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Category: robotics/AI – Page 699

Scientists create water-spitting ‘flying dragon’ robot to fight fires

The robot features eight adjustable water jets in its central and head regions, with a flexible firehose directed by a control unit on a trailing wheeled cart.

Functioning at a rate of 6.6 liters per second, the nozzles expel water with a pressure reaching up to one megapascal. At the tip of the hose, a combination of a traditional camera and a thermal imaging camera is integrated, facilitating the identification and location of the fire. This technological integration enhances the Dragon Firefighter’s firefighting capabilities, according to the team.

Learning process

The inaugural testing of the system took place during the opening ceremony of the World Robot Summit 2020 (WRS2020), held in September 2021 in Fukushima. Dragon Firefighter “successfully extinguished [49 min 0 s to 51 min 0 s] the ceremonial flame, consisting of fireballs lit by another robot, at a distance of four meters,” said a statement.

Breakthrough technology amplifies terahertz waves for 6G communication

A team of researchers, led by Professor Hyong-Ryeol Park from the Department of Physics at UNIST has introduced a technology capable of amplifying terahertz (THz) electromagnetic waves by over 30,000 times. This breakthrough, combined with artificial intelligence (AI) based on physical models, is set to revolutionize the commercialization of 6G communication frequencies.

Collaborating with Professor Joon Sue Lee from the University of Tennessee and Professor Mina Yoon from the Oak Ridge National Laboratory, the research team successfully optimized the THz nano-resonator specifically for 6G communication using advanced optimization technology.

The research findings have been published in the online version of Nano Letters.

This first CRISPR gene-editing treatment is just the beginning. Here’s what’s coming next

2023 was the year that CRISPR gene-editing sliced its way out of the lab and into the public consciousness—and American medical system. The Food and Drug Administration recently approved the first gene-editing CRISPR therapy, Casgevy (or exa-cel), a treatment from CRISPR Therapeutics and partner Vertex for patients with sickle cell disease. This comes on the heels of a similar green light by U.K. regulators in a historic moment for a gene-editing technology whose foundations were laid back in the 1980s, eventually resulting in a 2020 Nobel Prize in Chemistry for pioneering CRISPR scientists Jennifer Doudna and Emmanuelle Charpentier.

That decades-long gap between initial scientific spark, widespread academic recognition, and now the market entry of a potential cure for blood disorders like sickle cell disease that afflict hundreds of thousands of people around the world is telling. If past is prologue, even newer CRISPR gene-editing approaches being studied today have the potential to treat diseases ranging from cancer and muscular dystrophy to heart disease, birth more resilient livestock and plants that can grapple with climate change and new strains of deadly viruses, and even upend the energy industry by tweaking bacterial DNA to create more efficient biofuels in future decades. And novel uses of CRISPR, with assists from other technologies like artificial intelligence, might fuel even more precise, targeted gene-editing—in turn accelerating future discovery with implications for just about any industry that relies on biological material, from medicine to agriculture to energy.

With new CRISPR discoveries guided by AI, specifically, we can expand the toolbox available for gene editing, which is crucial for therapeutic, diagnostic, and research applications… but also a great way to better understand the vast diversity of microbial defense mechanisms, said Feng Zhang, another CRISPR pioneer, molecular biologist, and core member at the Broad Institute of MIT and Harvard in an emailed statement to Fast Company.

Timelapse of Future Technology Vol. II (Sci-Fi Documentary)

This timelapse of future technology begins with 2 Starships, launched to resupply the International Space Station. But how far into the future do you want to go?

Tesla Bots will be sent to work on the Moon, and A.I. chat bots will guide people into dreams that they can control (lucid dreams). And what happens when humanity forms a deeper understanding of dark energy, worm holes, and black holes. What type of new technologies could this advanced knowledge develop? Could SpaceX launch 100 Artificial Intelligence Starships, spread across our Solar System and beyond into Interstellar space, working together to form a cosmic internet, creating the Encyclopedia of the Galaxy. Could Einstein’s equations lead to technologies in teleportation, and laboratory grown black holes.

Other topics covered in this sci-fi documentary video include: the building of super projects made possible by advancing fusion energy, the possibilities of brain chips, new age space technology and spacecraft such as a hover bike developed for the Moon in 2050, Mars colonization, and technology predictions based on black holes, biotechnology, and when will humanity become a Kardashev Type 1, and then Type 2 Civilization.

To see more of Venture City and to access the ‘The Future Archive Files’…

• Timelapse of Future Technology (Master List)
• Encyclopedia of the Future (Entries)

…visit my Patreon here: / venturecity.

Continue reading “Timelapse of Future Technology Vol. II (Sci-Fi Documentary)” | >

AI and Us: Overcoming Concerns to Embrace the Future of Technology

As the prominence of Artificial Intelligence (AI) continues to rise in our society, so do the concerns about its implications. Therefore, addressing these fears requires a multi-faceted approach, combining careful design, transparent practices, robust regulation, and thoughtful ethical guidelines.

Below is a list of 20 potential effects AI could have on society, concerns raised by many, and how they could or are currently being overcome.

Ultimately, the goal is to navigate the AI-driven future responsibly, building a society where technology serves human needs effectively and ethically.

First AI Images Extracted From Human Brain Revealed

A group of researchers in Japan have found yet another interesting way to use AI technology. In a recent research project led by a team from the National Institutes for Quantum Science and Technology (QST) and Osaka University, they were able to translate human brain activity to depict mental images of objects, animals, and landscapes. They released pictures from the research, and the results are pretty astounding.

One of the images that the AI technology was able to decode from the brain activity was a vivid depiction of a leopard with detailed features like spots, ears, and more. Another image depicted an airplane. While we have previously had technology that is able to recreate images from brain activity, this is one of the very few studies that were able to make these mental images visible.

Of these previous studies, the images that could be decoded were fairly limited into several categories, like human faces, letters, and numbers. This new AI brain-decoding technology seems to be able to decode a much broader spectrum of images from the human mind. As the researchers in the study point out, “visualizing mental imagery for arbitrary natural images stands as a significant milestone.”

The Biggest Discoveries in Computer Science in 2023

Quanta Magazine’s full list of the major computer science discoveries from 2023.

In 2023, artificial intelligence dominated popular culture — showing up in everything from internet memes to Senate hearings. Large language models such as those behind ChatGPT fueled a lot of this excitement, even as researchers still struggled to pry open the “black box” that describes their inner workings. Image generation systems also routinely impressed and unsettled us with their artistic abilities, yet these were explicitly founded on concepts borrowed from physics.

The year brought many other advances in computer science. Researchers made subtle but important progress on one of the oldest problems in the field, a question about the nature of hard problems referred to as “P versus NP.” In August, my colleague Ben Brubaker explored this seminal problem and the attempts of computational complexity theorists to answer the question: Why is it hard (in a precise, quantitative sense) to understand what makes hard problems hard? “It hasn’t been an easy journey — the path is littered with false turns and roadblocks, and it loops back on itself again and again,” Brubaker wrote. “Yet for meta-complexity researchers, that journey into an uncharted landscape is its own reward.”