Not sure how old this video is. But, Very impressive if it is able to grab random objects at these speeds; although i suspect it needed a lot of training before.
This handy #roboticarm can be trained to catch practically anything. đ€ đȘ
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The chess world was amazed when the computer algorithm AlphaZero learned, after just four hours on its own, to beat the best chess programs built on human expertise. Now a research group at Aarhus University in Denmark has used the very same algorithm to control a quantum computer.
All across the world, numerous research groups are attempting to build a quantum computer. Such a computer would be able to solve certain problems that cannot be solved with current classical computers, even if we combined all these computers in the world into one.
At Aarhus University, researchers share the ambition of building a quantum computer. For this reason, a research group under the direction of Professor Jacob Sherson has just used the computer algorithm AlphaZero to learn to control a quantum system.
The unique relationship between the coordinates in the bore of a Magnetic Resonance Imaging (MRI) scanner and the magnetic field gradients used for MRI allows building a localization system based on the measurement of these gradients. We have previously presented a miniature 3D Hall probe integrated in a low cost, low voltage 0.35ÎŒm CMOS chip from which we were able to measure the magnetic gradient 3D maps of 1.5T and 3T MRI scanners. In this paper, this 3D Hall probe has been integrated in a magnetic tracking device prototype and an algorithm was built to determine the position of the probe. First experimental results show that the probe gives its position with accuracy close to a few millimeters, and that sub-millimeter localization in a one-shot-3ms-measurement should be readily possible. Such a prototype opens the way for the development of MRI compatible real time magnetic tracking systems which could be integrable in surgical tools for MR-guided minimally-invasive surgery.
Itâs been nearly 350 years since Sir Isaac Newton outlined the laws of motion, claiming âFor every action, there is an equal and opposite reaction.â These laws laid the foundation to understand our solar system and, more broadly, to understand the relationship between a body of mass and the forces that act upon it. However, Newtonâs groundbreaking work also created a pickle that has baffled scientists for centuries: The Three-Body Problem.
After using the laws of motion to describe how planet Earth orbits the sun, Newton assumed that these laws would help us calculate what would happen if a third celestial body, such as the moon, were added to the mix. However, in reality, three-body equations became much more difficult to solve.
The breakthrough system combines a glucose sensor, insulin pump and a smart control algorithm to allow Type 1 diabetes patients to continually regulate blood-sugar levels.
The great Elizabeth Parrish on ageing the most sinister disease on earth⊠I hate it when words are used to make aging sound like a normal sickness or a great sickness, Such as grandest??? Or most Important disease??? The decomposer disease that Woman-man has called natural aging all these years has been in reality a clandestine plague so complicated yet so easily seen by the naked eye if certain scholars-textbooks do not get in the wayâŠ
Aging is The Eukaryotic Cellular pandemic plague AEWR has named the Senesonic-Sensonic plague. A disease that causes all of our cells to age nearly at the same rate causing our cells to have to regenerate the day long or the body drops.
WHEN without the Plague our cells individually would live decades instead of mere hours. Causing a bodily effect of Super Longevity-truly Immortality living into millennia once the plague is ended. SO IT IS NOT Lizâs fault, {I met her at RAADFEST 2018 she is a very special mind} but it is the pioneers of biologyâs fault that the Human being has died needlessly for now centuries.
Aging could have been cured 200 and more years ago⊠I search for strong willed men and Women to now join AEWR as investors-partners in agings now end. We have found the causes and yes a very expensive cure we named the Gerevivify Algorithm⊠gerevivify.blogspot.com/ WE HAVE MUCH TO DO⊠r.p.berry & AEWR.
The English philosopher Thomas Hobbes correctly identified the historical state of humans when he said âLife in the state of nature is nasty, brutish and short.â For most of history the average human rarely lived beyond 35 years, but today the average Briton lives beyond 85 years. In this video, Liz argues that this luxury of time helps us realise that we must live with the consequences of our actions â which facilitates caring about our environment and each other. Lizâs organisation, BioViva, intend to accelerate this trend by using advanced medicine to increase health and longevity beyond 100 years for everyone.
Googleâs health research unit said it has developed an artificial-intelligence system that can match or outperform radiologists at detecting breast cancer, according to new research. But doctors still beat the machines in some cases.
The model, developed by an international team of researchers, caught cancers that were originally missed and reduced false-positive cancer flags for patients who didnât actually have cancer, according to a paper published on Wednesday in the journal Nature. Data from thousands of mammograms from women in the U.K. and the U.S. was used to train the AI system.
But the algorithm isnât yet ready for clinical use, the researchers said.
In a study published Jan. 1 in Nature, researchers from Google Health, and from universities in the U.S. and U.K., report on an AI model that reads mammograms with fewer false positives and false negatives than human experts. The algorithm, based on mammograms taken from more than 76,000 women in the U.K. and more than 15,000 in the U.S., reduced false positive rates by nearly 6% in the U.S., where women are screened every one to two years, and by 1.2% in the U.K., where women are screened every three years. The AI model also lowered false negatives by more than 9% in the U.S. and by nearly 3% in the U.K.
Working with medical experts, engineers at Google Health have created an AI model that lowers false positive and false negative rates for mammogram breast cancer screening.
In this age of âbig data,â artificial intelligence (AI) has become a valuable ally for scientists. Machine learning algorithms, for instance, are helping biologists make sense of the dizzying number of molecular signals that control how genes function. But as new algorithms are developed to analyze even more data, they also become more complex and more difficult to interpret. Quantitative biologists Justin B. Kinney and Ammar Tareen have a strategy to design advanced machine learning algorithms that are easier for biologists to understand.
The algorithms are a type of artificial neural network (ANN). Inspired by the way neurons connect and branch in the brain, ANNs are the computational foundations for advanced machine learning. And despite their name, ANNs are not exclusively used to study brains.
Biologists, like Tareen and Kinney, use ANNs to analyze data from an experimental method called a âmassively parallel reporter assayâ (MPRA) which investigates DNA. Using this data, quantitative biologists can make ANNs that predict which molecules control specific genes in a process called gene regulation.
