{"id":4374,"date":"2024-08-19T15:17:38","date_gmt":"2024-08-19T18:17:38","guid":{"rendered":"https:\/\/matrixgo.ai\/alucinacoes-ia-como-evitar\/"},"modified":"2024-08-19T15:17:38","modified_gmt":"2024-08-19T18:17:38","slug":"alucinacoes-ia-como-evitar","status":"publish","type":"post","link":"https:\/\/matrixgo.ai\/en\/alucinacoes-ia-como-evitar\/","title":{"rendered":"AI hallucinations? What are they? And how can they be avoided?"},"content":{"rendered":"<p>Have you noticed any <strong>Artificial Intelligence hallucination<\/strong>? The concept may seem confusing and generate doubt, but you have most likely already <strong>interacted with a chatbot<\/strong> or even <strong>with a generative AI engine<\/strong> and <strong>got an answer completely outside of what was asked\/requested<\/strong>. Or worse, he wholeheartedly believed in false information created by AI. Yes, <strong>Artificial Intelligence hallucinates<\/strong>, and often produces situations that pose challenges for users and developers. Learn more about hallucinations and how to avoid them below.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Hallucinations<\/strong><\/h2>\n\n\n\n<p>First of all, it is necessary to emphasize that <strong>there is no scientific consensus on the use of the term \u201challucinations\u201d<\/strong> to describe such a phenomenon. Some scholars and experts say <strong>not being able to credit something too human<\/strong>, like a hallucination, to a <strong>machine that has no consciousness<\/strong>The statement makes sense, but the term has become popular among the community as a whole because it clearly exemplifies this \u201cconfusion\u201d of AI.<\/p>\n\n\n\n<p>Conceptually, <strong>Hallucinations are incorrect or misleading results generated by AI. These errors can be caused by a variety of factors, including insufficient training data, incorrect assumptions made by the model, and\/or biases in the data used to train the model.<\/strong>.<\/p>\n\n\n\n<p>Some developers, however, try to play <strong>the blame for hallucinations on the users&#039; lap<\/strong>; according to them, imprecise, generic, and confusing questions and\/or instructions generate inadequate results. In theory, <strong>AI is only as good as the pilot operating it<\/strong>. It makes sense, but the point is that hallucinations appear even when the input data is structured and accurate.<\/p>\n\n\n\n<p>And that&#039;s where the danger lies. Think, for example, of <strong>AIs trained to make important decisions, such as medical diagnoses or financial negotiations<\/strong> \u2013 the impact of errors generated by AI in these contexts is gigantic.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>How do Hallucinations occur?<\/strong><\/h2>\n\n\n\n<p>You <strong>AI engines are trained on data and learn to make predictions by finding patterns in the data<\/strong>. It turns out that the accuracy of these predictions depends on the <strong>quality and integrity of training data<\/strong>.<\/p>\n\n\n\n<p>This is precisely the number one factor that reduces the quality and accuracy of AI responses. <strong>If the training data is biased, flawed, or incomplete, the AI model will only learn incorrect patterns.<\/strong>, generating inaccurate predictions and hallucinations.<\/p>\n\n\n\n<p>That&#039;s why it&#039;s so important that <strong>when developing a chatbot and\/or integrating a generative AI engine into an internal or external flow, companies must perform extensive data mining and curation<\/strong>, so that they can <strong>feed the Artificial Intelligence engines with quality<\/strong>This is precisely the biggest challenge facing companies today.<\/p>\n\n\n\n<p>However, it&#039;s not just faulty training data that leads to hallucinations. <strong>Lack of adequate foundation is another factor to consider.<\/strong>. You <strong>AI models may have difficulty accurately understanding real-world knowledge, physical and natural properties, and factual information<\/strong>And when this foundation is missing, the model generates outputs that it considers plausible, even though they may be incorrect, untrue, or even meaningless.<\/p>\n\n\n\n<p>It&#039;s not uncommon to discover that AI has invented something that doesn&#039;t exist, fabricated dates, and\/or created events. This is quite dangerous.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Examples of AI Hallucinations<\/strong><\/h2>\n\n\n\n<p>Hallucinations can take many forms. But in general, <strong>involve 3 contexts<\/strong>:<\/p>\n\n\n\n<p><strong>Incorrect predictions:<\/strong> the AI model can predict that an event will occur based on its training data, even if it is completely unlikely.<\/p>\n\n\n\n<p><strong>False positives:<\/strong> The AI model may mistakenly identify something as a threat. Consider, for example, a fraud detection model that flags a legitimate transaction as fraudulent.<\/p>\n\n\n\n<p><strong>False negatives: <\/strong>\u00a0the AI model fails to identify\/select something it should, missing it; a serious risk, for example, in medical diagnostics.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>How to avoid hallucinations?<\/strong><\/h2>\n\n\n\n<p>The question that won&#039;t go away: <strong>Is there a cure for these hallucinations?<\/strong><\/p>\n\n\n\n<p>In short: yes! <strong>But there is no \u201csilver bullet\u201d or something that will completely eliminate<\/strong> any possibility of AI error. Some ways to control hallucinations:<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Limit the possible outcomes<\/strong><\/h3>\n\n\n\n<p>When training AI engines it is <strong>important to limit the number of possible outcomes that the model can predict<\/strong>. Something like \u201cby limits\u201d in generating results. This can be done through a technique known as <strong>Regularization<\/strong>. Regularization <strong>penalizes the AI model for making overly extreme predictions<\/strong>, which helps generate responses, preventing Artificial Intelligence from \u201cgoing off on a tangent\u201d.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Train AI only with relevant and specific sources<\/strong><\/h3>\n\n\n\n<p>It&#039;s quite a lot <strong>tempting to feed AI with all the data on the internet<\/strong>, empowering it to respond and interact in a near-omniscient manner. In fact, this can work for some businesses.<\/p>\n\n\n\n<p>However, <strong>the variety and abundance of data can (and should) generate inaccuracies<\/strong> in the results.<\/p>\n\n\n\n<p>For AI models that require extremely high precision and\/or whose incorrect results can have crucial impacts on people&#039;s lives, it is <strong>advisable to use only data relevant to the task the model will perform<\/strong>For example, if AI is used for specific medical diagnoses, use only medical data and images.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Create a model for the AI to follow<\/strong><\/h3>\n\n\n\n<p>When training an Artificial Intelligence engine it is highly <strong>advisable to create standards for the model to follow<\/strong>. By \u201cstandards\u201d, understand <strong>unify information and present it in an orderly manner<\/strong> (with topics, numbers, connections). Learning is faster and the risk of inappropriate associations is lower.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Tell AI what you don&#039;t want<\/strong><\/h3>\n\n\n\n<p>When training the AI model it is also <strong>preponderant to tell her what you don&#039;t want her to generate<\/strong>. \u201cSet limits\u201d on this technology. For example, <strong>a company&#039;s generative AI chatbot should under no circumstances direct the user to the competitor<\/strong>.<\/p>\n\n\n\n<p><strong>Guardrails<\/strong>, or protective grids (in literal translation), <strong>It is precisely the system and\/or practice of including mechanisms so that the AI engine does not generate discriminatory, unethical or illegal results.<\/strong>. And more: that he <strong>ensure data privacy and confidentiality<\/strong> both the company and the users.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Hallucination-Free AI?<\/strong><\/h2>\n\n\n\n<p><strong>Will we have an AI without hallucinations?<\/strong> Get correct and reliable 100% responses to the input data?<\/p>\n\n\n\n<p>As said, <strong>everything depends on the integrity of the training data, the limitations of the results and the limits imposed on this generation<\/strong>Experts on the subject agree that we created a monster (generative AI) and now we are trying to tame it \u2013 a Herculean task, but one that has been producing satisfactory results in certain businesses and segments.<\/p>\n\n\n\n<p><strong>READ ALSO: <a href=\"https:\/\/matrixgo.ai\/o-que-e-llm\/\">\u201cWhat is LLM? What does your business have to do with it?\u201d<\/a><\/strong><\/p>\n\n\n\n<p><strong>READ ALSO: <a href=\"https:\/\/matrixgo.ai\/aplicacoes-praticas-chatgpt-diferentes-setores\/\">\u201cPractical applications of ChatGPT in different sectors\u201d<\/a><\/strong><\/p>","protected":false},"excerpt":{"rendered":"<p>AI is crazy! Generating lies and unintelligible messages. They&#039;re hallucinations\u2026<\/p>","protected":false},"author":24,"featured_media":4375,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","_joinchat":[],"footnotes":""},"categories":[41,389,408,364,39,373],"tags":[70,537,65,194,439,155,67,217,422,72,538,404,539],"class_list":["post-4374","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-atendimento","category-chatbot","category-chatbots-ia","category-chatgpt","category-inteligencia-artificial","category-tecnologia","tag-ai","tag-alucinacoes","tag-atendimento","tag-bots","tag-chat-gpt","tag-chatbot","tag-chatbots","tag-ia","tag-ia-generativa","tag-inteligencia-artificial","tag-llm","tag-matrix-go","tag-vieses"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Alucina\u00e7\u00f5es de IA? 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