In order to bridge the gap between AI researchers and medical professionals we developed a very accessible free prototype system which can be used by medical professionals to understand the reality of Deep Learning tools for chest X-ray diagnostics.
Google’s parent firm, Alphabet, has long been working on multipurpose robots.
The fleet of “Everyday Robots,” as they are colloquially called, has recently been upgraded with sophisticated AI language systems so that they can better comprehend human speech.
Continue reading “Google Adds AI Language Skills To Alphabet’s Helper Robots” »
A new study by theoretical physicists has made progress toward identifying how particles and cells give rise to large-scale dynamics that we experience as the passage of time.
A central feature of how we experience the world is the flow of time from the past to the future. But it is a mystery precisely how this phenomenon, known as the arrow of time, arises from the microscopic interactions among particles and cells. Researchers at the CUNY Graduate Center Initiative for the Theoretical Sciences (ITS) are helping to unravel this enigma with the publication of a new paper in the journal Physical Review Letters. The findings could have important implications in a wide range of disciplines, including physics, neuroscience, and biology.
Fundamentally, the arrow of time emerges from the second law of thermodynamics. This is the principle that microscopic arrangements of physical systems tend to increase in randomness, moving from order to disorder. The more disordered a system becomes, the more difficult it is for it to find its way back to an ordered state, and the stronger the arrow of time. In short, the universe’s propensity toward disorder is the fundamental reason why we experience time flowing in one direction.
“I believe we can train the algorithm not only to picture accurately a face you’re looking at, but also any face you imagine vividly, such as your mother’s,” explains Dado.
“By developing this technology, it would be fascinating to decode and recreate subjective experiences, perhaps even your dreams,” Dado says. “Such technological knowledge could also be incorporated into clinical applications such as communicating with patients who are locked within deep comas.”
Continue reading “‘Mind-Reading’ Technology Translates Brainwaves into Photos” »
The success of COVID-19 vaccines is a great example of gene medicine’s tremendous potential to prevent viral infections. One reason for the vaccines’ success is their use of lipid nanoparticles, or LNPs, to carry delicate messenger RNA to cells to generate and boost immunity. LNPs—tiny fat particles—have become increasingly popular as a carrier to deliver various gene-based medicines to cells, but their use is complicated because each LNP must be tailored specifically for the therapeutic payload it carries.
A team led by Hai-Quan Mao, a Johns Hopkins materials scientist, has created a platform that shows promise to speed up the LNP design process and make it more affordable. The new approach also can be adapted to other gene therapies.
“In a nutshell, what we have done is creating a method that screens lipid nanoparticle components and their proportions to quickly help identify and create the optimal design for use with various therapeutic genes,” said Mao, director of the Institute for NanoBioTechnology at Johns Hopkins Whiting School of Engineering and professor in the departments of Materials Science and Engineering and Biomedical Engineering.
Circa 2018 face_with_colon_three
A paper published in 2017 appeared to show a limited quantum effect in bacteria. Now scientists argue that something much weirder happened.
Basically this means halting and controlling cellular death which would reverse the death process :3.
During pyroptosis, gasdermin D (GSDMD) forms plasma membrane pores that initiate cell lysis. Here, the authors develop optogenetically activatable human GSDMD to assess GSDMD pore behavior and show that they are dynamic and can close, which can be a pyroptosis regulatory mechanism.
In recent years, deep learning algorithms have achieved remarkable results in a variety of fields, including artistic disciplines. In fact, many computer scientists worldwide have successfully developed models that can create artistic works, including poems, paintings and sketches.
Researchers at Seoul National University have recently introduced a new artistic deep learning framework, which is designed to enhance the skills of a sketching robot. Their framework, introduced in a paper presented at ICRA 2022 and pre-published on arXiv, allows a sketching robot to learn both stroke-based rendering and motor control simultaneously.
The lead in some bullets used for hunting deer, moose, and elk is toxic to the humans who eat the harvested meat and to scavenger animals that feast on remains left in the field.
A team of researchers from the Canadian Light Source at the University of Saskatchewan (USask) and the College of Medicine at USask has for the first time used synchrotron imaging to study both the size and spread of bullet fragments in big game shot by hunters. Their findings were published today in PLOS ONE.
Researchers from RIKEN in Japan have achieved a major step toward large-scale quantum computing by demonstrating error correction in a three-qubit silicon-based quantum computing system. This work, published in Nature, could pave the way toward the achievement of practical quantum computers.
Quantum computers are a hot area of research today, as they promise to make it possible to solve certain important problems that are intractable using conventional computers. They use a completely different architecture, using superimposition states found in quantum physics rather than the simple 1 or 0 binary bits used in conventional computers. However, because they are designed in a completely different way, they are very sensitive to environmental noise and other issues, such as decoherence, and require error correction to allow them to do precise calculations.
One important challenge today is choosing what systems can best act as “qubits”—the basic units used to make quantum calculations. Different candidate systems have their own strengths and weaknesses. Some of the popular systems today include superconducting circuits and ions, which have the advantage that some form of error correction has been demonstrated, allowing them to be put into actual use albeit on a small scale. Silicon-based quantum technology, which has only begun to be developed over the past decade, is known to have an advantage in that it utilizes a semiconductor nanostructure similar to what is commonly used to integrate billions of transistors in a small chip, and therefore could take advantage of current production technology.
