Self-driving cars, voice assistants, and facial recognition technology are just a few of the advancements made possible by Hinton, LeCun, and Bengio’s work.
The award, named after British mathematician Alan Turing, carries a $1 million prize, which the trio will split. Previous Turing Award winners include Tim Berners-Lee, best known for inventing the World Wide Web.
Hinton is currently a top AI researcher at Google. LeCun is now at Facebook, working as the company’s chief AI scientist. Bengio has remained in academia but has worked with companies such as AT&T, Microsoft, and IBM.
Tiny selenium particles could have a therapeutic effect on ischemic brain strokes by promoting the recovery of brain damage. Pharmacologists, including Alireza Mashaghi from the Leiden Academic Centre for Drug Research discovered that selenium nanoparticles inhibit molecular mechanisms that are responsible for the loss of brain cells after a stroke. The results were published in Nature Scientific Reports in April.
Nanoparticles against strokes
An ischemic stroke happens when a supplying blood vessel to the brain is narrowed or obstructed. As a result, the brain gets too little blood. “This lack of blood can lead to brain tissue damage due to cellular toxicity, inflammation and cell death,” Mashaghi explains. “This will, in turn, lead to brain dysfunction and neurological complaints such as numbness, vision problems, dizziness and severed headache.” Ischemic stroke accounts for 87% of all strokes and is a significant cause of death. “So far, no neuroprotective agents have been shown to produce any measurable improvement in health in cerebral stroke cases. Our results now demonstrated that selenium nanoparticles inhibit molecular mechanisms that are responsible for the loss of brain cells after a stroke.”
Quantum information protocols are based on a variety of entanglement modes such as Einstein-Podolsky-Rosen (EPR), Greenberger-Horne-Zeilinger (GHZ) and other cluster states. For on-demand preparation, these states can be realized with squeezed light sources in optics, but such experiments lack versatility as they require a variety of optical circuits to individually realize diverse states of entanglement. In a recent study, Shuntaro Takeda and colleagues at the interdisciplinary departments of Applied Physics and Engineering in Japan addressed the shortcoming by developing an on-demand entanglement synthesizer. Using the experimental setup, the physicists programmably generated entangled states from a single squeezed source of light.
In the work, they used a loop-based circuit dynamically controlled at nanosecond time scales to process optical pulses in the time domain. The scientists generated and verified five different small-scale entangled states and a large-cluster containing more than 1000 modes in a single setup without changing the optical circuit. The circuit developed by Takeda et al. could store and release one part of the generated entangled states to function as a quantum memory. The experimental report published on Science Advances, will open a new way to build general entanglement synthesizers on-demand using a scalable quantum processor.
They use proprietary materials which are custom designed for printing. They are using stronger alloys designed to take advantage of Stargate’s printing physics. They have highly reliable materials for printing rocket structures and are using an in-house metallurgy and material characterization lab.
Popular films like “Her” and series such as “Black Mirror” depict a future of intimate relationships in a high-tech world: Man falls in love with operating system, woman loves person she meets in virtual reality. The rise of technologies like artificial intelligence (AI) may play a huge role in the future of our interpersonal relationships. Hardware, such as robots we could touch and feel, are one example of what this AI could look like; another would be software, or algorithms that take on a persona like Alexa or Siri and can seemingly interact with us.
Beyond overused sci-fi clichés, there’s great potential for AI to increase the authenticity and value of real human relationships. Below are some impressions of how AI might enhance the quality of friendship, romantic and professional relationships.
Dating
Men are from Mars and women are from Venus, but AI can be programmed to translate, helping circumvent missteps in love. Algorithms as key matchmakers in the future of dating might provide the support and information people need beyond the first date. For example, an AI personal assistant may give insights on how to approach someone for a second date, based on information culled from the first meeting, the internet and various digital databases. Soon, one’s tweets, likes and Facebook circle of friends could be used to build our dating profile and then a fool-proof guide to dating the other person.
Abstract: In standard nonrelativistic quantum mechanics the expectation of the energy is a conserved quantity. It is possible to extend the dynamical law associated with the evolution of a quantum state consistently to include a nonlinear stochastic component, while respecting the conservation law. According to the dynamics thus obtained, referred to as the energy-based stochastic Schrodinger equation, an arbitrary initial state collapses spontaneously to one of the energy eigenstates, thus describing the phenomenon of quantum state reduction. In this article, two such models are investigated: one that achieves state reduction in infinite time, and the other in finite time. The properties of the associated energy expectation process and the energy variance process are worked out in detail. By use of a novel application of a nonlinear filtering method, closed-form solutions—algebraic in character and involving no integration—are obtained for both these models. In each case, the solution is expressed in terms of a random variable representing the terminal energy of the system, and an independent noise process. With these solutions at hand it is possible to simulate explicitly the dynamics of the quantum states of complicated physical systems.
