A groundbreaking NHS trial will attempt to boost patients’ mood using a brain-computer-interface that directly alters brain activity using ultrasound.

The device, which is designed to be implanted beneath the skull but outside the brain, maps activity and delivers targeted pulses of ultrasound to “switch on” clusters of neurons. Its safety and tolerability will be tested on about 30 patient in the £6.5m trial, funded by the UK’s Advanced Research and Invention Agency (Aria).

In future, doctors hope the technology could revolutionise the treatment of conditions such as depression, addiction, OCD and epilepsy by rebalancing disrupted patterns of brain activity. — Read More

François Chollet, an influential AI researcher, is launching a new startup that aims to build frontier AI systems with novel designs.

The startup, Ndea, will consist of an AI research and science lab. It’s looking to “develop and operationalize” AGI. AGI, which stands for “artificial general intelligence,” typically refers to AI that can perform any task a human can. It’s a goalpost for many AI companies, including OpenAI.

… Ndea plans to use a technique called program synthesis, in tandem with other technical approaches, to unlock AGI.  — Read More

In November, a young man named Noland Arbaugh announced he’d be livestreaming from his home for three days straight. His broadcast was in some ways typical fare: a backyard tour, video games, meet mom.

The difference is that Arbaugh, who is paralyzed, has thin electrode-studded wires installed in his brain, which he used to move a computer mouse on a screen, click menus, and play chess. The implant, called N1, was installed last year by neurosurgeons working with Neuralink, Elon Musk’s brain-interface company.

The possibility of listening to neurons and using their signals to move a computer cursor was first demonstrated more than 20 years ago in a lab setting. Now, Arbaugh’s livestream is an indicator that Neuralink is a whole lot closer to creating a plug-and-play experience that can restore people’s daily ability to roam the web and play games, giving them what the company has called “digital freedom.”

But this is not yet a commercial product.  — Read More

The technology firm OpenAI made headlines last month when its latest experimental chatbot model, o3, achieved a high score on a test that marks progress towards artificial general intelligence (AGI). OpenAI’s o3 scored 87.5%, trouncing the previous best score for an artificial intelligence (AI) system of 55.5%.

This is “a genuine breakthrough”, says AI researcher François Chollet, who created the test, called Abstraction and Reasoning Corpus for Artificial General Intelligence (ARC-AGI)¹, in 2019 while working at Google, based in Mountain View, California. A high score on the test doesn’t mean that AGI — broadly defined as a computing system that can reason, plan and learn skills as well as humans can — has been achieved, Chollet says, but o3 is “absolutely” capable of reasoning and “has quite substantial generalization power”.

Researchers are bowled over by o3’s performance across a variety of tests, or benchmarks, including the extremely difficult FrontierMath test, announced in November by the virtual research institute Epoch AI.  …But many, including Rein, caution that it’s hard to tell whether the ARC-AGI test really measures AI’s capacity to reason and generalize. “ — Read More

The scourge of tuberculosis (TB) may be largely a distant memory for most Americans and Europeans, but it killed roughly 1.25 million people last year around the world. A non-profit based in India, which accounts for more than a quarter of all cases, is developing AI tools that could boost efforts to eradicate the disease.

Roughly 10 million people a year fall ill with TB, making it one of the world’s most prevalent infectious diseases. In 2018, Indian Prime Minister Narendra Modi made an ambitious pledge to eliminate TB in India by 2025. With 2.5 million cases recorded in India last year, that goal clearly won’t be met; still, the country has invested hundreds of millions of dollars in a vast national TB program, and has reduced the disease’s incidence by about 18 percent between 2015 and 2023.

… Indian non-profit Wadhwani AI has developed a suite of AI-powered tools to assist health workers detect undiagnosed cases, decide on treatment plans, and prevent people from dropping out of treatment. Working with the Indian government and the U.S. Agency for International Development, the organization is currently piloting these tools across the country. And Wadhwani’s director of solutions, Nakul Jain, says 2025 could see several incorporated into India’s national TB patient management system, Nikshay. — Read More

Virtual- and augmented-reality setups already modify the way users see and hear the world around them. Add in haptic feedback for a sense of touch and a VR version of Smell-O-Vision, and only one major sense remains: taste.

To fill the gap, researchers at the City University of Hong Kong have developed a new interface to simulate taste in virtual and other extended reality (XR). The group previously worked on other systems for wearable interfaces, such as haptic and olfactory feedback. To create a more “immersive VR experience,” they turned to adding taste sensations, says Yiming Liu, a coauthor of the group’s research paper published today in the Proceedings of the National Academy of Sciences. — Read More

For all the promise and dangers of AI, computers plainly can’t think. To think is to resist – something no machine does

Computers don’t actually do anything. They don’t write, or play; they don’t even compute. Which doesn’t mean we can’t play with computers, or use them to invent, or make, or problem-solve. The new AI is unexpectedly reshaping ways of working and making, in the arts and sciences, in industry, and in warfare. We need to come to terms with the transformative promise and dangers of this new tech. But it ought to be possible to do so without succumbing to bogus claims about machine minds.

What could ever lead us to take seriously the thought that these devices of our own invention might actually understand, and think, and feel, or that, if not now, then later, they might one day come to open their artificial eyes thus finally to behold a shiny world of their very own? One source might simply be the sense that, now unleashed, AI is beyond our control. Fast, microscopic, distributed and astronomically complex, it is hard to understand this tech, and it is tempting to imagine that it has power over us.

But this is nothing new. The story of technology – from prehistory to now – has always been that of the ways we are entrained by the tools and systems that we ourselves have made. — Read More

Expert problem-solving is driven by powerful languages for thinking about problems and their solutions. Acquiring expertise means learning these languages — systems of concepts, alongside the skills to use them. We present DreamCoder, a system that learns to solve problems by writing programs. It builds expertise by creating programming languages for expressing domain concepts, together with neural networks to guide the search for programs within these languages. A “wake-sleep” learning algorithm alternately extends the language with new symbolic abstractions and trains the neural network on imagined and replayed problems. DreamCoder solves both classic inductive programming tasks and creative tasks such as drawing pictures and building scenes. It rediscovers the basics of modern functional programming, vector algebra and classical physics, including Newton’s and Coulomb’s laws. Concepts are built compositionally from those learned earlier, yielding multi-layered symbolic representations that are interpretable and transferrable to new tasks, while still growing scalably and flexibly with experience. — Read More

#human

In the search for less energy-hungry artificial intelligence, some scientists are exploring living computers

Artificial intelligence systems, even those as sophisticated as ChatGPT, depend on the same silicon-based hardware that has been the bedrock of computing since the 1950s. But what if computers could be molded from living biological matter? Some researchers in academia and the commercial sector, wary of AI’s ballooning demands for data storage and energy, are focusing on a growing field known as biocomputing. This approach uses synthetic biology, such as miniature clusters of lab-grown cells called organoids, to create computer architecture. Biocomputing pioneers include Swiss company FinalSpark, which earlier this year debuted its “Neuroplatform”—a computer platform powered by human-brain organoids—that scientists can rent over the Internet for $500 a month. — Read More

The operation of the Neuroplatform currently relies on an architecture that can be classified as wetware: the mixing of hardware, software, and biology. The main innovation delivered by the Neuroplatform is through the use of four Multi-Electrode Arrays (MEAs) housing the living tissue – organoids, which are 3D cell masses of brain tissue.

Each MEA holds four organoids, interfaced by eight electrodes used for both stimulation and recording. Data goes to-and-fro via digital analog converters (Intan RHS 32 controller) with a 30kHz sampling frequency and a 16-bit resolution. These key architectural design features are supported by a microfluidic life support system for the MEAs, and monitoring cameras. Last but not least, a software stack allows researchers to input data variables, and then read and interpret processor output. — Read More