However, Rob Ott, a computer scientist at Stanford University in Palo Alto, California, who did work on the system—Deep Learning Interface for Accounting (DELIA)—notes that it simply held all of the missing money, some $40,120.16, in a “rainy day” account. “I don’t think you can attribute malice,” he says. “I’m sure DELIA was going to give the money back.”
Technologists shocked by program’s ability to set its own priorities—such as getting rich.
The machine overlords of the future may now, if it pleases them, eliminate all black and white imagery from the history of their meat-based former masters. All they’ll need is this system from Berkeley computer scientist Richard Zhang, which allows a soulless silicon sentience to “hallucinate” colors into any monochrome image.
It uses what’s called a convolutional neural network (several, actually) — a type of computer vision system that mimics low-level visual systems in our own brains in order to perceive patterns and categorize objects. Google’s DeepDream is probably the most well-known example of one. Trained by examining millions of images of— well, just about everything, Zhang’s system of CNNs recognizes things in black and white photos and colors them the way it thinks they ought to be.
Grass, for instance, has certain features — textures, common locations in images, certain other things often found on or near it. And grass is usually green, right? So when the network thinks it recognizes grass, it colors that region green. The same thing occurs for recognizing certain types of butterflies, building materials, flowers, the nose of a certain breed of dog and so on.
Nanoparticle diodes and devices that work when wet.
“Groundbreaking” research by Prof. Bartosz Grzybowski (School of Natural Science).
Nanoparticle Diodes and Devices That Work When Wet.
A new study by an international team of researchers, affiliated with UNIST has found a new way to produce electronic devices, such as diodes, logic gates, and sensors without the need of semiconductors.
In their study, published in the current edition of Nano Technology, the team reported that they used metal nanoparticles, coated with charged organic ligands to create versatile electronic circuits, which they have named “chemoelectronic” circuits.
MIT biological engineers have created a programming language that allows them to rapidly design complex, DNA-encoded circuits that give new functions to living cells.
Using this language, anyone can write a program for the function they want, such as detecting and responding to certain environmental conditions. They can then generate a DNA sequence that will achieve it.
“It is literally a programming language for bacteria,” says Christopher Voigt, an MIT professor of biological engineering. “You use a text-based language, just like you’re programming a computer. Then you take that text and you compile it and it turns it into a DNA sequence that you put into the cell, and the circuit runs inside the cell.”
Black-hole computing.
Might nature’s bottomless pits actually be ultra-efficient quantum computers? That could explain why data never dies.
“What is the best way to get from A to B by public transit? Google Maps is answering such queries for over 20,000 cities and towns in over 70 countries around the world, including large metro areas like New York, São Paulo or Moscow, and some complete countries, such as Japan or Great Britain.”
A University of Oklahoma-led team of physicists believes chip-based atomic physics holds promise to make the second quantum revolution—the engineering of quantum matter with arbitrary precision—a reality. With recent technological advances in fabrication and trapping, hybrid quantum systems are emerging as ideal platforms for a diverse range of studies in quantum control, quantum simulation and computing.
James P. Shaffer, professor in the Homer L. Dodge Department of Physics and Astronomy, OU College of Arts and Sciences; Jon Sedlacek, OU graduate student; and a team from the University of Nevada, Western Washington University, The United States Naval Academy, Sandia National Laboratories and Harvard-Smithsonian Center for Astrophysics, have published research important for integrating Rydberg atoms into hybrid quantum systems and the fundamental study of atom–surface interactions, as well as applications for electrons bound to a 2D surface.
“A convenient surface for application in hybrid quantum systems is quartz because of its extensive use in the semiconductor and optics industries,” Sedlacek said. “The surface has been the subject of recent interest as a result of it stability and low surface energy. Mitigating electric fields near ‘trapping’ surfaces is the holy grail for realizing hybrid quantum systems,” added Hossein Sadeghpour, director of the Institute for Theoretical Atomic Molecular and Optical Physics, Harvard-Smithsonian Center for Astrophysics.
(Phys.org)—One promising approach for scalable quantum computing is to use an all-optical architecture, in which the qubits are represented by photons and manipulated by mirrors and beam splitters. So far, researchers have demonstrated this method, called Linear Optical Quantum Computing, on a very small scale by performing operations using just a few photons. In an attempt to scale up this method to larger numbers of photons, researchers in a new study have developed a way to fully integrate single-photon sources inside optical circuits, creating integrated quantum circuits that may allow for scalable optical quantum computation.
The researchers, Iman Esmaeil Zadeh, Ali W. Elshaari, and coauthors, have published a paper on the integrated quantum circuits in a recent issue of Nano Letters.
As the researchers explain, one of the biggest challenges facing the realization of an efficient Linear Optical Quantum Computing system is integrating several components that are usually incompatible with each other onto a single platform. These components include a single-photon source such as quantum dots; routing devices such as waveguides; devices for manipulating photons such as cavities, filters, and quantum gates; and single-photon detectors.
Synthetic biology involves creating or re-engineering microbes or other organisms to perform specific tasks, like fighting obesity, monitoring chemical threats or creating biofuels. Essentially, biologists program single-celled organisms like bacteria and yeast much the same way one would program and control a robot.
But 10 years ago, it was extremely challenging to take a DNA sequence designed on a computer and turn it into a polymer that could implement its task in a specific host, say a mouse or human cell. Now, thanks to a multitude of innovations across computing, engineering, biology and other fields, researchers can type out any DNA sequence they want, email it to a synthesis company, and receive their completed DNA construct in a week. You can build entire chromosomes and entire genomes of bacteria in this way.
“Biology is the most powerful substrate for engineering that we know of,” said Christopher Voigt, Professor of Biological Engineering at MIT. “It’s more powerful than electrical engineering, mechanical engineering, materials science and others. Unlike all the other fields, we can look at what biology is already able to do. When we look at the natural world, we see things like the brain. That’s a complex place computing, electrical engineering and computer science can’t reach. The brain even constructs nanostructures very deliberately, something materials science has not accomplished.”