{"id":3448,"date":"2023-05-02T14:17:03","date_gmt":"2023-05-02T19:17:03","guid":{"rendered":"https:\/\/www.unmc.edu\/healthsecurity\/transmission\/?p=3448"},"modified":"2023-05-02T14:17:06","modified_gmt":"2023-05-02T19:17:06","slug":"scientists-use-gpt-ai-to-passively-read-peoples-thoughts-in-breakthrough","status":"publish","type":"post","link":"https:\/\/www.unmc.edu\/healthsecurity\/transmission\/2023\/05\/02\/scientists-use-gpt-ai-to-passively-read-peoples-thoughts-in-breakthrough\/","title":{"rendered":"Scientists Use GPT AI to Passively Read People’s Thoughts in Breakthrough"},"content":{"rendered":"
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Vice<\/a> <\/p>\n\n\n\n

Scientists have invented a language decoder that can translate a person\u2019s thoughts into text using an artificial intelligence (AI) transformer similar to ChatGPT, reports a new study. <\/p>\n\n\n\n

The breakthrough marks the first time that continuous language has been non-invasively reconstructed from human brain activities, which are read through a functional magnetic resonance imaging (fMRI) machine.\u00a0<\/p>\n\n\n\n

The decoder was able to interpret the gist of stories that human subjects watched or listened to\u2014or even simply imagined\u2014using fMRI brain patterns, an achievement that essentially allows it to read peoples\u2019 minds with unprecedented efficacy. While this technology is still in its early stages, scientists hope it might one day help people with neurological conditions that affect speech to clearly communicate with the outside world.<\/p>\n\n\n\n

However, the team that made the decoder also warned that brain-reading platforms could eventually have nefarious applications, including as a means of surveillance for governments and employers. Though the researchers emphasized that their decoder requires the cooperation of human subjects to work, they argued that \u201cbrain\u2013computer interfaces should respect mental privacy,\u201d according to a study published on Monday<\/a> in Nature Neuroscience<\/em>.<\/p>\n\n\n\n

\u201cCurrently, language-decoding is done using implanted devices that require neurosurgery, and our study is the first to decode continuous language, meaning more than full words or sentences, from non-invasive brain recordings, which we collect using functional MRI,\u201d said Jerry Tang, a graduate student in computer science at the University of Texas at Austin who led the study, in a press briefing held last Thursday. \u201cThe goal of language-decoding is to take recordings of a user’s brain activity and predict the words that the user was hearing or saying or imagining,\u201d he noted. \u201cEventually, we hope that this technology can help people who have lost the ability to speak due to injuries like strokes, or diseases like ALS.\u201d<\/p>\n\n\n\n

Continue reading<\/a><\/p>\n<\/a><\/div><\/div>","protected":false},"excerpt":{"rendered":"

Vice Scientists have invented a language decoder that can translate a person\u2019s thoughts into text using an artificial intelligence (AI) transformer similar to ChatGPT, reports a new study.  The breakthrough marks the first time that continuous language has been non-invasively reconstructed from human brain activities, which are read through a functional magnetic resonance imaging (fMRI) […]<\/p>\n","protected":false},"author":11,"featured_media":3449,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":false,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[18],"tags":[],"class_list":["post-3448","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-coping-with-covid"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/www.unmc.edu\/healthsecurity\/transmission\/wp-content\/uploads\/2023\/05\/wut.webp","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.unmc.edu\/healthsecurity\/transmission\/wp-json\/wp\/v2\/posts\/3448","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.unmc.edu\/healthsecurity\/transmission\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.unmc.edu\/healthsecurity\/transmission\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.unmc.edu\/healthsecurity\/transmission\/wp-json\/wp\/v2\/users\/11"}],"replies":[{"embeddable":true,"href":"https:\/\/www.unmc.edu\/healthsecurity\/transmission\/wp-json\/wp\/v2\/comments?post=3448"}],"version-history":[{"count":1,"href":"https:\/\/www.unmc.edu\/healthsecurity\/transmission\/wp-json\/wp\/v2\/posts\/3448\/revisions"}],"predecessor-version":[{"id":3450,"href":"https:\/\/www.unmc.edu\/healthsecurity\/transmission\/wp-json\/wp\/v2\/posts\/3448\/revisions\/3450"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.unmc.edu\/healthsecurity\/transmission\/wp-json\/wp\/v2\/media\/3449"}],"wp:attachment":[{"href":"https:\/\/www.unmc.edu\/healthsecurity\/transmission\/wp-json\/wp\/v2\/media?parent=3448"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.unmc.edu\/healthsecurity\/transmission\/wp-json\/wp\/v2\/categories?post=3448"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.unmc.edu\/healthsecurity\/transmission\/wp-json\/wp\/v2\/tags?post=3448"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}