Lifeboat Foundation

In the future, quantum computers may be able to solve problems that are far too complex for today’s most powerful supercomputers. To realize this promise, quantum versions of error correction codes must be able to account for computational errors faster than they occur.

However, today’s quantum computers are not yet robust enough to realize such error correction at commercially relevant scales.

On the way to overcoming this roadblock, MIT researchers demonstrated a novel superconducting qubit architecture that can perform operations between qubits—the building blocks of a quantum computer—with much greater accuracy than scientists have previously been able to achieve.

A team of computer scientists at UC Riverside has developed a new method to detect manipulated facial expressions in deep fake videos. The method could detect these expressions with up to 99% accuracy, making it more accurate than the current state-of-the-art methods.

The new research paper titled “Detection and Localization of Facial Expression Manipulations” was presented at the 2022 Winter Conference on Applications of Computer Vision.

Detecting Any Facial Manipulation

Running could be for everyone even at Olympic levels with biocomputing and crispr.

Citation: (2004) Gene Targeting Turns Mice into Long-Distance Runners. PLoS Biol 2(10): e322. https://doi.org/10.1371/journal.pbio.

Copyright: © 2004 Public Library of Science. This is an open-access distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Driving the technology forward are advances in materials science and AI, plus patient benefits like shorter recovery times and less pain.

In the ever-evolving landscape of artificial intelligence and natural language processing, one phenomenon has taken center stage like never before is the large language model. These creations, infused with billions of parameters and fuelled by vast data repositories, are transforming the way we interact with machines. As this field has begun to take over the Software engineering industry, understanding the technology and diving deep into its nuances becomes paramount.

In this blog, we will do a deep dive into the pieces and components inside a Large Language Model.

Believe it or not, air contains as much water as six times the world’s rivers combined.

This is mostly in the form of water vapor, and it actually replenishes naturally every 8 to 10 days — give or take. This offers a valuable potential reservoir of freshwater that could be tapped relatively easily.

All we need is the right kind of technology.

Surf Air Mobility Inc., a Southern California aerospace company devoted to developing regional air travel through the power of electrification, has placed an order for 20 Cessna Grand Caravan EX aircraft.

The Cessna Grand Caravan EX is designed and manufactured by Textron Aviation, a Textron Inc. (NYSE: TXT) company.

According to Textron, Surf Air Mobility has paid the deposit for the first of 100 aircraft with the option for an additional 50. The deliveries of the aircraft are expected to begin in the first half of 2024.

Summary: Researchers delved into how ChatGPT influences user decision-making, focusing on the ‘choice overload’ phenomenon. This condition emerges when an individual is overwhelmed by numerous options, often leading to decision paralysis or dissatisfaction.

The study found, however, that users preferred larger numbers of recommendations from ChatGPT over those from humans or online agents, appreciating the perceived accuracy of the chatbot’s suggestions. This points towards a new paradigm where AI-generated options might enhance decision-making processes across various industries.

The results of the Chi-Nu physics experiment at Los Alamos National Laboratory have contributed essential, never-before-observed data for enhancing nuclear security applications, understanding criticality safety and designing fast-neutron energy reactors. The Chi-Nu project, a years-long experiment measuring the energy spectrum of neutrons emitted from neutron-induced fission, recently concluded the most detailed and extensive uncertainty analysis of the three major actinide elements—uranium-238, uranium-235 and plutonium-239.

“Nuclear fission and related nuclear chain reactions were only discovered a little more than 80 years ago, and experimenters are still working to provide the full picture of fission processes for the major actinides,” said Keegan Kelly, a physicist at Los Alamos National Laboratory. “Throughout the course of this project, we have observed clear signatures of fission processes that in many cases were never observed in any previous experiment.”

The Los Alamos team’s final Chi-Nu study, on the isotope uranium-238, was recently published in Physical Review C. The experiment measured uranium-238’s prompt fission neutron spectrum: the energy of the neutron inducing the fission—the neutron that crashes into a nucleus and splits it—and the potentially wide-ranging energy distribution (the spectrum) of the neutrons released as a result. Chi-Nu focuses on “fast-neutron-induced” fission, with incident neutron energies in millions of electron volts, where there have typically been very few measurements.