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The brain-computer linkup firm, Neuralink, is set to reveal more about its progress toward its goals.
The Berkshire Hathaway-owned utilityâs largest-ever clean energy procurement opens up huge opportunities in Northwest and Rocky Mountain states.
Posted in 3D printing, habitats, robotics/AI, space
AI SpaceFactory, a space architecture and technology design agency, recently won first prize in NASAâs competition to build a prototype Mars habitat.
Last week the President Council of Advisors on Science and Technology (PCAST) met (webinar) to review policy recommendations around three sub-committee reports: 1) Industries of the Future (IotF), chaired be Dario Gil (director of research, IBM); 2) Meeting STEM Education and Workforce Needs, chaired by Catherine Bessant (CTO, Bank of America), and 3) New Models of Engagement for Federal/National Laboratories in the Multi-Sector R&D Enterprise, chaired by Dr. A.N. Sreeram (SVP, CTO, Dow Corp.)
Yesterday, the full report (Recommendations For Strengthening American Leadership In Industries Of The Future) was issued and it is fascinating and wide-ranging. To give you a sense of the scope, here are three highlights taken from the executive summary of the full report:
Army researchers developed a new way to protect and safeguard quantum information, moving quantum networks a step closer to reality.
Quantum information science is a rapidly growing interdisciplinary field exploring new ways of storing, manipulating and communicating information. Researchers want to create powerful computational capabilities using new hardware that operates on quantum physics principles.
For the Army, the new quantum paradigms could potentially lead to transformational capabilities in fast, efficient and secure collecting, exchanging and processing vast amounts of information on dynamic battlefields of the future.
Researchers at the Army Research Laboratory have developed a new method to protect and safeguard quantum information, moving quantum networks a step closer to reality.
Quantum information science is a rapidly growing interdisciplinary field exploring new ways of storing, manipulating and communicating information. Researchers aim to create powerful computational capabilities using new hardware that operates on quantum physics principles.
For the army, these new quantum paradigms could potentially lead to transformational capabilities in fast, efficient and secure collecting, exchanging and processing vast amounts of information on dynamic battlefields in the future.
Quantum information scientists have introduced a new method for machine learning classifications in quantum computing. The non-linear quantum kernels in a quantum binary classifier provide new insights for improving the accuracy of quantum machine learning, deemed able to outperform the current AI technology.
The research team led by Professor June-Koo Kevin Rhee from the School of Electrical Engineering, proposed a quantum classifier based on quantum state fidelity by using a different initial state and replacing the Hadamard classification with a swap test. Unlike the conventional approach, this method is expected to significantly enhance the classification tasks when the training dataset is small, by exploiting the quantum advantage in finding non-linear features in a large feature space.
Quantum machine learning holds promise as one of the imperative applications for quantum computing. In machine learning, one fundamental problem for a wide range of applications is classification, a task needed for recognizing patterns in labeled training data in order to assign a label to new, previously unseen data; and the kernel method has been an invaluable classification tool for identifying non-linear relationships in complex data.
MIT engineers develop a hybrid process that connects photonics with âartificial atoms,â to produce the largest quantum chip of its type.
Such noise nearly drowned out the signal in Googleâs quantum supremacy experiment. Researchers began by setting the 53 qubits to encode all possible outputs, which ranged from zero to 253. They implemented a set of randomly chosen interactions among the qubits that in repeated trials made some outputs more likely than others. Given the complexity of the interactions, a supercomputer would need thousands of years to calculate the pattern of outputs, the researchers said. So by measuring it, the quantum computer did something that no ordinary computer could match. But the pattern was barely distinguishable from the random flipping of qubits caused by noise. âTheir demonstration is 99% noise and only 1% signal,â Kuperberg says.
To realize their ultimate dreams, developers want qubits that are as reliable as the bits in an ordinary computer. âYou want to have a qubit that stays coherent until you switch off the machine,â Neven says.
Scientistsâ approach of spreading the information of one qubitâa âlogical qubitââamong many physical ones traces its roots to the early days of ordinary computers in the 1950s. The bits of early computers consisted of vacuum tubes or mechanical relays, which were prone to flip unexpectedly. To overcome the problem, famed mathematician John von Neumann pioneered the field of error correction.
