Lifeboat Foundation

Quantum theory is strange and counterintuitive, but it’s very precise. Lots of analogies and broad concepts are presented in popular science trying to give an accurate description of quantum behavior, but if you really want to understand how quantum theory (or any other theory) works, you need to look at the mathematical details. It’s only the mathematics that shows us what’s truly going on.

Mathematically, a quantum object is described by a function of complex numbers governed by the Schrödinger equation. This function is known as the wavefunction, and it allows you to determine quantum behavior. The wavefunction represents the state of the system, which tells you the probability of various outcomes to a particular experiment (observation). To find the probability, you simply multiply the wavefunction by its complex conjugate. This is how quantum objects can have wavelike properties (the wavefunction) and particle properties (the probable outcome).

No, wait. Actually a quantum object is described by a mathematical quantity known as a matrix. As Werner Heisenberg showed, each type of quantity you could observe (position, momentum, energy) is represented by a matrix as well (known as an operator). By multiplying the operator and the quantum state matrix in a particular way, you get the probability of a particular outcome. The wavelike behavior is a result of the multiple connections between states within the matrix.

Technology Lab —

Google AI invents its own cryptographic algorithm; no one knows how it works.

Neural networks seem good at devising crypto methods; less good at codebreaking.

Continue reading “Google AI invents its own cryptographic algorithm; no one knows how it works” »

NEWS ANALYSIS: The confluence of big data, massively powerful computing resources and advanced algorithms is bringing new artificial intelligence capabilities to scientific research.

WASHINGTON, DC—Massively parallel supercomputing hardware along with advanced artificial intelligence algorithms are being harnessed to deliver powerful new research tools in science and medicine, according to Dr. France A. Córdova, Director of the National Science Foundation.

Córdova spoke Oct. 26 at GPU Technology Conference organized by Nvidia, a company that got its start making video cards for PCs and gaming systems, that now manufactures advanced graphics processor for high-performance servers and supercomputers.

An artificial intelligence method developed by University College London computer scientists and associates has predicted the judicial decisions of the European Court of Human Rights (ECtHR) with 79% accuracy, according to a paper published today (Monday, Oct. 24) in PeerJ Computer Science.

The method is the first to predict the outcomes of a major international court by automatically analyzing case text using a machine-learning algorithm.*.

Artificial intelligence is a “momentous development,” said George Lee, co-chairman of the global technology, media and telecom group at Goldman Sachs.

“As awesome as the internet has been, it will be best remembered as really the predicate for machine learning,” said Lee, who’s also chief information officer of Goldman’s investment banking division. He appeared on CNBC’s “Squawk Alley” on Wednesday from Goldman’s Builders + Innovators Summit in Santa Barbara, California.

The internet enabled computing scale in a network and serves as a way to “collect data that’s used to train all these algorithms,” Lee said, predicting machine learning will “change our world … and even the course of our species in ways that are hard to predict today.”

Continue reading “Artificial intelligence will change the ‘course of our species’: Top Goldman tech banker” »

A London-based startup has combined some of today’s most disruptive technologies in a bid to change the way we’ll build the future. By retrofitting industrial robots with 3D printing guns and artificial intelligence algorithms, Ai Build has constructed machines that can see, create, and even learn from their mistakes.

When CEO and founder Daghan Cam was studying architecture, he noticed a disconnect between small-scale manufacturing and large-scale construction. “On one side we have a fully automated production pipeline,” Cam explained at a recent conference in London. “On the other side we’re completely dependent on human labor.” With the emergence of more efficient printing technologies, he thought there must be a better way.

Continue reading “Give a 3D printer artificial intelligence, and this is what you’ll get” »

https://youtube.com/watch?v=v-qVBko0r0U

Mars colonization — getting there is only a small part of the equation. The bigger problem is how to survive. Synthetic biology may be able to help.

If there is any organization on the planet that has had a closer view of the coming demise of Moore’s Law, it is the Institute of Electrical and Electronics Engineers (IEEE). Since its inception in the 1960s, the wide range of industry professionals have been able to trace a steady trajectory for semiconductors, but given the limitations ahead, it is time to look to a new path—or several forks, to be more accurate.

This realization about the state of computing for the next decade and beyond has spurred action from a subgroup, led by Georgia Tech professor Tom Conte and superconducting electronics researcher, Elie Track called “Rebooting Computing,” which produces reports based on invite-only deep dives on a wide range of post-Moore’s Law technologies, many of which were cited here this week via Europe’s effort to pinpoint future post-exascale architectures. The Rebooting Computing effort is opening its doors next week for a wider-reaching, open forum in San Diego to bring together new ideas in novel architectures and modes of computing as well as on the applications and algorithm development fronts.

According to co-chair of the Rebooting Computing effort, Elie Track, a former Yale physicist who has turned his superconducting circuits work toward high efficiency solar cells in his role at startup Nvizix, Moore’s Law is unquestionably dead. “There is no known technology that can keep packing more density and features into a given space and further, the real issue is power dissipation. We just cannot keep reducing things further; a fresh perspective is needed.” The problem with gaining that view, however, is that for now it means taking a broad, sweeping look across many emerging areas; from quantum and neuromorphic devices, approximate computing, and a wide range of other technologies. “It might seem frustrating that this is general, but there is no clear way forward yet. What we all agree on is that we need exponential growth in computing engines.”

Continue reading “IEEE Reboots, Scans for Future Architectures” »

Nice.

There are many scientific and non-scientific varieties of the answer about what came before Big Bang. Some say there was literally nothing and some say a black hole or a multiverse. But now a group of mathematicians from Canada and Egypt have analyzed some cutting edge scientific theory and a complex set of equations to find what preceded the universe in which we live. Their research paper has been published in Nature.

Continue reading “Scientists claim to have discover what existed BEFORE the beginning of the universe” »