Neuroscientists have used an artificial intelligence to read brain signals resulting in intelligible, recognizable, audible speech for the first time ever.
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Meanwhile, LIVE in Hollywood, FL today.
Brian Manning Delaney will join us with a presentation on “Navigating the Labyrinth of Dietary Restriction Methods.“
Followed with an Age Reversal Update by William Faloon.
William Faloon compiled the 1,500-page medical reference book Disease Prevention and Treatment, and his latest book is Pharmocracy: How Corrupt Deals and Misguided Medical Regulations Are Bankrupting America—and What to Do About It. He is also Director and Co-founder of the Life Extension Foundation.
“A software tool called CaImAn automates the arduous process of tracking the location and activity of neurons. It accomplishes this task using a combination of standard computational methods and machine-learning techniques. In a new paper, the software’s creators demonstrate that CaImAn achieves near-human accuracy in detecting the locations of active neurons based on calcium imaging data.”
Journal Article: https://www.simonsfoundation.org/…/caiman-calcium-imaging-…/
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D-Wave, the well-funded quantum computing company, today announced its next-gen quantum computing platform with 5,000 qubits, up from 2,000 in the company’s current system. The new platform will come to market in mid-2020.
The company’s new so-called Pegasus topology connects every qubit to 15 other qubits, up from six in its current topology. With this, developers can use the machine to solve larger problems with fewer physical qubits — or larger problems in general.
It’s worth noting that D-Wave’s qubits are different from those of the company’s competitors like Rigetti, IBM and Google, with shorter coherence times and a system that mostly focuses on solving optimization problems. To do that, D-Wave produces lots of qubits, but in a relatively high-noise environment. That means you can’t compare D-Wave’s qubit count to that of its competitors (with D-Wave claiming the superiority of its machine for certain problems), which are building universal quantum computers.
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Center for Nanoscale Materials researchers present a quantum model for achieving ground-state cooling in low frequency mechanical resonators and show how cooperativity and entanglement are key factors to enhance the cooling figure of merit.
A resonator with near-zero thermal noise has better performance characteristics in nanoscale sensing, quantum memories, and quantum information processing applications. Passive cryogenic cooling techniques, such as dilution refrigerators, have successfully cooled high-frequency resonators but are not sufficient for lower frequency systems. The optomechanical effect has been applied successfully to cool low-frequency systems after an initial cooling stage. This method parametrically couples a mechanical resonator to a driven optical cavity, and, through careful tuning of the drive frequency, achieves the desired cooling effect. The optomechanical effect is expanded to an alternative approach for ground-state cooling based on embedded solid-state defects. Engineering the atom-resonator coupling parameters is proposed, using the strain profile of the mechanical resonator allowing cooling to proceed through the dark entangled states of the two-level system ensemble.
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FedEx is the latest company to join the delivery robot craze.
The company said Wednesday it will test a six-wheeled, autonomous robot called the SameDay Bot in Memphis, Tenn. this summer and plans to expand to more cities.
It’s partnering with major brands, including Walmart, Target, Pizza Hut and AutoZone, to understand how delivery robots could help other businesses.
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A team of researchers at The University of Cambridge has recently introduced a unique experimental testbed that could be used for experiments in cooperative driving. This testbed, presented in a paper pre-published on arXiv, consists of 16 miniature Ackermann-steering vehicles called Cambridge Minicars.
“Using true-scale facilities for vehicle testbeds is expensive and requires a vast amount of space,” Amanda Prorok. “Our main objective was to build a low-cost, multi-vehicle experimental setup that is easy to maintain and that is easy to use to prototype new autonomous driving algorithms. In particular, we were interested in testing and tangibly demonstrating the benefits of cooperative driving on multi-lane road topographies.”
Studies investigating cooperative driving are often expensive and time consuming due to a lack of available low-cost platforms that researchers can use to test their systems and algorithms. Prorok and her colleagues thus set out to develop an effective and inexpensive experimental testbed that could ultimately support research into cooperative driving and multi-car navigation.
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IonQ used its trapped-ion computer and a scalable co-design framework for solving chemistry problems. They applied it to compute the ground-state energy of the water molecule. The robust operation of the trapped ion quantum computer yields energy estimates with errors approaching the chemical accuracy, which is the target threshold necessary for predicting the rates of chemical reaction dynamics.
Quantum chemistry is a promising application where quantum computing might overcome the limitations of known classical algorithms, hampered by an exponential scaling of computational resource requirements. One of the most challenging tasks in quantum chemistry is to determine molecular energies to within chemical accuracy.
At the end of 2018, IonQ announced that they had loaded 79 operating qubits into their trapped ion system and had loaded 160 ions for storage in another test. This new research shows that they are making progress applying their system to useful quantum chemistry problems. They are leveraging the trapped-ions system longer stability to process many steps. The new optimization methods developed for this first major quantum chemistry problem can also be used to solve significant optimization and machine learning problems.
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