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Researchers at Universidad Autónoma de Madrid have recently created an innovative, AI-powered platform that could enhance remote learning, allowing educators to securely monitor students and verify that they are attending compulsory online classes or exams.

An initial prototype of this platform, called Demo-edBB, is set to be presented at the AAAI-23 Conference on Artificial Intelligence in February 2022, in Washington, and a version of the paper is available on the arXiv preprint server.

“Our investigation group, the BiDA-Lab at Universidad Autónoma de Madrid, has substantial experience with biometric signals and systems, behavior analysis and AI applications, with over 300 hundred published papers in last two decades,” Roberto Daza Garcia, one of the researchers who carried out the study, told TechXplore.

Scientists determine that a gamma-ray burst detected on Earth was caused by a space explosion that happened less than 900 million years ago.

On September 5, 2021, light from a very energetic gamma-ray burst (GRB) – an incredibly energetic explosion that happened in a faraway galaxy – reached our planet. To get to Earth, it traveled for more than 12.8 billion years. The glow began its journey when the Universe (which is considered to be 13.7 billion years old) was just 880 million years old.

A worldwide team of astronomers proceeded to study the explosion’s afterglow in the months that followed this finding in order to understand what caused it. Dr. Andrea Rossi, a researcher at the Italian National Institute of Astrophysics (INAF), headed the group. Professor Carole Mundell from the University of Bath was also involved.

Scientists from Ohio University, Argonne National Laboratory, and the University of Illinois at Chicago used scanning tunneling microscopy to form a charged rare earth molecule on a metal surface and rotate it clockwise and counterclockwise without affecting its charge.

Their findings open up new avenues for research into the atomic-scale manipulation of materials important to the future, ranging from quantum computing.

Continue reading “For the First Time: Scientists Have Formed a Charged Rare Earth Molecule on a Metal Surface and Rotated It” »

Taking inspiration from Mother Nature once again results in a new material with fantastic properties.

Using a chain of atoms in single-file to simulate the event horizon of a black hole, a team of physicists has observed the equivalent of what we call Hawking radiation – particles born from disturbances in the quantum fluctuations caused by the black hole’s break in spacetime.

This, they say, could help resolve the tension between two currently irreconcilable frameworks for describing the Universe: the general theory of relativity, which describes the behavior of gravity as a continuous field known as spacetime; and quantum mechanics, which describes the behavior of discrete particles using the mathematics of probability.

For a unified theory of quantum gravity that can be applied universally, these two immiscible theories need to find a way to somehow get along.

Unity CEO Anirvan Ghosh, Ph.D./courtesy of Unity Biotechnology

Senolytic therapies are, at this point, as revolutionary as checkpoint inhibitors but with broader effectiveness. This approach delays the onset of diseases of aging by removing senescent cells from the body, thus enabling people to remain healthier longer or to regain some degree of function lost to disease.

Senolytics is a new field and most of the research is still in academic centers – most notably, the Mayo Clinic. Approval of any therapeutics is years – perhaps even a decade – away.

Ammaar Reshi was playing around with ChatGPT, an AI-powered chatbot from OpenAI when he started thinking about the ways artificial intelligence could be used to make a simple children’s book to give to his friends. Just a couple of days later, he published a 12-page picture book, printed it, and started selling it on Amazon without ever picking up a pen and paper.

The feat, which Reshi publicized in a viral Twitter thread, is a testament to the incredible advances in AI-powered tools like ChatGPT—which took the internet by storm two weeks ago with its uncanny ability to mimic human thought and writing. But the book, Alice and Sparkle, also renewed a fierce debate about the ethics of AI-generated art. Many argued that the technology preys on artists and other creatives—using their hard work as source material, while raising the specter of replacing them.

Deep Learning AI Specialization: https://imp.i384100.net/GET-STARTED
GPT-4 is the next large language model from OpenAI after GPT-3 and ChatGPT, and it’s expected to use 100 trillion parameters while accepting multi-modal inputs including audio, text, and video. Researchers have created a soft robotics device that can heal itself after being wounded and continue moving. New memristor deep learning system reduces power for AI training by 100 thousand times.

AI News Timestamps:
0:00 OpenAI GPT-4 Size.
1:18 GPT-4 AI Model Sparsity.
2:06 OpenAI Going For Multimodal.
3:15 OpenAI’s Cost of Training.
4:32 New Self Healing Soft Robotics.
6:04 New Memristor Deep Learning System.

#technology #tech #ai

Self-supervised learning is a form of unsupervised learning in which the supervised learning task is constructed from raw, unlabeled data. Supervised learning is effective but usually requires a large amount of labeled data. Getting high-quality labeled data is time-consuming and resource-intensive, especially for sophisticated tasks like object detection and instance segmentation, where more in-depth annotations are sought.

Self-supervised learning aims to first learn usable representations of the data from an unlabeled pool of data by self-supervision and then to refine these representations with few labels for the supervised downstream tasks such as image classification, semantic segmentation, etc.

Self-supervised learning is at the heart of many recent advances in artificial intelligence. However, existing algorithms focus on a particular modality (such as images or text) and a high computer resource requirement. Humans, on the other hand, appear to learn significantly more efficiently than existing AI and to learn from diverse types of information consistently rather than requiring distinct learning systems for text, speech, and other modalities.