Lifeboat Foundation

Researchers at the University of California, Los Angeles (UCLA) and the California NanoSystems Institute in Los Angeles have recently developed a soft swimming robot based on a self-sustained hydrogel oscillator. This robot, presented in a paper published in Science Robotics, operates under constant light input without the need for a battery.

“When I shone light on a soft, fast responsive hydrogel pillar, I observed the pillar started to oscillate around the optical beam,” Yusen Zhao, a Ph.D. student involved in the research, said. “It looked very intriguing to me, and I wondered: How can a constant input produce intermittent output? Under what conditions does the oscillation happen? Would it be powerful enough to propel and swim in water, and eventually lead to solar sails? With these questions, I continued systematic studies aiming to achieve these objectives.”

Zhao and his colleagues developed a soft oscillator made of a light-responsive soft gel, which is molded into the shape of a pillar or strip. When light hits a spot of this gel pillar, it is automatically absorbed and converted into heat. The locally heated spot on the robot causes it to eject some of its water and shrink in volume, resulting in its tail bending towards the light source.

Machine learning techniques have so far proved to be very promising for the analysis of data in several fields, with many potential applications. However, researchers have found that applying these methods to quantum physics problems is far more challenging due to the exponential complexity of many-body systems.

Once the realm of science fiction, voice-mimicking software is now “well within the range of any lay criminal who’s got creativity to spare,” one cybersecurity expert said.

“The creation of AGI will be the most important technological development in human history, with the potential to shape the trajectory of humanity,” said OpenAI CEO Sam Altman.

Check out the CRAZIEST Cases Of MIND CONTROL In Nature! From brain controlled robot beetles to ants getting mind controlled by parasitic wasps, this top 10 list of amazing mind control techniques will shock you!

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On this week’s episode of Futuris, Euronews visits a hazelnut orchard in Italy to see how the new generation of robots can help farmers and agronomists make agriculture cheaper and more environmentally friendly.

Computer vision is one of the most popular applications of artificial intelligence. Image classification, object detection and object segmentation are some of the use cases of computer vision-based AI. These techniques are used in a variety of consumer and industrial scenarios. From face recognition-based user authentication to inventory tracking in warehouses to vehicle detection on roads, computer vision is becoming an integral part of next-generation applications.

Computer vision uses advanced neural networks and deep learning algorithms such as Convolutional Neural Networks (CNN), Single Shot Multibox Detector (SSD) and Generative Adversarial Networks (GAN). Applying these algorithms requires a thorough understanding of neural network architecture, advanced mathematics and image processing techniques. For an average ML developer, CNN remains to be a complex branch of AI.

Apart from the knowledge and understanding of algorithms, CNNs demand high end, expensive infrastructure for training the models, which is out of reach for most of the developers.

Consultants at Gartner recently calculated that in 2021 “ai augmentation” will create $2.9trn of “business value” and save 6.2bn man-hours globally. A survey by McKinsey last year estimated that ai analytics could add around $13trn, or 16%, to annual global gdp by 2030. Retail and logistics stand to gain most.

Two surprising leaders have emerged from the pack.

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During Amazon’s all-hands meeting in March, CEO Jeff Bezos stated that he is fascinated by the emerging trends in the auto industry. Bezos noted that it was this fascination that ultimately played a part in Amazon’s hefty $700 million investment in electric truck startup Rivian Automotive back in February.

“If you think about the auto industry right now, there’s so many things going on with Uber-ization, electrification, the connected car — so it’s a fascinating industry. It’s going to be something very interesting to watch and participate in, and I’m very excited about that whole industry,” Bezos said.

Bezos’ optimism for emerging industries extends beyond the electric car market. Apart from Rivian, Amazon has also invested in self-driving startup Aurora, hinting that the CEO is also looking to capitalize on autonomous driving technology for the e-commerce giant’s operations in the future. If its investment in Aurora pans out, for example, Amazon would likely gain an optimized solution that would allow the company to deliver shipments to its customers using self-driving machines.