The human visual system has long been a source of inspiration for computer vision researchers, who aim to develop machines that can see and understand the world around them with the same level of efficiency and accuracy as humans. While machine vision systems have made significant progress in recent years, they still face major challenges when it comes to processing vast amounts of visual data while consuming minimal power.

One approach to overcoming these hurdles is through neuromorphic computing, which mimics the structure and function of biological neural systems. However, two major challenges persist: achieving color recognition comparable to human vision, and eliminating the need for external power sources to minimize energy consumption.

A recent breakthrough by a research team led by Associate Professor Takashi Ikuno from Tokyo University of Science has addressed these issues with a groundbreaking solution. Their self-powered artificial synapse is capable of distinguishing colors with remarkable precision, making it particularly suitable for edge computing applications where energy efficiency is crucial.

The device integrates two different dye-sensitized solar cells that respond differently to various wavelengths of light, generating its electricity via solar energy conversion. This self-powering capability makes it an attractive solution for industries such as autonomous vehicles, healthcare, and consumer electronics, where visual recognition capabilities are essential but power consumption is limited.

The researchers demonstrated the potential of their device in a physical reservoir computing framework, recognizing different human movements recorded in red, green, and blue with an impressive 82% accuracy. This achievement has significant implications for various industries, including autonomous vehicles, which could utilize these devices to efficiently recognize traffic lights, road signs, and obstacles.

In healthcare, self-powered artificial synapses could power wearable devices that monitor vital signs like blood oxygen levels with minimal battery drain. For consumer electronics, this technology could lead to smartphones and augmented/virtual reality headsets with dramatically improved battery life while maintaining sophisticated visual recognition capabilities.

The realization of low-power machine vision systems with color discrimination capabilities close to those of the human eye is within reach, thanks to this breakthrough research. The potential applications of self-powered artificial synapses are vast, and their impact will be felt across various industries in the years to come.

Harnessing the Power of AI: Why Leashes are Better than Guardrails for Regulation

For years, policymakers have debated the best way to regulate Artificial Intelligence (AI) to prevent its potential risks. A new paper by experts Cary Coglianese and Colton R. Crum proposes a game-changing approach: rather than imposing strict “guardrails” to control AI development, they suggest using flexible “leashes.” This management-based regulation would allow firms to innovate while ensuring public safety.

The authors argue that guardrails are not effective for AI due to its rapidly evolving nature and diverse applications. Social media, chatbots, autonomous vehicles, precision medicine, and fintech investment advisors are just a few examples of how AI is transforming industries. While offering numerous benefits, such as improved cancer detection, AI also poses risks like AV collisions, social media-induced suicides, and bias in digital formats.

Coglianese and Crum provide three case studies illustrating the potential harm from unregulated AI:

1. Autonomous vehicle (AV) crashes
2. Social media-related suicides
3. Bias and discrimination through AI-generated content

In each scenario, firms using AI tools would be expected to put their technology on a leash by implementing internal systems to mitigate potential harms. This flexible approach allows for technological innovation while ensuring that companies are accountable for the consequences of their actions.

Management-based regulation offers several advantages over guardrails:

* It can flexibly respond to AI’s novel uses and problems
* It enables technological exploration, discovery, and change
* It provides a tethered structure that helps prevent AI from “running away”

By embracing this leash-like approach, policymakers can harness the power of AI while minimizing its risks.

The University of Nebraska-Lincoln engineering team has made significant strides in developing soft robotics and wearable systems inspired by human and plant skin’s ability to self-heal injuries. Led by engineer Eric Markvicka, the team presented a groundbreaking paper at the IEEE International Conference on Robotics and Automation that showcased their innovative approach to creating an intelligent, self-healing artificial muscle.

The team’s strategy overcomes the long-standing problem of replicating traditional rigid systems using soft materials and incorporating nature-inspired design principles. Their multi-layer architecture enables the system to identify damage, pinpoint its location, and autonomously initiate a self-repair mechanism – all without external intervention.

The “muscle” or actuator features three layers: a damage detection layer composed of liquid metal microdroplets embedded in silicone elastomer, a self-healing component that uses thermoplastic elastomer to seal the wound, and an actuation layer that kick-starts the muscle’s motion when pressurized with water.

To begin the process, the team induces monitoring currents across the damage detection layer, which triggers formation of an electrical network between traces. Puncture or pressure damage causes this network to form, allowing the system to recognize and respond to the damage.

The next step is using electromigration – a phenomenon traditionally viewed as a hindrance in metallic circuits – to erase the newly formed electrical footprint. By further ramping up the current, the team can induce electromigration and thermal failure mechanisms that reset the damage detection network, effectively completing one cycle of damage and repair.

This breakthrough has far-reaching implications for various industries, particularly in agricultural states where robotics systems frequently encounter sharp objects. It could also revolutionize wearable health monitoring devices that must withstand daily wear and tear.

The technology has the potential to transform society more broadly by reducing electronic waste and mitigating environmental harm caused by consumer-based electronics’ short lifespans. Most consumer electronics have a lifespan of only one or two years, contributing billions of pounds of toxic waste each year.

“If we can begin to create materials that are able to passably and autonomously detect when damage has happened, and then initiate these self-repair mechanisms, it would really be transformative,” Markvicka said.