New York, May 2 (IANS) US scientists have developed a new artificial intelligence (AI) system that can translate a person's brain activity -- while listening to a story or silently imagining telling a story -- into a continuous stream of text.

The system, developed by a team at the University of Texas at Austin relies in part on a transformer model, similar to the ones that power Open AI's ChatGPT and Google's Bard.

It might help people who are mentally conscious yet unable to physically speak, such as those debilitated by strokes, to communicate intelligibly again, according to the team who published the study in the journal Nature Neuroscience.

Unlike other language decoding systems in development, this system called semantic decoder does not require subjects to have surgical implants, making the process noninvasive. Participants also do not need to use only words from a prescribed list.

Brain activity is measured using an functional MRI scanner after extensive training of the decoder, in which the individual listens to hours of podcasts in the scanner.

Later, provided that the participant is open to having their thoughts decoded, their listening to a new story or imagining telling a story allows the machine to generate corresponding text from brain activity alone.

"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," said Alex Huth, an assistant professor of neuroscience and computer science at UT Austin.

"We're getting the model to decode continuous language for extended periods of time with complicated ideas," he added.

The result is not a word-for-word transcript. Instead, researchers designed it to capture the gist of what is being said or thought, albeit imperfectly. About half the time, when the decoder has been trained to monitor a participant's brain activity, the machine produces text that closely (and sometimes precisely) matches the intended meanings of the original words.

For example, in experiments, a participant listening to a speaker say: "I don't have my driver's licence yeta had their thoughts translated as, "She has not even started to learn to drive yet."

The team also addressed questions about potential misuse of the technology in the study. The paper describes how decoding worked only with cooperative participants who had participated willingly in training the decoder.

Results for individuals on whom the decoder had not been trained were unintelligible, and if participants on whom the decoder had been trained later put up resistance -- for example, by thinking other thoughts -- results were similarly unusable.

"We take very seriously the concerns that it could be used for bad purposes and have worked to avoid that," said Jerry Tang, a doctoral student in computer science. "We want to make sure people only use these types of technologies when they want to and that it helps them."

In addition to having participants listen or think about stories, the researchers asked subjects to watch four short, silent videos while in the scanner. The semantic decoder was able to use their brain activity to accurately describe certain events from the videos.

The system currently is not practical for use outside of the laboratory because of its reliance on the time needed on an fMRI machine. But the researchers think this work could transfer to other, more portable brain-imaging systems, such as functional near-infrared spectroscopy (fNIRS).

New Delhi, March 30 (IANS) Google has denied the reports that it is copying Microsoft-owned OpenAI's ChatGPT to train its AI chatbot called Bard.

A report in The Information claimed that OpenAI's success "has forced the two AI research teams within Google's parent, Alphabet, to overcome years of intense rivalry to work together".

According to the report, citing sources, software engineers at Google's Brain AI group are working with employees at DeepMind, which is a sibling company within Alphabet to develop software to compete with OpenAI.

"Known internally as Gemini, the joint effort began in recent weeks, after Google stumbled with Bard, its first attempt to compete with OpenAI's chatbot," the report claimed.

However, a Google spokesperson told The Verge that "Bard is not trained on any data from ShareGPT or ChatGPT".

Meanwhile, Google has announced it is opening up access to its ChatGPT competitor "Bard" as an early experiment for users to collaborate with generative AI.

Early access to Bard has rolled out in the US and the UK, and the company said it will expand the access over time to more countries and languages.

Bard, like OpenAI's ChatGPT and Microsoft's Bing chatbot, is based on a large language model (LLM), specifically a lightweight and optimised version of LaMDA, which the tech giant said will be updated with newer, more capable models in the future.

Users can interact with Bard by asking questions and refining their responses with follow-up questions.