Lifeboat Foundation

Even if you are not a quantum physicist, you will most likely have heard of Schrödinger’s famous cat. Erwin Schrödinger came up with the feline that can be alive and dead at the same time in a thought experiment in 1935. The obvious contradiction—after all, in everyday life we only ever see cats that are either alive or dead—has prompted scientists to try to realize analogous situations in the laboratory. So far, they have managed to do so using, for instance, atoms or molecules in quantum mechanical superposition states of being in two places at the same time.

At ETH, a team of researchers led by Yiwen Chu, professor at the Laboratory for Solid State Physics, has now created a substantially heavier Schrödinger cat by putting a small crystal into a superposition of two oscillation states. Their results, which have been published this week in the journal Science, could lead to more robust quantum bits and shed light on the mystery of why quantum superpositions are not observed in the macroscopic world.

In Schrödinger’s original thought experiment, a cat is locked up inside a metal box together with a radioactive substance, a Geiger counter and a flask of poison. In a certain time-frame—an hour, say—an atom in the substance may or may not decay through a quantum mechanical process with a certain probability, and the decay products might cause the Geiger counter to go off and trigger a mechanism that smashes the flask containing the poison, which would eventually kill the cat.

Astronomers using data from NASA’s Chandra X-ray Observatory and other telescopes have identified a new threat to life on planets like Earth: a phase during which intense X-rays from exploded stars can affect planets over 100 light-years away. This result, as outlined in our latest press release, has implication for the study of exoplanets and their habitability.

This newly found threat comes from a supernova’s blast wave striking dense gas surrounding the exploded star, as depicted in the upper right of our artist’s impression. When this impact occurs it can produce a large dose of X-rays that reaches an Earth-like planet (shown in the lower left, illuminated by its host star out of view to the right) months to years after the explosion and may last for decades. Such intense exposure may trigger an extinction event on the planet.

A new study reporting this threat is based on X-ray observations of 31 supernovae and their aftermath—mostly from NASA’s Chandra X-ray Observatory, Swift and NuSTAR missions, and ESA’s XMM-Newton—show that planets can be subjected to lethal doses of radiation located as much as about 160 light-years away. Four of the supernovae in the study (SN 1979C, SN 1987A, SN 2010jl, and SN 1994I) are shown in composite images containing Chandra data in the supplemental image.

People are outsourcing home-based tasks like meal prep and bedtime stories to artificial intelligence, too.

Synthesis AI, a startup that specializes in synthetic data technologies, announced that they have developed a new technology for digital human creation, which enables one to create highly realistic 3D digital humans from text prompts using generative AI and VFX pipelines.

The technology showcased by Synthesis AI allows users to input specific text descriptions such as age, gender, ethnicity, hairstyle, and clothing to generate a 3D model that matches the specifications. Users can also edit the 3D model by changing text prompts or using sliders to adjust features like facial expressions and lighting.

Dropbox is a free service that lets you bring your photos, docs, and videos anywhere and share them easily. Never email yourself a file again!

At last, a new study has found the answers to “basic biology questions” that could help explain what drives ageing and what can we do to reverse it.

Fused neurons suggest ctenophores’ nervous system evolved independently of that in other animals.

Shared with Dropbox.

The earliest artificial neural network, the Perceptron, was introduced approximately 65 years ago and consisted of just one layer. However, to address solutions for more complex classification tasks, more advanced neural network architectures consisting of numerous feedforward (consecutive) layers were later introduced. This is the essential component of the current implementation of deep learning algorithms. It improves the performance of analytical and physical tasks without human intervention, and lies behind everyday automation products such as the emerging technologies for self-driving cars and autonomous chat bots.

The key question driving new research published today in Scientific Reports is whether efficient learning of non-trivial classification tasks can be achieved using brain-inspired shallow feedforward networks, while potentially requiring less computational complexity.

Continue reading “Is deep learning a necessary ingredient for artificial intelligence?” »