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The idea of solar energy being transmitted from space is not a new one. In 1968, a NASA engineer named Peter Glaser produced the first concept design for a solar-powered satellite. But only now, 55 years later, does it appear scientists have actually carried out a successful experiment. A team of researchers from Caltech announced on Thursday that their space-borne prototype, called the Space Solar Power Demonstrator (SSPD-1), had collected sunlight, converted it into electricity and beamed it to microwave receivers installed on a rooftop on Caltech’s Pasadena campus. The experiment also proves that the setup, which launched on January 3, is capable of surviving the trip to space, along with the harsh environment of space itself.

“To the best of our knowledge, no one has ever demonstrated wireless energy transfer in space even with expensive rigid structures. We are doing it with flexible lightweight structures and with our own integrated circuits. This is a first,” said Ali Hajimiri, professor of electrical engineering and medical engineering and co-director of Caltech’s Space Solar Power Project (SSPP), in a press release published on Thursday.

The experiment — known in full as Microwave Array for Power-transfer Low-orbit Experiment (or MAPLE for short) — is one of three research projects being carried out aboard the SSPD-1. The effort involved two separate receiver arrays and lightweight microwave transmitters with custom chips, according to Caltech. In its press release, the team added that the transmission setup was designed to minimize the amount of fuel needed to send them to space, and that the design also needed to be flexible enough so that the transmitters could be folded up onto a rocket.

Three of these procedures have thus far been undertaken in Canada.

A neurosurgeon in Canada has become the first in the nation to perform robot-assisted deep brain stimulation surgery on a patient suffering from epilepsy with success.

This is according to a report by CTV News published on Wednesday.


Interesting Engineering is a cutting edge, leading community designed for all lovers of engineering, technology and science.

“It can also be my opponent. It can help me train.”

An assistant professor of Interactive Computing at the Georgia Institute of Technology has revealed a robotic tennis partner that may soon become your sparring partner and skilled opponent.

Dr. Matthew Gombolay envisions a future where human-scale robots play a crucial role in sports and athletic training. His latest creation, ESTHER (Experimental Sport Tennis Wheelchair Robot) is inspired by the limitations of traditional static ball machines used for tennis training.

Open-source AI can be defined as software engineers collaborating on various artificial intelligence projects that are open to the public to develop. The goal is to better integrate computing with humanity. In early March, the open source community got their hands on Meta’s LLaMA which was leaked to the public. In barely a month, there are very innovative OpenSource AI model variants with instruction tuning, quantization, quality improvements, human evals, multimodality, RLHF, etc.

Open-source models are faster, more customizable, more private, and capable. They are doing things with $100 and 13B params that even market leaders are struggling with. One open-source solution, Vicuna, is an… More.


This article explores AI in the context of open-sourced alternatives and highlights market dynamics in play.

Russia claims that its S-350 Vityaz air defence system shot down a Ukrainian aircraft while operating in “automatic mode”. The Russian Deputy PM said that its highly acclaimed S-350 Vityaz air defence system was operating in the NVO zone. It demonstrated capabilities of autonomously detecting, tracking, and destroying Ukrainian air targets without any operator’s intervention. Watch the video to find out how did the system work on AI?

#artificialintelligence #S350Vityaz #worldnews #defencenews.

00:00 — INTRODUCTION
01:13 — HOW DID THE SYSTEM WORK ON AI?
02:47 — RUSSIA’S S-350 AIR DEFENCE SYSTEM

Footage Courtesy: Twitter n18oc_world n18oc_crux.

A team of researchers successfully constructed nanofiltration membranes with superior quality using the mussel-inspired deposition methods. Such was achieved via a two-part approach to fabricate the thin-film composite (TFC) nanofiltration membranes. Firstly, the substrate surface was coated through fast and novel deposition to form a dense, robust, and functional selective layer. Then, the structure controllability of the selective layer was enhanced by optimizing the interfacial polymerization (IP) process. As a result, the properties of nanofiltration membranes produced are with high durability and added functionality. When put into a bigger perspective, these high-performance TFC nanofiltration membranes are potential solutions to a number of fields, including water softening, wastewater treatment, and pharmaceutical purification. Hence, there is a need to further explore and expand the application in an industrial scale instead of being bound within the walls of the laboratories.

Membrane-based technologies, especially enhanced nanofiltration systems, have been highly explored due to their myriad of distinct properties, primarily for their high efficiency, mild operation, and strong adaptability. Among these, the TFC nanofiltration membranes are favoured for their smaller molecular weight cutoff, and narrower pore size distribution which lead to higher divalent and multivalent ion rejection ability. Moreover, these membranes show better designability owing to their thin selective layer make-up and porous support with different chemical compositions. However, the interfacial polymerization (IP) rate of reaction is known to affect the permeability and selectivity of the TFC nanofiltration membranes by weakening the controllability of the selective layer structure. Therefore, this study was designed to improve the structural quality of the TFC nanofiltration membranes through surface and interface engineering, and subsequently, increase the functionality.

It is one of the ambitions of the United Nations to ensure availability and sustainable management of water and sanitation for all (SDG 6: Clean water and sanitation). A report by the United Nations’ Water for Life initiative stated that one in four people do not have access to safe drinking water, and up to 50% of the global population are at risk of living in water stressed areas by 2025. With such concerns looming close, undoubtably, there is a demand for advanced and efficient wastewater treatment technology to be put in place. Thus, the successful designing of improved and highly functional TFC nanofiltration membranes through innovative approaches portrayed in this study could be the much-needed solution in addressing these issues.

Background

Many everyday tasks can fall under the mathematical class of “hard” problems. Typically, these problems belong to the complexity class of nondeterministic polynomial (NP) hard. These tasks require systematic approaches (algorithms) for optimal outcomes. In the case of significant complex problems (e.g., the number of ways to fix a product or the number of stops to be made on a delivery trip), more computations are required, which rapidly outgrows cognitive capacities.

A recent Science Advances study investigated the effectiveness of three popular smart drugs, namely, modafinil (MOD), methylphenidate (MPH), and dextroamphetamine (DEX), against the difficulty of real-life daily tasks, i.e., the 0–1 knapsack optimization problem (“knapsack task”). A knapsack task is basically a combinatorial optimization task, the class of NP-time challenging problems.

The compelling feature of this new breed of quasiparticle, says Pedram Roushan of Google Quantum AI, is the combination of their accessibility to quantum logic operations and their relative invulnerability to thermal and environmental noise. This combination, he says, was recognized in the very first proposal of topological quantum computing, in 1997 by the Russian-born physicist Alexei Kitaev.

At the time, Kitaev realized that non-Abelian anyons could run any quantum computer algorithm. And now that two separate groups have created the quasi-particles in the wild, each team is eager to develop their own suite of quantum computational tools around these new quasiparticles.