News

Thin film converts heat from electronics into energy

Nearly 70 percent of the energy produced in the United States each year is wasted as heat. Much of that heat is less than 100 degrees Celsius and emanates from things like computers, cars or large industrial processes. Engineers at the University of California, Berkeley, have developed a thin-film system that can be applied to sources of waste heat like these to produce energy at levels unprecedented for this kind of technology.

NASA’s Got a Plan for a ‘Galactic Positioning System’ to Save Astronauts Lost in Space

20 Entangled Qubits Bring the Quantum Computer Closer

In 1981, Richard Feynman suggested that a quantum computer might be able to simulate the evolution of quantum systems much better than classical computers. Except for several proof-of-principle experiments, no working quantum computer has yet been built.

An Augmented Reality Microscope for Cancer Detection

Applications of deep learning to medical disciplines including ophthalmology, dermatology, radiology, and pathology have recently shown great promise to increase both the accuracy and availability of high-quality healthcare to patients around the world. At Google, we have also published results showing that a convolutional neural network is able to detect breast cancer metastases in lymph nodes at a level of accuracy comparable to a trained pathologist. However, because direct tissue visualization using a compound light microscope remains the predominant means by which a pathologist diagnoses illness, a critical barrier to the widespread adoption of deep learning in pathology is the dependence on having a digital representation of the microscopic tissue.

This AI Will Turn Your Dog Into a Cat

As detailed in a paper published to arXiv, the neural net is actually a generative adversarial network (GAN), which is a way of training a machine learning algorithm without human supervision. In GANs, two neural nets are pitted against one another: One neural net generates new images and tries to trick the other neural net into thinking the images are real. If the other neural net is able to tell the generated images are false

Blowing in the wind: Plutonium at former nuclear weapons site

A New Study Suggests There Could Have Been Intelligent Life on Earth Before Humans

U.S. bans American companies from selling to Chinese phone maker ZTE

The billion-dollar question: How does the Clipper mission get to Europa?

Autonomous braking: ‘The most significant development since the safety belt’