Lifeboat Foundation

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 phase transitions in Vanadium Dioxide (VO₂). VO₂ has an insulating phase when relaxed at room temperature, and undergoes a steep insulator-to-metal transition at 68 °C, where its lattice structure changes. Classically, VO₂ exhibits a volatile memory: “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 memory effect in the material’s structure.

Azure.

Azure is using recycled plastic to 3D print prefab homes. The startup is now selling many house models ranging from a backyard studio to a two-bedroom ADU.

Sandia has been working on the project for more than a decade – now comes scaling.

Findings suggest it is possible to treat soil and water on Mars for farming.

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.

Not yet. But we should make sure we act now to stay well ahead.

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 quantum simulations. 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 error mitigation, 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.

A pair of researchers at MIT have found evidence suggesting that a new kind of computer could be built based on liquid crystals rather than silicon. In their paper published in the journal Science Advances, Žiga Kos and Jörn Dunkel outline a possible design for a computer that takes advantage of slight differences in the orientation of the molecules that make up liquid crystals and the advantages such a system would have over those currently in use.

Most modern computer screens are made using liquid crystal displays (LCDs). Such displays are made by growing crystals in a flat plane. These crystals are made up of rod-shaped molecules that line up in a parallel fashion (those that line up the wrong way are removed). The orientation of the molecules in LCDs are not all perfect alignments, of course, but they are close enough to allow for sharp imagery.

In this new effort, Kos and Dunkel, suggest it should be possible to take advantage of those slight misalignments to create a new way to hold and manipulate computer data. They note that such a computer could encode a unique value to each type of misalignment to hold a bit of data. Thus, a computer using this approach would not be constrained to conventional binary bits—it could have a whole host of options, perhaps making it much faster than machines used today (depending on how quickly the orientations could be changed).