Lifeboat Foundation: Safeguarding Humanity
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Category: robotics/AI

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 that is easy to maintain and that is easy to use to prototype new 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 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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“It’s dangerous to directly correlate things like, ‘This is a brain!’” Gimzewski told ZDNet. “It’s exhibiting electrical characteristics which are very similar to a functional MRI of brains, similar to the electric characteristics of neuronal cultures, and also EEG patterns.”

READ MORE: Neuromorphic computing and the brain that wouldn’t die [ZDNet]

More on brain-like circuitry: Brain-Based Circuitry Just Made Artificial Intelligence A Whole Lot Faster.

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A consortium of groups has come together with the painstaking task of charting the longevity industry, such as its companies, journalists, thought leaders, investors, and recent developments. The Longevity Industry in UK Landscape Overview 2018 report covers a great amount of ground and is well worth a read for people who are interested in this rapidly evolving scientific field.

This particular edition, which spans an impressive 1000+ pages, is focused on the United Kingdom; there will be additional reports covering Switzerland, Japan, Hong Kong, and California, and there will also be a more general global industry report in its second edition.

Interest in longevity has been increasing for some years, and we are at last seeing a true industry starting to bloom as more and more companies, researchers, and investors step into the ring. Companies such as Unity Biotechnology taking senescent cell-clearing therapies to human trials, deep learning approaches being applied to aging by companies such as Insilco Medicine, and Ichor Therapeutics’ development of age-related macular degeneration therapies have served to ignite the fires of enthusiasm and have brought ever-increasing funding and interest into this field.

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This thesis has been rolling around like a marble in the bowl of a lot of people’s brains for a while now, and many of those marbles were handed out by Martin Ford, in his 2015 book, “Rise of the Robots: Technology and the Threat of a Jobless Future.” In the book, and in an essay in “Confronting Dystopia: The New Technological Revolution and the Future of Work” (Cornell), Ford acknowledges that all other earlier robot-invasion panics were unfounded. In the nineteenth century, people who worked on farms lost their jobs when agricultural processes were mechanized, but they eventually earned more money working in factories. In the twentieth century, automation of industrial production led to warnings about “unprecedented economic and social disorder.” Instead, displaced factory workers moved into service jobs. Machines eliminate jobs; rising productivity creates new jobs.

Probably, but don’t count yourself out.

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