Lifeboat Foundation

A new artificial intelligence system called a semantic decoder 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 researchers at The University of Texas at Austin might help people who are mentally conscious yet unable to physically speak, such as those debilitated by strokes, to communicate intelligibly again.

The study, published in the journal Nature Neuroscience, was led by Jerry Tang, a doctoral student in computer science, and Alex Huth, an assistant professor of neuroscience and computer science at UT Austin. The work relies in part on a transformer model, similar to the ones that power Open AI’s ChatGPT and Google’s Bard.

Unlike other language decoding systems in development, this system 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 fMRI 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.

Scientists have developed a noninvasive AI system focused on translating a person’s brain activity into a stream of text, according to a peer-reviewed study published Monday in the journal Nature Neuroscience.

The system, called a semantic decoder, could ultimately benefit patients who have lost their ability to physically communicate after suffering from a stroke, paralysis or other degenerative diseases.

Speaking with ‘The New York Times,’ Geoffrey Hinton says a part of him regrets his life’s work on artificial intelligence.

A team of scientists at the Instituto Italiano di Tecnologia in Italy has created the world’s first completely edible and rechargeable battery. The innovative battery could be used to power edible electronics for health diagnostics, food quality monitoring, and edible soft robotics.

Edible Rechargeable Battery

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Greater scale and symbolic models are necessary before AI and machine learning can meet big challenges like breaking the best encryption algorithms.

Researchers have taught an AI to make artificial genomes — possibly overcoming the problem of how to protect people’s genetic information while also amassing enough DNA for research.

Generative adversarial networks (GANs) pit two neural networks against each other to produce new, synthetic data that is so good it can pass for real data. Examples have been popping up all over the web — generating pictures and videos (a la “this city does not exist”). AIs can even generate convincing news articles, food blogs, or human faces (take a look here for a complete list of all the oddities created by GANs).

Now, researchers from Estonia are going more in-depth with deepfakes of human DNA. They created an algorithm that repeatedly generates the genetic code of people that don’t exist.

When people pay for sexual media, they’re seeking more than an anonymous image. AI cannot replicate the underlying desires that drive sex work.

Join top executives in San Francisco on July 11–12, to hear how leaders are integrating and optimizing AI investments for success. Learn More

After several decades of hope, hype and false starts, it appears that artificial intelligence (AI) has finally gone from throwing off sparks to catching fire. Tools like DALL-E and ChatGPT have seized the spotlight and the public imagination, and this latest wave of AI appears poised to be a game-changer across multiple industries.

But what kind of impact will AI have on the 3D engineering space? Will designers and engineers see significant changes in their world and their daily workflows, and if so, what will those changes look like?

Join top executives in San Francisco on July 11–12, to hear how leaders are integrating and optimizing AI investments for success. Learn More

Generative AI has received a lot of attention already this year in the tech world and beyond. Whether it’s ChatGPT’s prose or Stable Diffusion’s art, 2022 provided an insight into the potential for AI to disrupt creative industries.

But behind the headlines, 2022 brought an even more important development in AI: the rise of the vector database.