MIT and UC San Diego’s Open-TeleVision tech enhances remote robotic control by integrating human intuition with VR.
Category: robotics/AI – Page 329
A new optical system for neural networks has been developed by the Max Planck Institute, offering a simpler and more energy-efficient alternative to current methods.
This system uses light transmission to perform computations, reducing the complexity and energy demands associated with traditional neural networks.
Optical Neural Networks
Researchers from MIT and elsewhere developed an easy-to-use tool that enables someone to perform complicated statistical analyses on tabular data using just a few keystrokes. Their method combines probabilistic AI models with the programming language SQL to provide faster and more accurate results than other methods.
South Korea is poised to enhance its defense capabilities with the launch of a revolutionary laser-based anti-aircraft weapon. Hanwha Aerospace, a leading South Korean defense firm, has begun production following a contract signed in late June with the Defense Acquisition Program Administration (DAPA). The contract, worth KRW100 billion (USD72.5 million), mandates the delivery of the ‘Laser Based Anti-Aircraft Weapon Block-I’ systems to the Republic of Korea (RoK) Armed Forces starting later in 2024. This advanced weapon system, developed since 2019 with an investment of KRW87.1 billion (approximately USD63 million), is set to bolster South Korea’s defense against emerging threats, particularly from North Korea.
DAPA has described the Block-I system as a new-concept future weapon system that employs a laser generated from an optical fiber to neutralize targets. The weapon is engineered to accurately strike small unmanned aerial vehicles (UAVs) and multicopters at close range. This innovative technology is silent, ammunition-free, and operates solely on electricity, making it a cost-effective solution, with each firing costing about KRW2,000. The laser anti-aircraft weapon (Block-I) represents a significant advancement in our defense capabilities. If the output is improved in the future, it could become a game-changing asset on the battlefield, capable of responding to aircraft and ballistic missiles.
Dubbed the “StarWars Project,” the weapon’s development is a crucial element of South Korea’s strategy to modernize its defense systems amidst North Korea’s increasing weapons advancements. The laser beam emitted by the weapon is invisible to the human eye and produces no sound, adding to its tactical advantages. Upon deployment, South Korea will be the first country to operate this type of advanced laser weapon system, marking a significant milestone in military technology. This strategic development underscores South Korea’s commitment to maintaining a robust and modern defense posture in an increasingly complex security environment.
Quantum Systems, the Munich-based manufacturer of dual-use reconnaissance drones that use multi-sensor technology to collect data for government agencies and commercial users, confirms for the first time the deployment of a previously unreleased AI sensor upgrade of the type “Receptor AI” in Ukraine. The new upgrade kit is based on a Jetson Orin Nvidia chip and several sensors for the Vector reconnaissance drone. The further development enables optical navigation during the day and at night and in poor visibility conditions, as well as automated AI-supported object recognition and identification. In times of electronic warfare, navigation is the biggest challenge for the use of drones.
“We are implementing the upgrade without any weight changes and with the same range. We are designing these adaptations without fundamental changes to the existing platform architecture,” says Daniel Kneifel, Director of Software Engineering at Quantum Systems.
“We are demonstrating that AI does not have to be an abstract topic, but offers tangible benefits in use. For Quantum Systems, the combination of hardware and software is crucial to being able to offer market-leading solutions in the field of aerial intelligence,” says Sven Kruck, CRO and Managing Director, Quantum Systems.
You won’t have a job, but you will beat illness, boost your IQ and cheat death, says a futurologist.
A University of Maryland spinoff firm, Wave Engine Corporation, has created a simpler, more affordable jet propulsion system for drones.
The digitally controlled modern-day pulsejet engine features no moving parts and claims to offer major improvements in the cost reduction and rapid production of future jet-powered aircraft.
In March, the Baltimore-based company demonstrated the full flight capability of its J-1 engine on an Unmanned Aerial Vehicle (UAV).
World’s smallest violin for AI execs.
Researchers are ringing the alarm bells, warning that companies like OpenAI and Google are rapidly running out of human-written training data for their AI models.
And without new training data, it’s likely the models won’t be able to get any smarter, a point of reckoning for the burgeoning AI industry.
“There is a serious bottleneck here,” AI researcher Tamay Besiroglu, lead author of a new paper to be presented at a conference this summer, told the Associated Press. “If you start hitting those constraints about how much data you have, then you can’t really scale up your models efficiently anymore.”
To put the forecasted demand into context, consider this: A recent MIT study found that a single data center consumes electricity equivalent to 50,000 homes. Estimates indicate that Microsoft, Amazon, and Google operate about 600 data centers in the U.S. today…
Arguments exist that by 2030, 80% of renewable power sources will fulfill electricity demand. For reference, the U.S. generated roughly 240 billion kilowatt hours of solar and 425 billion kilowatt hours of wind, totaling 665 billion kilowatt hours in 2023. Assuming a 50/50 split between wind and solar, that scenario implies that, to satisfy the U.S. electricity demand that adequately facilitates AI competitiveness, wind and solar will have to generate approximately 3.4 trillion kilowatt hours of electricity each. That is more than a ten-fold increase over the next five years. The EIA highlights that the U.S. planned utility-scale electric-generating capacity addition in 2023 included 29 million kilowatts of solar (54% of the total) and 6 million kilowatts of wind (11% of the total), which pales in comparison to the estimated amount required.
It just doesn’t get much more clear; renewables cannot begin to supply the energy needed for AI data centers. Only fossil fuels and nuclear can get the job done. It’s that simple. AI is not something global elites are going to let slide by. They’ve had a good run with the Big Green Grift but those days are going to gradually (maybe not so gradually) come to an end, as the demand for energy to power AI forces a reconsideration.
Scientists propose a new way of implementing a neural network with an optical system which could make machine learning more sustainable in the future. The researchers at the Max Planck Institute for the Science of Light have published their new method in Nature Physics, demonstrating a method that is much simpler than previous approaches.