{"id":6851,"date":"2023-10-27T19:21:39","date_gmt":"2023-10-27T19:21:39","guid":{"rendered":"https:\/\/dailyai.com\/?p=6851"},"modified":"2023-10-27T22:55:24","modified_gmt":"2023-10-27T22:55:24","slug":"ai-subjected-to-tests-on-theory-of-mind-and-systematic-generalization","status":"publish","type":"post","link":"https:\/\/dailyai.com\/pt\/2023\/10\/ai-subjected-to-tests-on-theory-of-mind-and-systematic-generalization\/","title":{"rendered":"IA sujeita a testes sobre a Teoria da Mente e a generaliza\u00e7\u00e3o sistem\u00e1tica"},"content":{"rendered":"

Os investigadores introduziram o FANToM, um novo par\u00e2metro de refer\u00eancia concebido para testar e avaliar rigorosamente a compreens\u00e3o e a aplica\u00e7\u00e3o da Teoria da Mente (ToM) pelos modelos de linguagem de grande dimens\u00e3o (LLM).<\/b><\/p>\n

A teoria da mente refere-se \u00e0 capacidade de atribuir cren\u00e7as, desejos e conhecimentos a si pr\u00f3prio e aos outros, e de compreender que os outros t\u00eam cren\u00e7as e perspectivas diferentes das suas.\u00a0<\/span><\/p>\n

A ToM \u00e9 vista como fundamental para a consci\u00eancia dos animais inteligentes. Para al\u00e9m dos humanos, considera-se que primatas como os orangotangos, os gorilas e os chimpanz\u00e9s t\u00eam ToM, bem como alguns animais n\u00e3o primatas, como os papagaios e os membros da fam\u00edlia dos corvos.\u00a0<\/span><\/p>\n

\u00c0 medida que os modelos de IA se tornam mais complexos, os investigadores de IA procuram novos m\u00e9todos de avalia\u00e7\u00e3o de capacidades como a ToM.<\/span><\/p>\n

Um novo marco de refer\u00eancia chamado FANToM<\/span><\/a>criado por investigadores do Allen Institute for AI, da Universidade de Washington, da Universidade Carnegie Mellon e da Universidade Nacional de Seul, submete os modelos de aprendizagem autom\u00e1tica a cen\u00e1rios din\u00e2micos que reflectem as interac\u00e7\u00f5es da vida real.\u00a0<\/span><\/p>\n

Com o FANToM, as personagens entram e saem de conversas, desafiando os modelos de IA a manter uma compreens\u00e3o exacta de quem sabe o qu\u00ea num dado momento.<\/span><\/p>\n

A submiss\u00e3o de grandes modelos lingu\u00edsticos (LLMs) ao FANToM revelou que mesmo os modelos mais avan\u00e7ados t\u00eam dificuldade em manter uma ToM consistente.\u00a0<\/span><\/p>\n

O desempenho dos modelos foi significativamente inferior ao dos participantes humanos, salientando as limita\u00e7\u00f5es da IA na compreens\u00e3o e navega\u00e7\u00e3o em interac\u00e7\u00f5es sociais complexas.\u00a0<\/span><\/p>\n

De facto, os humanos dominaram todas as categorias, como se pode ver abaixo.\u00a0<\/span><\/p>\n

\"AI
Os humanos foram muito superiores na resposta a perguntas relacionadas com o ToM em compara\u00e7\u00e3o com os LLMs populares. Fonte: FANToM<\/a>.<\/figcaption><\/figure>\n

Um aspeto interessante \u00e9 o facto de a vers\u00e3o de outubro da itera\u00e7\u00e3o do modelo GPT-4 ter sido ultrapassada por uma vers\u00e3o anterior de junho, o que poder\u00e1 confirmar as recentes hist\u00f3rias de utilizadores que afirmam que <\/span>ChatGPT est\u00e1 a piorar<\/span><\/a>.\u00a0<\/span><\/p>\n

O FANToM tamb\u00e9m revelou t\u00e9cnicas para melhorar a ToM da LLM, como o racioc\u00ednio em cadeia e outros m\u00e9todos de afina\u00e7\u00e3o. <\/span><\/p>\n

No entanto, o fosso entre as compet\u00eancias de ToM da IA e dos humanos continua a ser elevado.\u00a0<\/span><\/p>\n

A IA aproxima-se de compet\u00eancias lingu\u00edsticas semelhantes \u00e0s humanas<\/span><\/h2>\n

Num caso um pouco relacionado mas distinto <\/span>estudo publicado na Nature<\/span><\/a>, os cientistas desenvolveram uma rede neuronal capaz de generalizar uma linguagem semelhante \u00e0 humana.\u00a0<\/span><\/p>\n

Esta nova rede neuronal demonstrou uma capacidade impressionante de integrar palavras recentemente aprendidas no seu vocabul\u00e1rio existente. Podia ent\u00e3o utilizar essas palavras em v\u00e1rios contextos, uma capacidade cognitiva conhecida como generaliza\u00e7\u00e3o sistem\u00e1tica.\u00a0<\/span><\/p>\n

Os seres humanos exibem naturalmente uma generaliza\u00e7\u00e3o sistem\u00e1tica, incorporando sem problemas novo vocabul\u00e1rio no seu repert\u00f3rio.\u00a0<\/span><\/p>\n

Por exemplo, quando algu\u00e9m aprende o termo \"photobomb\", pode aplic\u00e1-lo em v\u00e1rias situa\u00e7\u00f5es quase imediatamente. Est\u00e3o sempre a surgir novas g\u00edrias e os seres humanos absorvem-nas naturalmente no seu vocabul\u00e1rio.\u00a0<\/span><\/p>\n

Os investigadores submeteram a sua pr\u00f3pria rede neural personalizada e o ChatGPT a uma s\u00e9rie de testes, descobrindo que o ChatGPT ficou atr\u00e1s do modelo personalizado em termos de desempenho.<\/span><\/p>\n

Embora os LLMs como o ChatGPT sejam excelentes em muitos cen\u00e1rios de conversa\u00e7\u00e3o, apresentam inconsist\u00eancias e lacunas vis\u00edveis noutros, um problema que esta nova rede neural resolve.<\/span><\/p>\n

Para investigar este aspeto da comunica\u00e7\u00e3o lingu\u00edstica, os investigadores realizaram uma experi\u00eancia com 25 participantes humanos, avaliando a sua capacidade de aplicar palavras recentemente aprendidas em diferentes contextos. <\/span>Os sujeitos foram apresentados a uma pseudo-linguagem constitu\u00edda por palavras sem sentido que representam v\u00e1rias ac\u00e7\u00f5es e regras.\u00a0<\/span><\/p>\n

Ap\u00f3s uma fase de treino, os participantes destacaram-se na aplica\u00e7\u00e3o destas regras abstractas a novas situa\u00e7\u00f5es, demonstrando uma generaliza\u00e7\u00e3o sistem\u00e1tica.<\/span><\/p>\n

Quando a rede neural recentemente desenvolvida foi exposta a esta tarefa, reflectiu o desempenho humano. <\/span>No entanto, quando o ChatGPT foi sujeito ao mesmo desafio, teve dificuldades significativas, falhando entre 42 e 86% do tempo, dependendo da tarefa espec\u00edfica.<\/span><\/p>\n

Este facto \u00e9 significativo por duas raz\u00f5es. Em primeiro lugar, pode dizer-se que esta nova rede neuronal superou efetivamente o GPT-4 nesta tarefa espec\u00edfica - o que j\u00e1 \u00e9 suficientemente impressionante. Em segundo lugar, este estudo exp\u00f5e novos m\u00e9todos para ensinar modelos de IA a generalizar uma nova linguagem como os humanos.\u00a0<\/span><\/p>\n

Como Elia Bruni, especialista em processamento de linguagem natural na Universidade de Osnabr\u00fcck, na Alemanha, descreve, \"Infundir sistematicidade nas redes neuronais \u00e9 um grande neg\u00f3cio\".<\/span><\/p>\n

Em conjunto, estes dois estudos oferecem novas abordagens para o treino de modelos de IA mais inteligentes, capazes de rivalizar com os humanos em \u00e1reas cr\u00edticas como a lingu\u00edstica e a Teoria da Mente. <\/span><\/p>","protected":false},"excerpt":{"rendered":"

Os investigadores introduziram o FANToM, um novo par\u00e2metro de refer\u00eancia concebido para testar e avaliar rigorosamente a compreens\u00e3o e a aplica\u00e7\u00e3o da Teoria da Mente (ToM) por parte dos grandes modelos lingu\u00edsticos (LLM). A Teoria da Mente refere-se \u00e0 capacidade de atribuir cren\u00e7as, desejos e conhecimentos a si pr\u00f3prio e aos outros, e de compreender que os outros t\u00eam cren\u00e7as e perspectivas diferentes das suas. A ToM \u00e9 vista como fundamental para a consci\u00eancia dos animais inteligentes. Para al\u00e9m dos seres humanos, considera-se que primatas como os orangotangos, os gorilas e os chimpanz\u00e9s t\u00eam ToM, bem como alguns animais n\u00e3o primatas, como os papagaios e os membros da fam\u00edlia dos corvos. Como modelos de IA<\/p>","protected":false},"author":2,"featured_media":6853,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[404,115,105,93],"class_list":["post-6851","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-agi","tag-chatgpt","tag-machine-learning","tag-openai"],"yoast_head":"\nAI subjected to tests on Theory of Mind and systematic generalization | DailyAI<\/title>\n<meta name=\"description\" content=\"Researchers have introduced FANToM, a novel benchmark designed to rigorously test and evaluate large language models\u2019 (LLMs) understanding and application of Theory of Mind (ToM).\" \/>\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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