Moonshot Thinking For Aging, Mental Health, And Drug Re-Purposing — Dr. Tim R. Peterson.
Washington University in St. Louis.
Smartwatches and other battery-powered electronics would be even smarter if they could run AI algorithms. But efforts to build AI-capable chips for mobile devices have so far hit a wall—the so-called “memory wall” that separates data processing and memory chips that must work together to meet the massive and continually growing computational demands imposed by AI.
“Transactions between processors and memory can consume 95 percent of the energy needed to do machine learning and AI, and that severely limits battery life,” said computer scientist Subhasish Mitra, senior author of a new study published in Nature Electronics.
Now, a team that includes Stanford computer scientist Mary Wootters and electrical engineer H.-S. Philip Wong has designed a system that can run AI tasks faster, and with less energy, by harnessing eight hybrid chips, each with its own data processor built right next to its own memory storage.
The arrival of government-operated autonomous police robots does not look like predictions in science fiction movies. An army of robots with gun arms is not kicking down your door to arrest you. Instead, a robot snitch that looks like a rolling trash can is programmed to decide whether a person looks suspicious —and then call the human police on them. Police robots may not be able to hurt people like armed predator drones used in combat— yet —but as history shows, calling the police on someone can prove equally deadly.
Long before the 1987 movie Robocop, even before Karel Čapek invented the word robot in 1920, police have been trying to find ways to be everywhere at once. Widespread security cameras are one solution—but even a blanket of CCTV cameras couldn’t follow a suspect into every nook of public space. Thus, the vision of a police robot continued as a dream, until now. Whether they look like Boston Dynamics’ robodogs or Knightscope’s rolling pickles, robots are coming to a street, shopping mall, or grocery store near you.
Hyundai and Apple teaming up to challenge Tesla? 😃
Apple and Hyundai plan to sign a deal that would lead to a “beta” version of an Apple electric vehicle as early as 2022, according to a Sunday report from Reuters.
Reuters cited a report from Korea IT News that said the companies are planning to sign a deal by March 2021 to partner on the self-driving electric cars, according to a Sunday report from Korea IT News.
https://www.youtube.com/watch?v=FH_qe_mfF7Q&feature=youtu.be
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Optical micro-combs.
The invention could revolutionize neural networks and neuromorphic processing in general. “This breakthrough was achieved with ‘optical micro-combs’, as was our world-record internet data speed reported in May 2020,” said in a statement Swinburne’s Professor David Moss.
A new deep-learning algorithm could provide advanced notice when systems — from satellites to data centers — are falling out of whack.
When you’re responsible for a multimillion-dollar satellite hurtling through space at thousands of miles per hour, you want to be sure it’s running smoothly. And time series can help.
A time series is simply a record of a measurement taken repeatedly over time. It can keep track of a system’s long-term trends and short-term blips. Examples include the infamous Covid-19 curve of new daily cases and the Keeling curve that has tracked atmospheric carbon dioxide concentrations since 1958. In the age of big data, “time series are collected all over the place, from satellites to turbines,” says Kalyan Veeramachaneni. “All that machinery has sensors that collect these time series about how they’re functioning.”
Using AI and cameras to track and monitor the accumulation of litter in rivers.
Using AI to help people keep the earth clean! 😃
This automated approach can be used in any other city around the world, helping to reduce how much waste enters local waterways and reaches the ocean.
The startup TuSimple is deploying tractor-trailers that drive themselves from pickup to delivery.
(Inside Science) — It took years of painstaking work for Carlos Souza and his colleagues to map out every road in the Brazilian Amazon biome. Official maps of the 4.2 million-square-kilometer region only show roads built by federal and local governments. But by carefully tracing lines on satellite images, the researchers concluded in 2016 that the true length of all the roads combined was nearly 13 times higher.
“When we don’t have a good understanding of how much roadless areas we have on the landscape, we probably will misguide any conservation plans for that territory,” said Souza, a geographer at a Brazil-based environmental nonprofit organization called Imazon.
Now, Imazon researchers have built an artificial intelligence algorithm to find such roads automatically. Currently, the algorithm is reaching about 70% accuracy, which rises to 87%-90% with some additional automated processing, said Souza. Analysts then confirm potential roads by examining the satellite images. Souza presented the research last month at a virtual meeting of the American Geophysical Union.
