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Any Xenomorph-fearing ‘Alien’ fan will tell you that sound doesn’t exist in space. The thing is, that’s not completely true.

Back in May, during black hole week, NASA released an eerie sound clip of a black hole showing that space does make a lot of noise, depending on where you look, and how you process it.


“The misconception that there is no sound in space originates because most space is a ~vacuum, providing no way for sound waves to travel. A galaxy cluster has so much gas that we’ve picked up actual sound. Here it’s amplified, and mixed with other data, to hear a black hole!”

Unstable black holes would require a rewrite of Einstein’s gravitational theory.

An international group of scientists finally proved that slowly rotating Kerr black holes are stable, a report from Quanta Magazine

In 1963, mathematician Roy Kerr found a solution to Einstein’s equations that accurately described the spacetime around what is now known as a rotating black hole.


The solutions to Einstein’s equations that describe a spinning black hole won’t blow up, even when poked or prodded.

Scientists in Taiwan demonstrated a new way to produce high-purity lead-iodide, as a precursor material for a perovskite solar cell. By using temperature to better control the orientation of crystals, the group was able to show much higher efficiencies when the precursor was used to fabricate a perovskite layer and subsequently a working solar cell.

EPFL researchers have discovered that Vanadium Dioxide (VO2), a compound used in electronics, is capable of “remembering” the entire history of previous external stimuli. This is the first material to be identified as possessing this property, although there could be others.

Mohammad Samizadeh Nikoo, a Ph.D. student at EPFL’s Power and Wide-band-gap Electronics Research Laboratory (POWERlab), made a chance discovery during his research on in Vanadium Dioxide (VO2). VO2 has an insulating phase when relaxed at , and undergoes a steep insulator-to-metal transition at 68 °C, where its lattice structure changes. Classically, VO2 exhibits a : “the material reverts back to the insulating state right after removing the excitation” says Samizadeh Nikoo. For his thesis, he set out to discover how long it takes for VO2 to transition from one state to another. But his research led him down a different path: after taking hundreds of measurements, he observed a effect in the material’s structure.

I have been invited to participate in a quite large event in which some experts and I (allow me to not consider myself one) will discuss about Artificial Intelligence, and, in particular, about the concept of Super Intelligence.

It turns out I recently found out this really interesting TED talk by Grady Booch, just in perfect timing to prepare my talk.

No matter if you agree or disagree with Mr. Booch’s point of view, it is clear that today we are still living in the era of weak or narrow AI, very far from general AI, and even more from a potential Super Intelligence. Still, Machine Learning bring us with a great opportunity as of today. The opportunity to put algorithms to work together with humans to solve some of our biggest challenges: climate change, poverty, health and well being, etc.

Near-term quantum computers, quantum computers developed today or in the near future, could help to tackle some problems more effectively than classical computers. One potential application for these computers could be in physics, chemistry and materials science, to perform quantum simulations and determine the ground states of quantum systems.

Some quantum computers developed over the past few years have proved to be fairly effective at running . However, near-term quantum computing approaches are still limited by existing hardware components and by the adverse effects of background noise.

Researchers at 1QB Information Technologies (1QBit), University of Waterloo and the Perimeter Institute for Theoretical Physics have recently developed neural , a new strategy that could improve ground state estimates attained using quantum simulations. This strategy, introduced in a paper published in Nature Machine Intelligence, is based on machine-learning algorithms.