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In a world-first, researchers from the GrapheneX-UTS Human-centric Artificial Intelligence Centre at the University of Technology Sydney (UTS) have developed a portable, non-invasive system that can decode silent thoughts and turn them into text.

The technology could aid communication for people who are unable to speak due to illness or injury, including stroke or paralysis. It could also enable seamless communication between humans and machines, such as the operation of a bionic arm or robot.

The study has been selected as the spotlight paper at the NeurIPS conference, an annual meeting that showcases world-leading research on artificial intelligence and machine learning, held in New Orleans on 12 December 2023.

Scientists have fused human brain tissue to a computer chip, creating a mini cyborg in a petri dish that can perform math equations and recognize speech.

Dubbed Brainoware, the system consists of brain cells artificially grown from human stem cells, which have been fostered to develop into a brain-like tissue. This mini-brain organoid is then hooked up to traditional hardware where it acts as a physical reservoir that can capture and remember the information it receives from the computer inputs.

The researchers wanted to explore the idea of exploiting the efficiency of the human brain’s architecture to supercharge computational hardware. The rise of artificial intelligence (AI) has massively increased the demand for computing power, but it’s somewhat limited by the energy efficiency and performance of the standard silicon chips.

A nonintrusive human-machine interface for controlling extra arms was tested using a neurorobotic platform.

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Researchers from the Human-centric Artificial Intelligence Centre at the University of Technology Sydney have developed a portable, non-invasive system that can turn silent thoughts into text.

Continue reading “Revolutionary Mind-Reading AI System” »

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In the realm of computing technology, there is nothing quite as powerful and complex as the human brain. With its 86 billion neurons and up to a quadrillion synapses, the brain has unparalleled capabilities for processing information. Unlike traditional computing devices with physically separated units, the brain’s efficiency lies in its ability to serve as both a processor and memory device. Recognizing the potential of harnessing the brain’s power, researchers have been striving to create more brain-like computing systems.

Efforts to mimic the brain’s activity in artificial systems have been ongoing, but progress has been limited. Even one of the most powerful supercomputers in the world, Riken’s K Computer, struggled to simulate just a fraction of the brain’s activity. With its 82,944 processors and a petabyte of main memory, it took 40 minutes to simulate just one second of the activity of 1.73 billion neurons connected by 10.4 trillion synapses. This represented only one to two percent of the brain’s capacity.

Continue reading “Scientists built a Cyborg computer with living brain tissue” »

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A group of Spanish researchers have developed a brain-computer interface based on electroencephalograms that allowed a group of 22 users to play a simple multiplayer game. The interface was 94% accurate in translating players’ thoughts into game moves, with each move taking just over 5 seconds. The study was published in Frontiers in Human Neuroscience.

A brain-computer interface is a technology that enables direct communication between the human brain and external devices, such as computers or prosthetic limbs. Brain-computer interfaces work by detecting and interpreting neural signals, typically through electrodes placed on the user’s head. These signals are then translated into actionable commands, allowing individuals to control computers, devices, or applications using their thoughts.

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Scientists have grown a tiny brain-like organoid out of human stem cells, hooked it up to a computer, and demonstrated its potential as a kind of organic machine learning chip, showing it can quickly pick up speech recognition and math predictions.

As incredible as recent advances have been in machine learning, artificial intelligence still lags way behind the human brain in some important ways. For example, the brain happily learns and adapts all day long on an energy budget of about 20 watts, where a comparably powerful artificial neural network needs about 8 million watts to achieve anything remotely comparable.

What’s more, the human brain’s neural plasticity, its ability to grow new nervous tissue and expand existing connective channels, has granted it an ability to learn from noisy, low-quality data streams, with minimal training and energy expenditure. What AI systems accomplish with brute force and massive energy, the brain achieves with an effortless elegance. It’s a credit to the billions of years of high-stakes trial and error that delivered the human brain to the state it’s in today, in which it’s chiefly used to watch vast numbers of other people dancing while we’re on the toilet.

In a world-first, researchers from the GrapheneX-UTS Human-centric Artificial Intelligence Centre at the University of Technology Sydney (UTS) have developed a portable, non-invasive system that can decode silent thoughts and turn them into text.

The technology could aid communication for people who are unable to speak due to illness or injury, including stroke or paralysis. It could also enable seamless communication between humans and machines, such as the operation of a bionic arm or robot.

Continue reading “Portable, non-invasive, mind-reading AI turns thoughts into text” »

Summary: Researchers created a revolutionary system that can non-invasively convert silent thoughts into text, offering new communication possibilities for people with speech impairments due to illnesses or injuries.

The technology uses a wearable EEG cap to record brain activity and an AI model named DeWave to decode these signals into language. This portable system surpasses previous methods that required invasive surgery or cumbersome MRI scanning, achieving state-of-the-art EEG translation performance.

Continue reading “AI and EEG Transform Silent Thoughts to Text” »