A team of scientists from the University of Texas at Austin has developed an AI model that can read your thoughts. (Image: Pixabay)
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Can AI read your mind? Scientists use ChatGPT-like tech to turn people’s thoughts into text in real-time
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It’s 2023, and the world is rapidly drifting away from traditionally known methods of dream interpretation. With the advent of artificial intelligence newer methods of reading the human mind are at play. In March, it was reported that Japanese scientists recreated high-resolution images from scans of brain activity using stable diffusion, now it seems there is another breakthrough in the offing.
A team of scientists from the University of Texas at Austin has developed an AI model that can read your thoughts. The noninvasive AI system known as semantic decoder lays emphasis on translating brain activity into a stream of texts according to the peer-reviewed study published in the journal Nature Neuroscience.
The research was led by Jerry Tang, a doctoral student in computer science; Alex Huth, an assistant professor of neuroscience and computer science at UT Austin. The study conducted by Tang and Huth is based partly on a transformer model which is similar to the one that powers Google Bard and OpenAI’s ChatGPT.
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With their latest innovation, scientists are hopeful that it can be of assistance to people with paralysis or some form of disability. The newly developed tech is essentially an AI-based decoder that can translate brain activities into a stream of text. This means now AI will allow a person’s thoughts to be read in a non-invasive way, something that has never been attempted in the history of neuroscience or medical science in general.
As part of the study, three people were assigned to MRI machines and were asked to listen to stories. In what can be called a major breakthrough, scientists claim that they produced the text of the participants’ thoughts without the help of any brain implant. It is to be noted that the mind-reading technology captured the main points of their thoughts and did not exactly replicate their thoughts in their entirety.
“For a noninvasive method, this is a real leap forward compared to what’s been done before, which is typically single words or short sentences. We’re getting the model to decode continuous language for extended periods of time with complicated ideas,” Huth was quoted as saying in a report published on the UT Texas website.
According to scientists, the AI system can generate a stream of text when a participant listens to or imagines a story. This according to the researchers is possible once the AI system is fully trained. Researchers essentially deployed a technology like ChatGPT to interpret the thoughts of people while they were watching silent films or when they imagined themselves to be telling a story. The new study has also raised concerns about mental privacy.
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Apart from Tang and Huth, Amanda LeBel a former research assistant at the Huth Lab and Shailee Jain, a computer science graduate at UT Austin, are co-authors of the study.
As an AI enthusiast with a deep understanding of the field, I find the recent development from the University of Texas at Austin truly remarkable. The team's creation of an AI model, named the semantic decoder, capable of reading thoughts by translating brain activity into text represents a significant leap forward in the intersection of neuroscience and artificial intelligence.
The technology's noninvasive nature is particularly noteworthy, as it opens up possibilities for assisting individuals with paralysis or disabilities. This innovative AI decoder, as outlined in the peer-reviewed study published in Nature Neuroscience, has the potential to revolutionize our approach to understanding and interpreting human thoughts without the need for invasive procedures or brain implants.
The research, led by Jerry Tang, a doctoral student in computer science, and Alex Huth, an assistant professor of neuroscience and computer science at UT Austin, draws on the advancements in transformer models. These models, similar to those powering Google Bard and OpenAI's ChatGPT, have proven instrumental in decoding brain activity.
In their study, the scientists utilized MRI machines to analyze brain activity as participants listened to stories. The AI system, akin to ChatGPT but tailored for decoding brain signals, translated this activity into a stream of text, marking a significant departure from previous attempts that typically captured single words or short sentences. This breakthrough is notable for its ability to decode continuous language for extended periods with complex ideas, according to Huth.
The process involved deploying technology similar to ChatGPT to interpret thoughts while participants watched silent films or imagined telling a story. The researchers demonstrated that the AI system could generate coherent text, capturing the main points of participants' thoughts without relying on brain implants.
This development also raises important ethical considerations regarding mental privacy, as the capability to translate thoughts into text becomes increasingly sophisticated. As technology continues to advance in this realm, it prompts discussions about the potential implications for individuals' privacy and the need for ethical guidelines in the development and application of such mind-reading technologies.
In conclusion, the University of Texas at Austin's AI breakthrough showcases the power of combining neuroscience and transformer models to create a noninvasive AI decoder capable of translating brain activity into text. This development holds promise for assisting individuals with disabilities and opens up new frontiers in our understanding of the human mind.
