Lifeboat Foundation

Now this is a cool concept; a studio that allows others to experiment and build their own Biocomputer, and other biotechnologies.

How does a leopard get its spots? A new exhibit at The Tech Museum of Innovation in San Jose has some clues about that.

I did an interview on AI and politics for CBC, which also went out on NPR yesterday.

This week, Google’s artificially intelligent computer, AlphaGo won a tournament in the complex board game called Go. American presidential candidate Zoltan Istvan says it’s that in a matter of 10 to 15 years A.I. will be advanced enough to be president of the United States of America.

Continue reading “The case for a robot president” »

Researchers in Finland have figured out a way to reliably make quantum computers — technology that’s tipped to revolutionise computing in the coming years — even more powerful. And all they had to do was throw common sense out the window.

You’re almost certainly reading this article on a classical computer — which includes all phones, laptops, and tablets — meaning that your computer can only ever do one thing at a time. It reads one bit, then the next bit, then the next bit, and so on. The reading is lightning fast and combines millions or billions or trillions of bits to give you what you want, but the bits are always read and used in order.

So if your computer searches for the solution to a problem, it tries one answer (a particular batch of ones and zeros), checks how far the result is from the goal, tries another answer (a different batch), and repeats. For complicated problems, that process can take an incredibly long time. Sometimes, that’s good. Very clever multiplication secures your bank account, and faster or more efficient equation-solvers put that in jeopardy.

Continue reading “New quantum computer device takes advantage of a loophole in causality” »

A quantum computer has been built that can find prime factors, potentially signalling the beginning of the end for cryptography that relies on the multiplication of large prime numbers, such as RSA encryption.

Now, we’re hitting Terminator mode with this.

If you’re worried that artificial intelligence will take over the world now that computers are powerful enough to outsmart humans at incredibly complex games, then you’re not going to like the idea that someday computers will be able to simply build their own chips without any help from humans. That’s not the case just yet, but researchers did come up with a way to grow metal wires at a molecular level.

At the same time, this is a remarkable innovation that paves the way for a future where computers are able to create high-end chip solutions just as a plant would grow leaves, rather than having humans develop computer chips using complicated nanoengineering techniques.

Continue reading “Remarkable nanowires could let computers of the future grow their own chips” »

More insights on a more controlled Quantum.

By a News Reporter-Staff News Editor at Physics Week — New research on Physics Research is the subject of a report. According to news reporting from Tokyo, Japan, by VerticalNews editors, the research stated, “A computational method called the local-field response method is proposed, where spins evolve by responding to an effective field consisting of gradually decreasing external fields and spin-spin interactions, similarly to what is carried out in adiabatic quantum computing (AQC). This method is partly quantum-mechanical.”

“With the operational function that we have proposed in these memory cells, there will be no need for time-consuming magnetization and demagnetization processes. This means that read and write operations will take only a few hundred picoseconds, depending on the materials and the geometry of the particular system, while conventional methods take hundreds or thousands of times longer than this,” said the study author Alexander Golubov, the head of Moscow Institute of Physics and Technology (MIPT)’s Laboratory of Quantum Topological Phenomena in Superconducting Systems.

Golubov and colleagues at Moscow State University have proposed creating basic memory cells based on quantum effects in superconductor “sandwiches.” Superconductors were predicted in the 1960s by the British physicist Brian Josephson. The electrons in these “sandwiches,” called “Josephson junctions,” are able to tunnel from one layer of a superconductor to another, passing through the dielectric like balls passing through a perforated wall.

Today, Josephson junctions are used both in quantum devices and conventional devices. For example, superconducting qubits are used to build the D-wave quantum system, which is capable of finding the minima of complex functions using the quantum annealing algorithm. There are also ultra-fast analogue-to-digital converters, devices to detect consecutive events, and other systems that do not require fast access to large amounts of memory. There have also been attempts to use the Josephson Effect to create ordinary processors. An experimental processor of this type was created in Japan in the late 1980s. In 2014, the research agency IAPRA resumed its attempts to create a prototype of a superconducting computer.

Continue reading “Rapid Superconducting Memory Cell Control System Developed” »

Specifically, artificially intelligent computers…

As sophisticated algorithms can complete tasks we once thought impossible, computers are seeming to become a real threat to humanity. Whether they decide to pulp us into human meat paste, or simply make our work completely unnecessary, argues technology reporter Alex Hern, we should be afraid of computers.

Even if we don’t create a true AI for a thousand years, these algorithms, pared with our exponentially increasing computing power, could have much of the same effect on our civilization as the more traditional, AI-centric type Singularity. Very, very soon.

Replacing inefficient experimentation, UConn researchers have used machine learning to systematically scan millions of theoretical compounds for qualities that would make better materials for solar cells, fibers, and computer chips.

Continue reading “Using machine learning to rationally design future electronics materials” »