{"id":27202,"date":"2023-09-12T20:06:18","date_gmt":"2023-09-12T18:06:18","guid":{"rendered":"https:\/\/sendapp.live\/?p=27202"},"modified":"2024-11-19T11:47:21","modified_gmt":"2024-11-19T10:47:21","slug":"sindrome-da-inteligencia-artificial-e-da-vaca-louca","status":"publish","type":"post","link":"https:\/\/sendapp.live\/pt\/2023\/09\/12\/intelligenza-artificiale-e-sindrome-della-mucca-pazza\/","title":{"rendered":"\u00a0Intelig\u00eancia Artificial e \u201cS\u00edndrome da Vaca Louca\u201d\u00a0"},"content":{"rendered":"

Intelig\u00eancia artificial<\/a> E "S\u00edndrome da Vaca Louca<\/a>"<\/p>\n

A intelig\u00eancia artificial (IA) enfrenta uma nova crise, desta vez interna. Um estudo recente realizado por pesquisadores da Rice e da Universidade de Stanford indica que o uso intenso de dados sint\u00e9ticos para treinar modelos de IA pode levar a s\u00e9rios problemas. Esta tend\u00eancia preocupante tem sido chamada de \u201cTranstorno de Autofagia Modelo\u201d ou MAD, um termo alarmante por um bom motivo.<\/p>\n

\"\"<\/p>\n

O que \u00e9 um conjunto de dados sint\u00e9tico?<\/h2>\n

Antes de mergulhar nos detalhes, \u00e9 crucial entender o que s\u00e3o conjuntos de dados sint\u00e9ticos. S\u00e3o conjuntos de dados gerados artificialmente, em vez de coletados no mundo real. Esses conjuntos de dados s\u00e3o usados para treinar modelos de aprendizado de m\u00e1quina e incluem dados que v\u00e3o desde textos e imagens gerados por algoritmos at\u00e9 dados financeiros simulados. A sua atratividade reside principalmente na sua disponibilidade, baixo custo e aus\u00eancia de problemas de privacidade.<\/p>\n

As vantagens dos conjuntos de dados sint\u00e9ticos<\/h2>\n

O poder dos dados sint\u00e9ticos reside na sua versatilidade e facilidade de uso. Eles n\u00e3o exigem coleta manual, evitam quest\u00f5es legais de privacidade e podem ser criados em volumes quase infinitos. A empresa de consultoria Gartner prev\u00ea que, at\u00e9 2030, esses conjuntos de dados substituir\u00e3o dados reais em muitas \u00e1reas de aplica\u00e7\u00e3o de IA.<\/p>\n

A s\u00edndrome da \u201cvaca louca\u201d no aprendizado de m\u00e1quina<\/h2>\n

Mas h\u00e1 um lado negro. O estudo mencionado acima fala sobre um fen\u00f4meno compar\u00e1vel ao overfitting no aprendizado de m\u00e1quina, conhecido como \u201cTranstorno de Autofagia Modelo\u201d (MAD). Este termo t\u00e9cnico descreve uma desordem em que um modelo de IA come\u00e7a a diminuir o seu desempenho com o uso cont\u00ednuo de dados sint\u00e9ticos. Ou seja, a IA come\u00e7a a \u201cenlouquecer\u201d.<\/p>\n

Causas e consequ\u00eancias do MAD<\/h2>\n

O problema parece surgir da falta de diversidade nos dados sint\u00e9ticos. Quando um modelo de IA \u00e9 treinado com um conjunto de dados demasiado homog\u00e9neo, come\u00e7a a sobrepor-se num ciclo destrutivo. Este fen\u00f4meno foi descrito como \u201cautof\u00e1gico\u201d, dando origem ao termo MAD.<\/p>\n

Solu\u00e7\u00f5es propostas e considera\u00e7\u00f5es futuras<\/h2>\n

Nem tudo est\u00e1 perdido, no entanto. Os pesquisadores sugerem que a incorpora\u00e7\u00e3o de dados reais no ciclo de treinamento poderia prevenir esse tipo de eros\u00e3o do modelo. E \u00e0 medida que a comunidade cient\u00edfica explora solu\u00e7\u00f5es, \u00e9 essencial que os criadores de IA estejam conscientes desta potencial armadilha.<\/p>\n

Conjuntos de dados sint\u00e9ticos: uma faca de dois gumes?<\/h2>\n

Em conclus\u00e3o, embora os conjuntos de dados sint\u00e9ticos ofere\u00e7am vantagens indubit\u00e1veis em termos de custo, efici\u00eancia e privacidade, trazem consigo riscos novos e inesperados. Christian Intern\u00f2, pesquisador na \u00e1rea de aprendizado de m\u00e1quina, resume perfeitamente o dilema: \u201cOs dados sint\u00e9ticos s\u00e3o o futuro, mas precisamos aprender como gerenci\u00e1-los\u201d. Com os olhos fixos no futuro, a comunidade de IA deve equilibrar os riscos e recompensas desta fronteira emergente de dados.<\/p>","protected":false},"excerpt":{"rendered":"

Intelig\u00eancia Artificial e a "Doen\u00e7a da Vaca Louca" A intelig\u00eancia artificial (IA) enfrenta uma nova crise, desta vez interna. Um estudo recente realizado por pesquisadores da Rice e\u2026<\/p>","protected":false},"author":22,"featured_media":27206,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_daim_seo_power":"","_daim_enable_ail":"","footnotes":""},"categories":[2538],"tags":[],"class_list":{"0":"post-27202","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-news"},"yoast_head":"\n\u00a0Intelligenza Artificiale e \u201cSindrome Della Mucca Pazza\u201d\u00a0<\/title>\n<meta name=\"description\" content=\"Intelligenza Artificiale e \u201cSindrome Della Mucca Pazza\u201d\u00a0L'intelligenza artificiale (IA) sta affrontando una nuova crisi...\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sendapp.live\/pt\/2023\/09\/12\/sindrome-da-inteligencia-artificial-e-da-vaca-louca\/\" 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