Toggle light / dark theme

In a new study, researchers at the Indian Institute of Science (IISc) show how a brain-inspired image sensor can go beyond the diffraction limit of light to detect miniscule objects such as cellular components or nanoparticles invisible to current microscopes. Their novel technique, which combines optical microscopy with a neuromorphic camera and machine learning algorithms, presents a major step forward in pinpointing objects smaller than 50 nanometers in size. The results are published in Nature Nanotechnology.

Since the invention of optical microscopes, scientists have strived to surpass a barrier called the , which means that the microscope cannot distinguish between two objects if they are smaller than a certain size (typically 200–300 nanometers).

Their efforts have largely focused on either modifying the molecules being imaged, or developing better illumination strategies—some of which led to the 2014 Nobel Prize in Chemistry. “But very few have actually tried to use the detector itself to try and surpass this detection limit,” says Deepak Nair, Associate Professor at the Center for Neuroscience (CNS), IISc, and corresponding author of the study.

Users of the Replika chatbot system can no longer engage in erotic or sexual dialogue with their digital counterparts, after years of being able to do so. This highlights a dilemma when people become emotionally attached to chatbots.

Under the name “AI Companion”, Replika is marketing a chatbot system that, like ChatGPT and the like, converses with users in natural language and is also embodied as a visual avatar. Replika will be “there to listen and talk” and “always on your side”, the company promises. With augmented reality, you can project the avatar chatbots life-size into your room.

It is a paid-for chatbot service that in the past used a fine-tuned variant of GPT-3 for language output. Luka, the company behind Replika, was an early OpenAI partner, using the language model via an API.

Benchmarks from German AI startup Aleph Alpha show that the startup’s latest AI models can keep up with OpenAI’s GPT-3. A success that should not lull Europe into a false sense of security.

ChatGPT has catapulted artificial intelligence into the public discussion like no other product before it. Behind the chatbot is the U.S. company OpenAI, which made headlines with the large-scale language model GPT-3 and later with the text-to-picture model DALL-E 2. The impact of systems like ChatGPT or Midjourney on education and work, which can be felt today, was foreseeable even then.

The underlying language models are often referred to in research as foundation models: a large AI model that, due to its generalist training with large datasets, can later take on many tasks for which it was not explicitly trained.

https://youtu.be/ELiyvT6Fq3g

ChatGPT is a powerful Artificial Intelligence platform that will take over the world!

In this video, I’m sharing with you all about ChatGPT, its capabilities, and why Bill Gates and other world-renowned experts believe it will be a major force in the future!

ChatGPT is a cutting-edge Artificial Intelligence platform that will change the way we live and work forever. It’s powered by the latest in machine learning and artificial intelligence technologies, and it has the potential to transform many industries.

If you’re interested in Artificial Intelligence or just want to know more about ChatGPT, watch this video and learn everything you need to know!

A multidisciplinary Northwestern University research team has created a groundbreaking transistor that is expected to be optimal for bioelectronics that are high-performance, lightweight, and flexible.

The new electrochemical transistor is compatible with both blood and water and has the ability to amplify significant signals, making it highly beneficial for biomedical sensing. This transistor could make it possible to develop wearable devices that can perform on-site signal processing right at the biology-device interface. Some potential applications include monitoring heart rate and levels of sodium and potassium in the blood, as well as tracking eye movements to study sleep disorders.

“All modern electronics use transistors, which rapidly turn current on and off,” said Tobin J. Marks, a co-corresponding author of the study. “Here we use chemistry to enhance the switching. Our electrochemical transistor takes performance to a totally new level. You have all the properties of a conventional transistor but far higher transconductance (a measure of the amplification it can deliver), ultra-stable cycling of the switching properties, a small footprint that can enable high-density integration, and easy, low-cost fabrication.”

New textiles developed at Aalto University change shape when they heat up, giving designers a wide range of new options. In addition to offering adjustable esthetics, responsive smart fabrics could also help monitor people’s health, improve thermal insulation, and provide new tools for managing room acoustics and interior design.

The new fabrics weave together old technology and a new approach. Liquid crystalline elastomers (LCEs) were developed in the 1980s. LCEs are a smart material that can respond to heat, light, or other stimuli, and they’ve been used as thin films in soft robotics. Although LCEs have been made into fibers, so far they haven’t been made into textiles.

In collaboration with researchers at the University of Cambridge, a team from the Multifunctional Materials Design research group at Aalto, led by Prof. Jaana Vapaavuori, has now used LCE yarns to make woven fabric using conventional crafting techniques and tested how the fabric behaved. The findings were published in Advanced Materials.

Advancing Biomedical R&D & Clinical Development In Saudi Arabia — Dr. Abdelali Haoudi, Ph.D., Managing Director, Biotechnology Park, King Abdullah International Medical Research Center, Ministry of National Guard Health Affairs.


Dr. Abdelali Haoudi, Ph.D. (https://kaimrc-biotech.org.sa/dr-abdelali-haoudi/) currently leads Strategy and Business Development functions, and is also Managing Director of the Biotechnology Park, at King Abdullah International Medical Research Center, at the Ministry of National Guard Health Affairs. He is also Distinguished Scholar at Harvard University-Boston Children’s Hospital.

Dr. Haoudi is an international Research & Development and Innovation Executive with over 25 years experience, having held several senior positions in Research and Development and Innovation. He has vast experience in science and technology policy development, strategy and business development, corporate development and international partnerships development.

The goal of the Search for Extraterrestrial Intelligence (SETI) is to quantify the prevalence of technological life beyond Earth via their “technosignatures”. One theorized technosignature is narrowband Doppler drifting radio signals.

The principal challenge in conducting SETI in the radio domain is developing a generalized technique to reject human radio frequency interference (RFI). Here, we present the most comprehensive deep-learning based technosignature search to date, returning 8 promising ETI signals of interest for re-observation as part of the Breakthrough Listen initiative.

The search comprises 820 unique targets observed with the Robert C. Byrd Green Bank Telescope, totaling over 480, hr of on-sky data. We implement a novel beta-Convolutional Variational Autoencoder to identify technosignature candidates in a semi-unsupervised manner while keeping the false positive rate manageably low. This new approach presents itself as a leading solution in accelerating SETI and other transient research into the age of data-driven astronomy.