{"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\/es\/2023\/12\/researchers-perform-ai-speech-recognition-with-human-brain-cells\/","title":{"rendered":"Los investigadores reconocen el habla con inteligencia artificial a partir de c\u00e9lulas cerebrales humanas"},"content":{"rendered":"

Se han integrado grupos de c\u00e9lulas cerebrales humanas cultivadas en placas de Petri con ordenadores para lograr un nivel fundamental de reconocimiento del habla.<\/b><\/p>\n

Feng Guo, de la Universidad de Indiana Bloomington, explica el estudio, publicado en <\/span>Naturaleza Electr\u00f3nica<\/span><\/a>Se trata de una demostraci\u00f3n preliminar para demostrar la viabilidad del concepto. <\/span>A\u00fan queda mucho camino por recorrer\". <\/span><\/p>\n

Guo se\u00f1ala dos retos principales de la IA convencional que esta forma de IA biol\u00f3gica pretende resolver: el elevado consumo de energ\u00eda y las limitaciones inherentes a los chips de silicio, como sus distintas funciones de procesamiento y almacenamiento de informaci\u00f3n.<\/span><\/p>\n

El equipo de Guo, junto con otros, como el australiano Cortical Labs, que c\u00e9lulas cerebrales entrenadas para jugar al Pong en 2022<\/a>est\u00e1n explorando la bioinform\u00e1tica con c\u00e9lulas nerviosas vivas como posible soluci\u00f3n a estos retos.\u00a0<\/span><\/p>\n

Estos organoides cerebrales -cultivos de tejidos tridimensionales autoorganizados parecidos a minicerebros- surgen de c\u00e9lulas madre en condiciones de crecimiento espec\u00edficas.\u00a0<\/span><\/p>\n

Pueden crecer hasta unos pocos mil\u00edmetros de di\u00e1metro y contener hasta 100 millones de c\u00e9lulas nerviosas. En comparaci\u00f3n, un cerebro humano tiene aproximadamente 100.000 millones de c\u00e9lulas nerviosas. Los organoides se colocan sobre una gu\u00eda de microelectrodos que estimula el organoide y registra la actividad neuronal. El equipo de Guo denomina a esta configuraci\u00f3n \"Brainoware\".<\/span><\/p>\n

En esencia, Brainoware es una nueva forma de IA muy diferente de lo que solemos ver en ordenadores y smartphones. <\/span><\/p>\n

En lugar de utilizar chips normales, los investigadores han creado un peque\u00f1o grupo de c\u00e9lulas del cerebro humano<\/a> - el organoide cerebral. Este diminuto \"minicerebro\" se cultiva en un laboratorio a partir de c\u00e9lulas madre y puede realizar algunas tareas b\u00e1sicas que solemos asociar con la IA, como reconocer patrones del habla.<\/span><\/p>\n

\"\"
A) Diagrama del sistema \"Brainoware\", que muestra un organoide cerebral (un minicerebro cultivado en laboratorio) conectado a un dispositivo que registra y estimula su actividad el\u00e9ctrica. B) Imagen microsc\u00f3pica del organoide cerebral, te\u00f1ida para resaltar sus diferentes tipos celulares, como neuronas maduras, astrocitos, neuronas en fase inicial y c\u00e9lulas progenitoras, que muestra su compleja estructura tridimensional. Fuente: Naturaleza Electr\u00f3nica<\/a>.<\/figcaption><\/figure>\n

C\u00f3mo funciona<\/span><\/h2>\n

\u00a0El organoide cerebral se coloca en un dispositivo especial que puede enviar y leer se\u00f1ales el\u00e9ctricas. <\/span><\/p>\n

De este modo, los investigadores pueden comunicarse con el organoide, como ense\u00f1\u00e1ndole a responder a determinados patrones o entradas. En el estudio, lo entrenaron para reconocer distintas voces a partir de clips de audio.<\/span><\/p>\n

Uno de los aspectos m\u00e1s notables del Brainware es que aprende y se adapta. Al igual que un cerebro humano mejora en sus tareas con la pr\u00e1ctica, el organoide mejora su capacidad de reconocer voces cuanto m\u00e1s se expone a ellas.\u00a0<\/span><\/p>\n

Esto nos acerca un paso m\u00e1s a la creaci\u00f3n de una IA que funcione m\u00e1s como el cerebro humano, que es excepcionalmente eficiente y no necesita mucha energ\u00eda para funcionar (aproximadamente la de una bombilla peque\u00f1a).<\/span><\/p>\n

Sin embargo, existen dificultades. Cultivar estos organoides cerebrales es complicado: son dif\u00edciles de crear, de reproducir y no duran mucho, pero el equipo est\u00e1 buscando soluciones.\u00a0<\/span><\/p>\n

Rendimiento de Brainoware<\/span><\/h2>\n

En un experimento de reconocimiento del habla sin supervisi\u00f3n, se entren\u00f3 a los organoides para distinguir una sola voz a partir de 240 grabaciones de audio de ocho individuos que emit\u00edan sonidos voc\u00e1licos japoneses. Estos sonidos se convirtieron en secuencias de se\u00f1ales y patrones espaciales para los organoides.<\/span><\/p>\n

Inicialmente, los organoides mostraron una tasa de precisi\u00f3n de aproximadamente 30 a 40%, que mejor\u00f3 a 70 a 80% tras dos d\u00edas de entrenamiento.\u00a0<\/span><\/p>\n

M\u00e1s informaci\u00f3n sobre el estudio<\/span><\/h2>\n

IA bioinspirada<\/span><\/a> adopta diversas formas, como <\/span>chips neurom\u00f3rficos<\/span><\/a> basada en neuronas biol\u00f3gicas. Esto va un paso m\u00e1s all\u00e1 al crear una arquitectura computacional a partir de organoides biol\u00f3gicos.\u00a0<\/span><\/p>\n

Aqu\u00ed tienes m\u00e1s detalles sobre su funcionamiento:<\/span><\/p>\n

    \n
  1. Hardware de IA bioinspirado<\/b>: El estudio, publicado en Nature Electronics, presenta Brainoware, un novedoso hardware de IA que emplea redes neuronales biol\u00f3gicas dentro de un organoide cerebral. Esto supone un cambio fundamental respecto a los tradicionales chips de silicio inspirados en el cerebro, ya que ofrece una emulaci\u00f3n m\u00e1s aut\u00e9ntica de la funci\u00f3n cerebral.<\/span><\/li>\n
  2. Estructura y funcionalidad de Brainoware<\/b>: Brainoware funciona interconectando un organoide cerebral, cultivado a partir de c\u00e9lulas madre pluripotentes humanas, con una matriz multielectrodo de alta densidad. Esta configuraci\u00f3n permite tanto la transmisi\u00f3n de se\u00f1ales el\u00e9ctricas al organoide como la detecci\u00f3n de respuestas neuronales. El organoide presenta propiedades como din\u00e1mica no lineal, memoria y capacidad para procesar informaci\u00f3n espacial.<\/span><\/li>\n
  3. Aplicaciones demostradas en el estudio<\/b>: El equipo aplic\u00f3 con \u00e9xito Brainoware en escenarios pr\u00e1cticos, como el reconocimiento del habla y la predicci\u00f3n de ecuaciones ca\u00f3ticas no lineales (como el mapa de H\u00e9non). Esto demuestra la capacidad de Brainoware para mejorar su rendimiento inform\u00e1tico mediante el entrenamiento, lo que subraya su potencial para tareas que requieren un aprendizaje adaptativo.<\/span><\/li>\n
  4. Retos y limitaciones<\/b>: A pesar de su enfoque innovador, Brainoware se enfrenta a varios retos t\u00e9cnicos, como la generaci\u00f3n y el mantenimiento de organoides cerebrales. Adem\u00e1s, la dependencia del hardware de equipos perif\u00e9ricos merma su potencial. En otras palabras, necesita muchos equipos de apoyo para que los organoides cerebrales funcionen correctamente.\u00a0<\/span><\/li>\n
  5. Orientaciones futuras y potencial<\/b>: El estudio sugiere que, con los avances en el cultivo de organoides y la resoluci\u00f3n de los problemas pr\u00e1cticos asociados, Brainoware podr\u00eda evolucionar hasta convertirse en un sistema m\u00e1s eficiente y sofisticado. Esto podr\u00eda dar lugar a un hardware de IA que imitara m\u00e1s fielmente el funcionamiento del cerebro humano, lo que podr\u00eda reducir el consumo de energ\u00eda.<\/span><\/li>\n<\/ol>\n

    En el futuro, este tipo de sistemas bioinform\u00e1ticos podr\u00edan llegar a realizar tareas de IA con mayor eficiencia energ\u00e9tica que los chips tradicionales basados en silicio.\u00a0<\/span><\/p>\n

    Los avances en IA bioinspirada de este a\u00f1o son muy prometedores para ayudar a la industria de la IA a superar los l\u00edmites de la computaci\u00f3n de fuerza bruta y crear tecnolog\u00edas energ\u00e9ticamente eficientes tan elegantes como la naturaleza. <\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Grupos de c\u00e9lulas cerebrales humanas cultivadas en placas de Petri se han integrado con ordenadores para alcanzar un nivel fundamental de reconocimiento del habla. Feng Guo, de la Universidad de Indiana Bloomington, explica sobre el estudio, publicado en Nature Electronics: \"Se trata de una demostraci\u00f3n preliminar para mostrar la viabilidad del concepto. A\u00fan queda un largo camino por recorrer\". Guo se\u00f1ala dos retos principales de la IA convencional que esta forma de IA biol\u00f3gica pretende resolver: el elevado consumo de energ\u00eda y las limitaciones inherentes a los chips de silicio, como sus distintas funciones de procesamiento y almacenamiento de informaci\u00f3n. El equipo de Guo, junto con otros, como el australiano 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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