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Category: robotics/AI – Page 104

From social to biological networks: New algorithm uncovers key proteins in human disease

Researchers at Ben-Gurion University of the Negev have developed a machine-learning algorithm that could enhance our understanding of human biology and disease. The new method, Weighted Graph Anomalous Node Detection (WGAND), takes inspiration from social network analysis and is designed to identify proteins with significant roles in various human tissues.

Proteins are essential molecules in our bodies, and they interact with each other in , known as (PPI) networks. Studying these networks helps scientists understand how proteins function and how they contribute to health and disease.

Prof. Esti Yeger-Lotem, Dr. Michael Fire, Dr. Jubran Juman, and Dr. Dima Kagan developed the algorithm to analyze these PPI networks to detect “anomalous” proteins—those that stand out due to their unique pattern of weighted interactions. This implies that the amount of the protein and its protein interactors is greater in that particular network, allowing them to carry out more functions and drive more processes. This also indicates the great importance that these proteins have in a particular network, because the body will not waste energy on their production for no reason.

Kawasaki Unveils Japan’s Future of Transport 😳

Kawasaki Unveils Japan’s Future of Transport | #breakingnews #Robotics.

🚨 Japan’s Kawasaki has unveiled a groundbreaking concept robot called CORLEO that could revolutionize future transport.

🔹 Designed to resemble a lion for navigating rough and mountainous terrains.
🔹 Powered by a hydrogen engine—eco-friendly innovation.
🔹 Controlled by shifting body weight, similar to horseback riding.
🔹 A bold step into the future of personal robotic transport.

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Kawasaki CORLEO robot, Japan transport robot, hydrogen-powered robot, robotic lion vehicle, futuristic mobility, mountain transport robot, robotics innovation Japan.

📢 Hashtags:
#ThriveNews #Japan #Robotics #Kawasaki #CORLEO #FutureTransport #Innovation #TechNews #HydrogenPower

Aiming for Lighter Light Sails

Norte and his colleagues initially considered patterning the light sails with an array of identical circular holes, but such a pattern would reduce the overall effect of the powering laser. As the sail speeds up and moves away from the laser, the wavelength it preferentially reflects will shift because of the Doppler effect, and the sail will subsequently receive less of a push. What is needed instead is a pattern that can handle Doppler-shift changes while remaining highly reflective.

To find the optimal pattern, the researchers turned to a neural network, which predicted an optimal shape that is oblong rather than circular. “It looks like a potato,” says Miguel Bessa of Brown University, Rhode Island, who led the theory side of the project. Specifically, the team arranged several potato shapes in a repeating five-neighbor pattern, or pentagonal lattice. The potato-shaped arrangement allows the system to respond to a broader range of wavelengths without having to make it thicker and thus heavier.

The researchers are now working on increasing the size of their sail and looking into ways to test how well it flies. Norte notes that the light sail is just a means to accelerate the nanospacecraft, which will include a microchip, cameras, and other instruments. All those parts need to be miniaturized so that they weigh less than one gram total. “We are really trying to use nanotechnology to go faster and further than we have been able to with traditional spacecraft,” Norte says.

3D-printed open-source robot offers accessible solution for materials synthesis

A team of researchers led by Professor Keisuke Takahashi at the Faculty of Science, Hokkaido University, have created FLUID (Flowing Liquid Utilizing Interactive Device), an open-source robotic system constructed using a 3D printer and off-the-shelf electronic components.

To demonstrate FLUID’s capabilities, the team used the robot to automate the co-precipitation of cobalt and nickel, creating binary materials with precision and efficiency.

“By adopting open source, utilizing a 3D printer, and taking advantage of commonly-available electronics, it became possible to construct a functional robot that is customized to a particular set of needs at a fraction of the costs typically associated with commercially-available robots,” said Mikael Kuwahara, the lead author of the study.

Getting an all-optical AI to handle non-linear math

A standard digital camera used in a car for stuff like emergency braking has a perceptual latency of a hair above 20 milliseconds. That’s just the time needed for a camera to transform the photons hitting its aperture into electrical charges using either CMOS or CCD sensors. It doesn’t count the further milliseconds needed to send that information to an onboard computer or process it there.

A team of MIT researchers figured that if you had a chip that could process photons directly, you could skip the entire digitization step and perform calculations with the photons themselves, which has the potential to be mind-bogglingly faster.

“We’re focused on a very specific metric here, which is latency. We aim for applications where what matters the most is how fast you can produce a solution. That’s why we are interested in systems where we’re able to do all the computations optically,” says Saumil Bandyopadhyay, an MIT researcher. The team implemented a complete deep neural network on a photonic chip, achieving a latency of 410 picoseconds. To put that in perspective, Bandyopadhyay’s chip could process the entire neural net it had onboard around 58 times within a single tick of the 4 GHz clock on a standard CPU.

Instead of sensing photons and processing the results, why not process the photons?

Fake job seekers are flooding U.S. companies that are hiring for remote positions, tech CEOs say

That’s because the candidate, whom the firm has since dubbed “Ivan X,” was a scammer using deepfake software and other generative AI tools in a bid to get hired by the tech company, said Pindrop CEO and co-founder Vijay Balasubramaniyan.

“Gen AI has blurred the line between what it is to be human and what it means to be machine,” Balasubramaniyan said. “What we’re seeing is that individuals are using these fake identities and fake faces and fake voices to secure employment, even sometimes going so far as doing a face swap with another individual who shows up for the job.”

Companies have long fought off attacks from hackers hoping to exploit vulnerabilities in their software, employees or vendors. Now, another threat has emerged: Job candidates who aren’t who they say they are, wielding AI tools to fabricate photo IDs, generate employment histories and provide answers during interviews.