Lifeboat Foundation: Safeguarding Humanity
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Unmanned aerial vehicles (UAVs), commonly known as drones, are already used in countless settings to tackle real-world problems. These flying robotic systems can, among other things, help to monitor natural environments, detect fires or other environmental hazards, monitor cities and find survivors of natural disasters.

To tackle all of these missions effectively, UAVs should be able to reliably detect targets and objects of interest in their surroundings. Computer scientists have thus been trying to devise new computational techniques that could enable these capabilities, using deep learning or other approaches.

Researchers at Yunnan University and the Chinese Academy of Sciences recently introduced a new object-detection system based on edge computing. Their proposed system, introduced in the IEEE Internet of Things Journal, could provide UAVs with the ability to spot relevant objects and targets in their surroundings without significantly increasing their power-consumption.

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With the rapid growth of the smart and wearable electronic devices market, smart next-generation energy storage systems that have energy storage functions as well as additional color-changing properties are receiving a great deal of attention. However, existing electrochromic devices have low electrical conductivity, leading to low efficiency in electron and ion mobility, and low storage capacities. Such batteries have therefore been limited to use in flexible and wearable devices.

On August 21, a joint research team led by Professor Il-Doo Kim from the KAIST Department of Materials Science and Engineering (DMSE) and Professor Tae Gwang Yun from the Myongji University Department of Materials Science and Engineering announced the development of a smart electrochromic Zn-ion battery that can visually represent its charging and discharging processes using an electrochromic polymer anode incorporated with a “π-bridge spacer,” which increases electron and efficiency.

Their research was published as an inside cover article for Advanced Materials on August 3 under the title, “A π-Bridge Spacer Embedded Electron Donor-Acceptor Polymer for Flexible Electrochromic Zn-Ion Batteries.”

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Id wonder, and Doubt, if it could handle recoil. Weapons on Dog bots and Mini Uav s i would of liked to see would use electric centrifuge weapons, recoilless weapons, but development on has stalled also.

The brain geniuses at the Pentagon have decided that a good use of the taxpayer dollar is to attach rifles onto robot dogs, because why the hell not, right?

As Military.com reports, a spokesperson for the US Army said that the branch is considering arming remote-controlled robot dogs with state-of-the-art rifles as part of its plan to “explore the realm of the possible” in the future of combat.

The vision, as you’ve probably gathered, is pretty simple: to mount a rifle onto a robotic dog for domestic tasks across the military — and send it out into an unspecified battlefield.

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Innovative technology that creates ultra-thin layers of human cells in tube-like structures could spur development of lifelike blood vessels and intestines in the lab.

The technique, known as RIFLE – rotational internal flow layer engineering – enables the construction of separate layers as delicate as one cell thick.

Such versatility is crucial to developing accurate human models of layered tubular tissue for use in research, offering an important alternative to animal models, experts say.

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What is an AI Graphic Design Tool?

Artificial intelligence (AI) models human intelligence processes in computers and computer-controlled robots. This enables computer systems to undertake arduous jobs, allowing people to concentrate on more vital matters.

As a result, the need for AI integrations in the workplace has grown over time. In fact, researchers project that the global AI software industry will be worth $791.5 billion by 2025.

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In a Nutshell…

Conclusively, the partnership between NASA and DARPA to test a nuclear-powered rocket for future Mars missions marks a significant milestone in space exploration. The use of a nuclear thermal rocket engine offers several benefits including faster transit times, increased science payload capacity, and higher power for instrumentation and communication. These advancements will play a crucial role in helping NASA meet its Moon-to-Mars objectives and establish a space transportation capability for the Earth-Moon economy. Moreover, the successful demonstration of the DRACO program could have far-reaching implications for future space exploration efforts. The nuclear thermal propulsion technology could be used for not just crewed missions to Mars but also for other deep space missions, enabling humans to journey faster than ever before. This collaboration between NASA and DARPA brings together the best of both worlds, and the successful outcome of this project will be a major achievement in advancing space technology. The future looks bright for the space industry, and with more innovations like the DRACO program, we may be able to explore even more of our universe in the years to come.

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AI systems are increasingly being employed to accurately estimate and modify the ages of individuals using image analysis. Building models that are robust to aging variations requires a lot of data and high-quality longitudinal datasets, which are datasets containing images of a large number of individuals collected over several years.

Numerous AI models have been designed to perform such tasks; however, many encounter challenges when effectively manipulating the age attribute while preserving the individual’s facial identity. These systems face the typical challenge of assembling a large set of training data consisting of images that show individual people over many years.

The researchers at NYU Tandon School of Engineering have developed a new artificial intelligence technique to change a person’s apparent age in images while ensuring the preservation of the individual’s unique biometric identity.

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