As I sit down in Nissan's simulator, I prepare myself for the fact that a cohort of researchers could scrutinize my skills as a wheelman with more rigor than the most aggravating backseat driver. And, I accept that this process involves wearing what looks like a too-small, sideways bicycle helmet, which holds 11 electrodes poking through my hair. "For each corner, there'll be an evaluation of your driving smoothness," says Lucian Gheorghe, the Nissan researcher in charge of this rig. Gheorghe is interested in motor related potentials, a specific pattern of activity the brain creates as it prepares to move a limb. It takes half a second for the body to translate that signal to the wave of an arm or kick of a leg, and Nissan wants to exploit the gap.
To further enhance its research capabilities Eco Marine Power announced today that it will begin using the Neural Network Console provided by Sony Network Communications Inc., as part of a strategy to incorporate Artificial Intelligence (AI) into various ongoing ship related technology projects including the further development of the patented Aquarius MRE (Marine Renewable Energy) and EnergySail. The Neural Network Console is an integrated development environment using deep learning for AI creation and has been used in deep learning applied technology development within Sony since 2015. Various functions are included such as recognition technology and a full-fledged GUI (graphical user interface) and these allow for deep learning programs to be developed. Deep learning refers to a form of machine learning that uses neural networks modelled after the human brain and is notable for its high versatility with applications in a wide variety of fields including signal processing, and robotics. An initial area of focus will be on studying how the Neural Network Console and AI can assist with the development of the automated control system for EMP's EnergySail.
Machine learning has returned with a vengeance. I still remember the dark days of the late '80s and '90s, when it was pretty clear that the current generation of machine-learning algorithms didn't seem to actually learn much of anything. Then big data arrived, computers became chess geniuses, conquered Go (twice), and started recommending sentences to judges. In most of these cases, the computer had sucked up vast reams of data and created models based on the correlations in the data. But this won't work when there aren't vast amounts of data available.
In a slightly disconcerting vision of things that may come to pass, transmission of brain waves through the Internet to manipulate devices was demonstrated in a study in 2014. Synaptic Interface – Taking it a step further, images are directly projected into a viewer's brain. Kymogen Wave Energy Generator – A low cost, clean method of producing energy from the constant power of oceanic waves is the promise of the Kymogen Wave Energy Generator. Orbital Solar Energy Harvesters – Solar power is nothing new but the wireless power transmission of energy from a solar energy collecting satellite is ground breaking.
You'll receive these courses in your bundle: Deep Learning: Convolutional Neural Networks in Python: Convolutional Neural Networks (CNNs) are the engine behind image recognition…find out how it works. Unsupervised Deep Learning in Python: Learn about encoders that process, then reassess information to find new connections to make computers even smarter. Natural Language Processing with Deep Learning in Python: Explore advanced natural language processing, the computer science and AI study that links computer and human languages. Natural Language Processing with Deep Learning in Python: Explore advanced natural language processing, the computer science and AI study that links computer and human languages.
The safety of critical maritime operations and the power output of wave energy converters can both be improved by measuring and predicting the shape and motion of sea waves. You will join a growing machine learning group at Exeter, working directly with Dr Jacqueline Christmas in collaboration with Prof Michael Belmont. For informal enquiries about the project, please contact Dr Jacqueline Christmas, J.T.Christmas@exeter.ac.uk. You should have strong programming skills, an aptitude for mathematics, and an enthusiasm for research into image processing and machine learning.