Exclusive Content:

Haiper steps out of stealth mode, secures $13.8 million seed funding for video-generative AI

Haiper Emerges from Stealth Mode with $13.8 Million Seed...

Running Your ML Notebook on Databricks: A Step-by-Step Guide

A Step-by-Step Guide to Hosting Machine Learning Notebooks in...

“Revealing Weak Infosec Practices that Open the Door for Cyber Criminals in Your Organization” • The Register

Warning: Stolen ChatGPT Credentials a Hot Commodity on the...

Electronic skin that mimics human pain response is a breakthrough

Development of Intelligent Electronic Skin Capable of Sensing Pain like Human Skin

Electronic skins that can mimic the sensory functions of human skin have the potential to revolutionize the fields of robotics and medical devices. While much research has been focused on creating artificial skins that can feel touch and temperature, a new breakthrough from researchers in Australia has now focused on developing electronic skins that can actually feel pain.

The team from Australia’s Royal Melbourne Institute of Technology has successfully created an artificial skin that can respond to painful stimuli in the same way that real skin does. This breakthrough is a significant step towards creating intelligent machines and prosthetics that can better understand and respond to their environments.

This new electronic skin is able to replicate the feedback loop of painful stimuli in great detail, allowing it to distinguish between different levels of pain and react accordingly. The researchers behind this innovation believe that they have created the first electronic somatosensors, which can mimic the complex system of neurons, neural pathways, and receptors that drive our perception of sensory stimuli.

The artificial skin incorporates three separate sensing technologies, including a stretchable electronic material made of biocompatible silicone, temperature-reactive coatings that respond to heat, and electronic memory cells that mimic the way the brain stores information. This innovative combination allows the artificial skin to react instantly when pressure, heat, or cold reach a painful threshold, providing a more realistic and human-like experience of pain.

Lead researcher Professor Madhu Bhaskaran explains, “No electronic technologies have been able to realistically mimic that very human feeling of pain – until now. Our artificial skin reacts instantly when pressure, heat or cold reach a painful threshold. It’s a critical step forward in the future development of the sophisticated feedback systems that we need to deliver truly smart prosthetics and intelligent robotics.”

With further development, the electronic skin could potentially be used for non-invasive skin grafts, providing a safer and more efficient option for patients in need of skin replacement. Overall, this breakthrough in creating electronic skins that can feel pain has the potential to greatly impact the fields of robotics and medical devices, opening up new possibilities for innovation and advancement in the future.

Latest

Create a Scalable Test Suite with Dataset Management in Amazon Bedrock AgentCore

Optimizing Agent Performance: The Role of Versioned Datasets in...

Expedia Unveils ChatGPT-Enhanced Travel Planning: Here’s How to Get Started.

Revolutionizing Travel: Expedia Integrates ChatGPT for Personalized Trip Planning Let...

2 Leading AI Robotics Stocks to Consider Over Tesla

Exploring Robotics Stocks: Two Promising Alternatives to Tesla The Evolution...

Centre Introduces AI Voice Chatbot for Addressing Grievances

Launch of Samadhan Didi: AI Chatbot to Empower Citizens...

Don't miss

Haiper steps out of stealth mode, secures $13.8 million seed funding for video-generative AI

Haiper Emerges from Stealth Mode with $13.8 Million Seed...

Running Your ML Notebook on Databricks: A Step-by-Step Guide

A Step-by-Step Guide to Hosting Machine Learning Notebooks in...

VOXI UK Launches First AI Chatbot to Support Customers

VOXI Launches AI Chatbot to Revolutionize Customer Services in...

Investing in digital infrastructure key to realizing generative AI’s potential for driving economic growth | articles

Challenges Hindering the Widescale Deployment of Generative AI: Legal,...

Assessing Deep Agents with LangSmith on AWS

Evaluating AI Agents: A Comprehensive Guide to Reliable Assessment This post was co-authored with Karan Singh, Head of Partnerships at LangChain. Understanding the Challenges of...

Comprehensive Observability for Amazon SageMaker AI LLM Inference: Monitoring GPU Utilization...

Comprehensive Observability for Large Language Models in Production with Amazon SageMaker AI Inference Understanding the Importance of Observability in LLM Deployment Two Dimensions of LLM Observability:...

Training Azerbaijani Language Models Using Amazon SageMaker AI

Building an Azerbaijani Language Model: Optimizing Training with Open Source Tools and AWS Acknowledgments Introduction to the Challenge Solution Overview Stage 1: Tokenizer Development Stage 2: Continued Pre-training (CPT) Stage...