas cerebrais humanas cultivadas em placas de Petri foram integradas em computadores para atingir um n\u00edvel fundamental de reconhecimento da fala. Feng Guo, da Universidade de Indiana Bloomington, explica o estudo, publicado na Nature Electronics: \"Esta \u00e9 uma demonstra\u00e7\u00e3o preliminar para mostrar a viabilidade do conceito. H\u00e1 ainda um caminho consider\u00e1vel a percorrer\". Guo aponta dois desafios principais da IA convencional que esta forma de IA biol\u00f3gica procura resolver: o elevado consumo de energia e as limita\u00e7\u00f5es inerentes aos chips de sil\u00edcio, como as suas fun\u00e7\u00f5es distintas de processamento e armazenamento de informa\u00e7\u00e3o. A equipa de Guo, juntamente com outras, como a australiana Cortical Labs,<\/p>","protected":false},"author":2,"featured_media":8195,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[350,203,101],"class_list":["post-8193","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-bio-inspired-ai","tag-biotech","tag-medtech"],"yoast_head":"\nResearchers perform AI speech recognition with human brain cells | DailyAI<\/title>\n<meta name=\"description\" content=\"Clusters of human brain cells cultivated in Petri dishes have been integrated with computers to achieve a fundamental level of speech recognition.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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