How to create a Robotic Arm under the control of the new KRIA Robotic Starter Kit By Adam Taylor.
Category: robotics/AI – Page 1,387
Smaller, Cheaper Lidar With New Chip-Based Beam Steering Device
Researchers have developed a new chip-based beam steering technology that provides a promising route to small, cost-effective, and high-performance lidar systems. Lidar, or light detection and ranging, uses laser pulses to acquire 3D information about a scene or object. It is used in a wide range of applications such as autonomous driving, 3D holography, biomedical sensing, free-space optical communications, and virtual reality.
“Optical beam steering is a key technology for lidar systems, but conventional mechanical-based beam steering systems are bulky, expensive, sensitive to vibration, and limited in speed,” said research team leader Hao Hu from the Technical University of Denmark. “Although devices known as chip-based optical phased arrays (OPAs) can quickly and precisely steer light in a non-mechanical way, so far, these devices have had poor beam quality and a field of view typically below 100 degrees.”
The Physics of Self-Replication and Nanotechnology
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Cryogeomorphic Characterization of Shadowed Regions in the Artemis Exploration Zone
No more dark side of the Moon?
An international research team headed by ETH Zurich has investigated the permanently shadowed regions of the Moon with the use of artificial intelligence. Future lunar missions will be able to find acceptable spots thanks to the knowledge they have gained about the region’s physical properties.
The research was published in Geophysical Research Letters on August 26.
We produce the first high-signal-to-noise ratio and-resolution orbital images over 44 shadowed regions within the Artemis exploration zone using an AI tool.
Northrop Grumman’s RQ-4 RangeHawks Embark on New Mission
It will be reconfigured to meet testing needs.
The giant drone, RQ-4 RangeHawk, will soon be used to support the development of hypersonic missiles in the U.S., its manufacturer, Northrop Grumman, said in a press release.
Hypersonic missiles are the newest frontier in the weapons race, with countries like Russia and North Korea laying claims to have successfully demonstrated this technology. The U.S. hypersonic missile program has faced a few hiccups with repetitive test failures. Last month, the U.S. Air Force confirmed that its Air-launched Rapid Response Weapon (ARRW) had been successfully tested, almost after a year after similar claims from Russia.
GRAND FORKS, N.D. – Aug. 24, 2022 – Northrop Grumman Corporation’s (NYSE: NOC) RQ-4 RangeHawk is poised to support the SkyRange program’s U.S. hypersonic missile flight tests from its Grand Sky facility near Grand Forks, North Dakota. SkyRange is the Department of Defense Test Resource Management Center’s (TRMC) unmanned high-altitude, long-endurance, responsive mobile flight test system.
In support of the SkyRange initiative, Block 20 and 30 RQ-4B Global Hawk aircraft are being transferred to TRMC to be reconfigured into RangeHawks. The conversion will integrate advanced payloads to equip the aircraft with the capability to support the testing of hypersonic vehicles and other long-range weapons. RangeHawks provide over-the-horizon altitude, endurance and flexibility, which are critical for collecting telemetry and other data to monitor the vehicle during flight tests. Increasing the capacity of hypersonic vehicle testing furthers research and development necessary to remain competitive in the global landscape.
“Our RQ-4 RangeHawks will support the emerging class of hypersonic weapons and provide a combination of range, endurance and payload capacity,” said Jane Bishop, vice president and general manager, global surveillance, Northrop Grumman. “These aircraft will continue their role in vital national security missions while enabling us to bring premier aircraft design, modification, operations and sustainment work to the Grand Forks community.”
Scaling up the production of liquid metal circuits
Carnegie Mellon mechanical engineering researchers have developed a new scalable and reproducible manufacturing technique that could accelerate the mainstream adoption and commercialization of soft and stretchable electronics.
The next generation of robotic technology will produce soft machines and robots that are safe and comfortable for direct physical interaction with humans and for use in fragile environments. Unlike rigid electronics, soft and stretchable electronics can be used to create wearable technologies and implantable electronics where safe physical contact with biological tissue and other delicate materials is essential.
Soft robots that safely handle delicate fruits and vegetables can improve food safety by preventing cross-contamination. Robots made from soft materials can brave the unexplored depths of the sea to collect delicate marine specimens. And the many biomedical applications for soft robots include wearable and assistive devices, prostheses, soft tools for surgery, drug delivery devices, and artificial organ function.
ROBE Array could let small companies access popular form of AI
A breakthrough low-memory technique by Rice University computer scientists could put one of the most resource-intensive forms of artificial intelligence—deep-learning recommendation models (DLRM)—within reach of small companies.
DLRM recommendation systems are a popular form of AI that learns to make suggestions users will find relevant. But with top-of-the-line training models requiring more than a hundred terabytes of memory and supercomputer-scale processing, they’ve only been available to a short list of technology giants with deep pockets.
Rice’s “random offset block embedding array,” or ROBE Array, could change that. It’s an algorithmic approach for slashing the size of DLRM memory structures called embedding tables, and it will be presented this week at the Conference on Machine Learning and Systems (MLSys 2022) in Santa Clara, California, where it earned Outstanding Paper honors.
Scientists Have Created Microrobots That Can Automatically Brush and Floss Your Teeth
Researchers from the University of Pennsylvania demonstrated in a proof-of-concept study that a hands-free device could successfully automate the treatment and removal of dental plaque and bacteria that cause tooth decay.
In the future, a shape-shifting robotic microswarm may serve as a toothbrush, rinse, and dental floss all in one. The technology, created by a multidisciplinary team at the University of Pennsylvania, has the potential to provide a brand-new, automated method for carrying out the repetitive but important daily duties of brushing and flossing. For people who lack the manual dexterity to efficiently clean their teeth alone, this system could be extremely helpful.
These microrobots are composed of iron oxide nanoparticles with catalytic and magnetic properties. Researchers were able to control their movement and configuration using a magnetic field to either produce bristle-like structures that remove dental plaque from the wide surfaces of teeth or elongated threads that can slide between teeth like a piece of floss. In both situations, the nanoparticles are driven by a catalytic reaction to release antimicrobials that eliminate harmful oral bacteria on site.
Robert Long–Artificial Sentience, Digital Minds
Robert Long is a research fellow at the Future of Humanity Institute. His work is at the intersection of the philosophy of AI Safety and consciousness of AI. We talk about the recent LaMDA controversy, Ilya Sutskever’s slightly conscious tweet, the metaphysics and philosophy of consciousness, artificial sentience, and how a future filled with digital minds could get really weird.
Audio & transcript: https://theinsideview.ai/roblong.
Michaël: https://twitter.com/MichaelTrazzi.
Robert: https://twitter.com/rgblong.
Robert’s blog: https://experiencemachines.substack.com.
OUTLINE
00:00:00 Intro.
00:01:11 The LaMDA Controversy.
00:07:06 Defining AGI And Consciousness.
00:10:30 The Slightly Conscious Tweet.
00:13:16 Could Large Language Models Become Conscious?
00:18:03 Blake Lemoine Does Not Negotiate With Terrorists.
00:25:58 Could We Actually Test Artificial Consciousness?
00:29:33 From Metaphysics To Illusionism.
00:35:30 How We Could Decide On The Moral Patienthood Of Language Models.
00:42:00 Predictive Processing, Global Workspace Theories and Integrated Information Theory.
00:49:46 Have You Tried DMT?
00:51:13 Is Valence Just The Reward in Reinforcement Learning?
00:54:26 Are Pain And Pleasure Symetrical?
01:04:25 From Charismatic AI Systems to Artificial Sentience.
01:15:07 Sharing The World With Digital Minds.
01:24:33 Why AI Alignment Is More Pressing Than Artificial Sentience.
01:39:48 Why Moral Personhood Could Require Memory.
01:42:41 Last thoughts And Further Readings.
Quantum AI Breakthrough: New Theorem Shrinks Need for Training Data
Aug. 24, 2022 — Training a quantum neural network requires only a small amount of data, according to a new proof that upends previous assumptions stemming from classical computing’s huge appetite for data in machine learning, or artificial intelligence. The theorem has several direct applications, including more efficient compiling for quantum computers and distinguishing phases of matter for materials discovery.
“Many people believe that quantum machine learning will require a lot of data. We have rigorously shown that for many relevant problems, this is not the case,” said Lukasz Cincio, a quantum theorist at Los Alamos National Laboratory and co-author of the paper containing the proof published in the journal Nature Communications. “This provides new hope for quantum machine learning. We’re closing the gap between what we have today and what’s needed for quantum advantage, when quantum computers outperform classical computers.”
“The need for large data sets could have been a roadblock to quantum AI, but our work removes this roadblock. While other issues for quantum AI could still exist, at least now we know that the size of the data set is not an issue,” said Patrick Coles, a quantum theorist at the Laboratory and co-author of the paper.