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

A cubic millimeter of brain tissue may not sound like much. But considering that that tiny square contains 57,000 cells, 230 millimeters of blood vessels, and 150 million synapses, all amounting to 1,400 terabytes of data, Harvard and Google researchers have just accomplished something stupendous.

Led by Jeff Lichtman, the Jeremy R. Knowles Professor of Molecular and Cellular Biology and newly appointed dean of science, the Harvard team helped create the largest 3D brain reconstruction to date, showing in vivid detail each cell and its web of connections in a piece of temporal cortex about half the size of a rice grain. — Read More

The Study

AI is a lever that becomes a lens

I remember when I first saw GPT-3 output writing: that line of letters hammered out one by one, rolling horizontally across the screen in its distinctive staccato. It struck both wonder and terror into my heart.

I felt ecstatic that computers could finally talk back to me. But I also felt a heavy sense of dread. I’m a writer—what would happen to me? 

We’ve all had this experience with AI over the last year and a half. It is an emotional rollercoaster. It feels like it threatens our conception of ourselves.  — Read More

It is estimated that 180,000 Americans live with quadriplegia, and each year, an additional ~18,000 suffer a paralyzing spinal cord injury. We live in a digital society where‬‭ much of our work, entertainment, and social lives rely heavily on our use of computers and‬‭ smart devices. People with quadriplegia often find that their needs to engage seamlessly with the digital world go unmet, leading to decreased independence, isolation, and financial challenges. Our goal is to provide a high-performance interface that will enhance the control of digital devices for people with quadriplegia, unlocking their personal and professional potential.

The first step toward this goal was achieved just over 100 days ago at Barrow Neurological Institute in Phoenix Arizona, where Noland Arbaugh, the first participant of the PRIME Study*, received his Neuralink implant (Link). As noted in our last blog post, the surgery went extremely well, and he was able to go home the following day.

The aim of the PRIME Study is to demonstrate that the Link is safe and useful in daily life. We will monitor its technical performance remotely and quantify any benefit it provides by timing the duration of independent use and assessing how it affects study participants’ quality of life. — Read More