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An intelligent material that learns by physically changing itself, similar to how the human brain works, could be the foundation of a completely new generation of computers. Radboud physicists working toward this so-called “quantum brain” have made an important step. They have demonstrated that they can pattern and interconnect a network of single atoms, and mimic the autonomous behavior of neurons and synapses in a brain. They report their discovery in Nature Nanotechnology.

Considering the growing global demand for computing capacity, more and more data centers are necessary, all of which leave an ever-expanding energy footprint. “It is clear that we have to find new strategies to store and process information in an energy efficient way,” says project leader Alexander Khajetoorians, Professor of Scanning Probe Microscopy at Radboud University.

“This requires not only improvements to technology, but also fundamental research in game changing approaches. Our new idea of building a ‘quantum brain’ based on the quantum properties of materials could be the basis for a future solution for applications in artificial intelligence.”

In the coming Age of Superintelligence [and automation] everyone should be entitled to social dividend, “free” money such as UBI, just for being alive. We should not forget that the wealthiest of us would not be as fortunate without civilization. Otherwise, Jeff Bezos would have to forage for food in the Amazon jungle all by himself. Being a human today is more than enough of a fair contribution to receive free money from the government. Going forward we’ll see more and more prominent voices vouching for UBI.

#HybridEconomy #UniversalBasicIncome #UBI #BasicIncome #SocialDividend #TaxWallStreet #WealthTax #InheritanceTax

Attacks on vulnerable computer networks and cyber-infrastructure—often called zero-day attacks—can quickly overwhelm traditional defenses, resulting in billions of dollars of damage and requiring weeks of manual patching work to shore up the systems after the intrusion.

Using AI and computer automation, Technion researchers have developed a ‘conjecture generator’ that creates mathematical conjectures, which are considered to be the starting point for developing mathematical theorems. They have already used it to generate a number of previously unknown formulas. The study, which was published in the journal Nature, was carried out by undergraduates from different faculties under the tutelage of Assistant Professor Ido Kaminer of the Andrew and Erna Viterbi Faculty of Electrical Engineering at the Technion.

Most image-recognition systems are trained using large databases that contain millions of photos of everyday objects, from snakes to shakes to shoes. With repeated exposure, AIs learn to tell one type of object from another. Now researchers in Japan have shown that AIs can start learning to recognize everyday objects by being trained on computer-generated fractals instead.

Computer-aided calculations have played a crucial part in producing the proofs of several high-profile results. And more recently, some mathematicians have made progress towards AI that doesn’t just perform repetitive calculations, but develops its own proofs. Another growing area has been software that can go over a mathematical proof written by humans and check that it is correct.


Algorithm named after mathematician Srinivasa Ramanujan suggests interesting formulae, some of which are difficult to prove true.