Lifeboat Foundation

CU Boulder scientists have found how ions move in tiny pores, potentially improving energy storage in devices like supercapacitors. Their research updates Kirchhoff’s law, with significant implications for energy storage in vehicles and power grids.

Imagine if your dead laptop or phone could be charged in a minute, or if an electric car could be fully powered in just 10 minutes. While this isn’t possible yet, new research by a team of scientists at CU Boulder could potentially make these advances a reality.

Published in the Proceedings of the National Academy of Sciences, researchers in Ankur Gupta’s lab discovered how tiny charged particles, called ions, move within a complex network of minuscule pores. The breakthrough could lead to the development of more efficient energy storage devices, such as supercapacitors, said Gupta, an assistant professor of chemical and biological engineering.

We’re living in an aging society with cognitive loss placing stress on caregivers to monitor older adults struggling with memory decline.

MemPal is a wearable voice-based memory assistant that helps older adults live more independently and safely at home while also reducing caregiver burden. MemPal uses AI to automatically log the user’s actions in real-time based on visual context from a wearable camera without storing any image data, thereby preserving user privacy. With this activity log, MemPal helps older adults recall locations of misplaced objects and completion of past actions using simple voice-based queries such as “Hey Pal, where is my phone?” Additionally, MemPal provides context-based proactive safety reminders (e.g., “you may have forgotten to turn off the stove” or” you already took your medicine an hour ago”) and automatically tracks the completion on the MemPal app, allowing for remote monitoring by caregivers. Lastly MemPal can generate an automatic, summarized diary of activities for caregivers that may also prove useful for physicians to better understand patient behavior within their home.

MemPal was tested within the homes of 15 older adults (ages 65+). Our study demonstrated improved performance of object finding with audio-based assistance compared to no aid and positive overall user perceptions on the designed system. We discuss future design guidelines to adapt these types of wearable systems to various older adults’ needs.

Samsung has unveiled the world’s thinnest LPDDR5X DRAM chips for smartphones, tablets, and other mobile devices. The chip is just 0.65mm thin.

Passwords, Touch ID, and Face ID could all be a thing of the past, as Apple is working on a future where unlocking your devices is as easy as just holding a future iPhone or letting your Apple Watch sense your unique heart rhythm.

Everyone’s heart has a unique rhythm, which the Apple Watch monitors through the ECG app. In a recently granted patent, Apple describes a technique for identifying users based on their unique cardiovascular measurements.

With this technology, you can unlock all your devices if you keep wearing your Apple Watch. Verifying your heart patterns instead of a password or a fingerprint scan increases security and speeds up your identification.

Topological insulators, capable of transmitting electricity without loss, may function in fractional dimensions such as 1.58. This breakthrough, combined with room-temperature operability, paves the way for advancements in quantum computing and energy efficiency through fractal structures.

What if we could find a way to make electric currents flow, without energy loss? A promising approach for this involves using materials known as topological insulators. They are known to exist in one (wire), two (sheet) and three (cube) dimensions; all with different possible applications in electronic devices. Theoretical physicists at Utrecht University, together with experimentalists at Shanghai Jiao Tong University, have discovered that topological insulators may also exist at 1.58 dimensions, and that these could be used for energy-efficient information processing. Their study was published recently in Nature Physics.

Classical bits, the units of computer operation, are based on electric currents: electrons running means 1, no electrons running means 0. With a combination of 0s and 1s, one can build all the devices that you use in your daily life, from cellphones to computers. However, while running, these electrons meet defects and impurities in the material, and lose energy. This is what happens when your device gets warm: the energy is converted into heat, and so your battery is drained faster.

Machine learning influences numerous aspects of modern society, empowers new technologies, from Alphago to ChatGPT, and increasingly materializes in consumer products such as smartphones and self-driving cars. Despite the vital role and broad applications of artificial neural networks, we lack systematic approaches, such as network science, to understand their underlying mechanism. The difficulty is rooted in many possible model configurations, each with different hyper-parameters and weighted architectures determined by noisy data. We bridge the gap by developing a mathematical framework that maps the neural network’s performance to the network characters of the line graph governed by the edge dynamics of stochastic gradient descent differential equations. This framework enables us to derive a neural capacitance metric to universally capture a model’s generalization capability on a downstream task and predict model performance using only early training results. The numerical results on 17 pre-trained ImageNet models across five benchmark datasets and one NAS benchmark indicate that our neural capacitance metric is a powerful indicator for model selection based only on early training results and is more efficient than state-of-the-art methods.

The “neural processing unit” is being pushed as the next big thing for “AI PCs” and “AI smartphones,” but they won’t eliminate the need for cloud-based AI.

Nanotransfection is very useful and could be used as a way to heal oneself on a smartphone in one touch with cell reprogramming and much more like gene transfer.

Tissue nanotransfection (TNT), a cutting-edge technique of in vivo gene therapy, has gained substantial attention in various applications ranging from in vivo tissue reprogramming in regenerative medicine, and wound healing to cancer treatment. This technique harnesses the advancements in the semiconductor processes, facilitating the integration of conventional transdermal gene delivery methods—nanoelectroporation and microneedle technologies. TNT silicon chips have demonstrated considerable promise in reprogramming fibroblast cells of skin in vivo into vascular or neural cells in preclinical studies to assist in the recovery of injured limbs and damaged brain tissue. More recently, the application of TNT chips has been extended to the area of exosomes, which are vital for intracellular communication to track their functionality during the wound healing process.

A 64-year-old named Mark has spent the last year learning how to control devices like his laptop and phone using a brain implant. And thanks to OpenAI, it’s gotten a whole lot easier to do.

The neurotech startup Synchron said Thursday it’s using OpenAI’s latest artificial intelligence models to build a new generative chat feature for patients with its brain-computer interface, or BCI.

A BCI system decodes brain signals and translates them into commands for external technologies. Synchron’s model is designed to help people with paralysis communicate and maintain some independence by controlling smartphones, computers and other devices with their thoughts.