Sony Corp. has created one of the hottest gadgets of the year in the PlayStation 5, but its launch has been marred by scalpers who are buying up scarce supplies and threatening the long-term health of the company’s most important product.
“When was the last time you lost a correction signal when running a tractor or combine in the field? In Russia, that’s an even bigger problem, but because of that, a new tool is being deployed — a vision-based guidance system. That’s where Cognitive Agro Pilot comes in. “This system detects obstacles, including people, animals, metallic objects and stones along its way, without GPS navigation and RTK positioning,” says Olga Uskova, CEO, Cognitive, based in Moscow. “Cognitive Agro Pilot can operate in territories with a weak satellite signal.” The company has developed a system that uses a high-definition camera in an armored housing that can “see” ahead. Tied to an artificial intelligence system, the systems provide precision guidance. This is more than following a row.”
Russian firm Cognitive Agro Pilot is using computer vision and machine learning for precision guidance.
(Checks math.)
Scientists have new evidence that Earth’s many periodic mass extinctions follow a cycle of about 27 million years, connecting the five major mass extinctions with more minor ones occurring throughout Earth’s life-fostering timespan. The artificial intelligence analysis could also shift how evolutionary scientists think about the aftermath of mass extinctions.
Connecticut-based company LiquidPiston is developing a portable generator for the US Army that uses its X-Engine, a fresh and extremely powerful take on the rotary engine that’ll deliver as much power as the Army’s current-gen-set at one-fifth the size.
We’ve written a few times before about the fascinating LiquidPiston rotary engine. It’s not a Wankel – indeed, it’s closer to an inside-out Wankel – and with only two moving parts, it’s able to deliver extraordinary power density at up to 1.5 horsepower per pound (0.45 kg).
Continue reading “LiquidPiston’s ‘inside-out’ rotary X-Engine wins Army research contract” »
The flight marks the first known time an AI has to been used to control a US military aircraft.
“This is the first time this has ever happened,” assistant Air Force Secretary Will Roper told the newspaper.
The AI took care of some highly specific tasks and was never in control of actually flying the plane — or, notably, any weapon systems.
There is no doubt that the future of transport is autonomous. Tesla is already rolling out a beta version of full self driving and that will be released fully in 2021, I am sure. From robotaxis to freight transport, our lives will get easier, cheaper and more convenient and for those with current mobility issues, the change will be even greater. Here I look at some of the ways that all our lives, the environment and the places we live will change…for the better. I cannot wait…can you?
In The Mind Blowing Future Of Transportation — How Self Driving Cars Will Change The World, I will look at the future of autonomous vehicles and how they will change our world…for the better.
Continue reading “How Self Driving Cars Will Change The World” »
Previous research has shown that eye contact, in human-human interaction, elicits increased affective and attention related psychophysiological responses. In the present study, we investigated whether eye contact with a humanoid robot would elicit these responses. Participants were facing a humanoid robot (NAO) or a human partner, both physically present and looking at or away from the participant. The results showed that both in human-robot and human-human condition, eye contact versus averted gaze elicited greater skin conductance responses indexing autonomic arousal, greater facial zygomatic muscle responses (and smaller corrugator responses) associated with positive affect, and greater heart deceleration responses indexing attention allocation. With regard to the skin conductance and zygomatic responses, the human model’s gaze direction had a greater effect on the responses as compared to the robot’s gaze direction. In conclusion, eye contact elicits automatic affective and attentional reactions both when shared with a humanoid robot and with another human.
Grasping objects is something primates do effortlessly, but how does our brain coordinate such a complex task? Multiple brain areas across the parietal and frontal cortices of macaque monkeys are essential for shaping the hand during grasping, but we lack a comprehensive model of grasping from vision to action. In this work, we show that multiarea neural networks trained to reproduce the arm and hand control required for grasping using the visual features of objects also reproduced neural dynamics in grasping regions and the relationships between areas, outperforming alternative models. Simulated lesion experiments revealed unique deficits paralleling lesions to specific areas in the grasping circuit, providing a model of how these areas work together to drive behavior.
One of the primary ways we interact with the world is using our hands. In macaques, the circuit spanning the anterior intraparietal area, the hand area of the ventral premotor cortex, and the primary motor cortex is necessary for transforming visual information into grasping movements. However, no comprehensive model exists that links all steps of processing from vision to action. We hypothesized that a recurrent neural network mimicking the modular structure of the anatomical circuit and trained to use visual features of objects to generate the required muscle dynamics used by primates to grasp objects would give insight into the computations of the grasping circuit. Internal activity of modular networks trained with these constraints strongly resembled neural activity recorded from the grasping circuit during grasping and paralleled the similarities between brain regions.
