In Hyper Reality’s dystopian future city, every interaction has a digital overlay, filling your vision with information like a character in a computer game.
Yesterday, we saw the news from D-Wave in development & release of a new scalable QC. Now, Dartmouth has been able to develop a method to design faster pulses, offering a new way to accurately control quantum systems.
Dartmouth College researchers have discovered a method to design faster pulses, offering a new way to accurately control quantum systems.
The findings appear in the journal Physical Review A.
Quantum physics defines the rules that govern the realm of the ultra-small — the atomic and sub-atomic world — which explains the behavior of matter and its interactions. Scientists have been trying to exploit the seemingly strange properties of this quantum world to build practical devices, such as ultra-fast computers or ultra-precise quantum sensors. Building a practical device, however, requires accurately controlling your device to make it do what you want. This turns out to be challenging since quantum properties are very fragile.
Light waves might be able to drive future transistors. The electromagnetic waves of light oscillate approximately one million times in a billionth of a second, hence with petahertz frequencies. In principle also future electronics could reach this speed and become 100.000 times faster than current digital electronics. This requires a better understanding of the sub-atomic electron motion induced by the ultrafast electric field of light. Now a team of the Laboratory for Attosecond Physics (LAP) at the Max-Planck Institute of Quantum Optics (MPQ) and the Ludwig-Maximilians-Universität (LMU) and theorists from the University of Tsukuba combined novel experimental and theoretical techniques which provide direct access to this motion for the first time.
Electron movements form the basis of electronics as they facilitate the storage, processing and transfer of information. State-of-the-art electronic circuits have reached their maximum clock rates at some billion switching cycles per second as they are limited by the heat accumulating in the process of switching power on and off.
The electric field of light changes its direction a trillion times per second and is able to move electrons in solids at this speed. This means that light waves can form the basis for future electronic switching if the induced electron motion and its influence on heat accumulation is precisely understood. Physicists from the Laboratory for Attosecond Physics at the MPQ and the LMU already found out that it is possible to manipulate the electronic properties of matter at optical frequencies.
Last weekend, an invite-only group of about 150 experts convened privately at Harvard. Behind closed doors, they discussed the prospect of designing and building an entire human genome from scratch, using only a computer, a DNA synthesizer and raw materials.
The artificial genome would then be inserted into a living human cell to replace its natural DNA. The hope is that the cell “reboots,” changing its biological processes to operate based on instructions provided by the artificial DNA.
In other words, we may soon be looking at the first “artificial human cell.”
PlaNet, made by a team led by Google computer vision specialist Tobias Weyand, can determine the location of photos just by studying its pixels.
You can usually tell where a picture was taken by recognizing certain location cues within the photo. Major landmarks like the Great Wall of China or the Tower of London are immediately recognizable and fairly easy to pinpoint, but how about when the photo lacks any familiar location cues, like a photo of food, of pets, or one taken indoors?
People do fairly well on this task by relying on all sorts of knowledge about the world. You could figure out where a photo was taken by looking at any words found on the photo, or by looking at the architectural styles or vegetation.
Advances in microchips—particularly the graphics-processing units pioneered by Nvidia—are fueling growth in machine learning, a programming approach in which computers teach themselves without explicit instructions.
By 2050, the world will need to feed an additional 2.5 billion people living in cities. Yet as the demand for food rises, the amount of land available for agriculture in developed countries is expected to decline. In Japan, at the Fujitsu factory of Aizu-Wakamatsu which still manufactures semiconductor chips for computers, a different project is underway which may offer a solution to this problem. The company has converted an unused part of the factory into a farm to grow food — and more specifically, to grow lettuce. Fujitsu has focused on growing a low-potassium variety, which is sold to people with kidney problems who cannot process the mineral properly. Join Rachel Mealey in Japan’s Fukushima Prefecture to visit the sun-free and soil-free urban farms of the future.
Biography: Stuart Russell received his B.A. with first-class honours in physics from Oxford University in 1982 and his Ph.D. in computer science from Stanford in 1986. He then joined the faculty of the University of California at Berkeley, where he is Professor (and formerly Chair) of Electrical Engineering and Computer Sciences and holder of the Smith-Zadeh Chair in Engineering. He is also an Adjunct Professor of Neurological Surgery at UC San Francisco and Vice-Chair of the World Economic Forum’s Council on AI and Robotics. He has published over 150 papers on a wide range of topics in artificial intelligence including machine learning, probabilistic reasoning, knowledge representation, planning, real-time decision making, multitarget tracking, computer vision, computational physiology, and global seismic monitoring. His books include “The Use of Knowledge in Analogy and Induction”, “Do the Right Thing: Studies in Limited Rationality” (with Eric Wefald), and “Artificial Intelligence: A Modern Approach” (with Peter Norvig).
Abstract: Autonomous weapons systems select and engage targets without human intervention; they become lethal when those targets include humans. LAWS might include, for example, armed quadcopters that can search for and eliminate enemy combatants in a city, but do not include cruise missiles or remotely piloted drones for which humans make all targeting decisions. The artificial intelligence (AI) and robotics communities face an important ethical decision: whether to support or oppose the development of lethal autonomous weapons systems (LAWS).