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At the Technical University of Denmark (DTU), a team of researchers have developed a new kind of 3D printer whose technology combines a CT scanner and light. By reversing the principle of CT scanning, they could create all types of parts in record time from different polymer resins and play on their hardness. They would thus be able to reproduce the appearance of blood vessels or muscle tissue.

Today’s CT scans allow us to make slice images of our body parts and to visualize tissues of different densities. This X-ray machine is therefore used in the medical sector to establish a diagnosis. In this case, it was used to design a new, faster resin 3D printer.

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The Force was strong in him. One of Enzo Romero’s favorite activities is playing the guitar, which he effortlessly does with his bright blue hand. Initially, it used to hurt, as he used his handless right arm to press down on chords. But now, with fingers on the end, he can play music painlessly.

Star Wars: Episode V The Empire Strikes Back, marketed as simply The Empire Strikes Back, is a 1980 film directed by Irvin Kershner and written by Leigh Brackett and Lawrence Kasdan from a story by George Lucas. It is the second part of the Star Wars original trilogy.

The film concerns the continuing struggles of the Rebel Alliance against the Galactic Empire. During the film, Han Solo, Chewbacca, and Princess Leia Organa are being pursued across space by Darth Vader and his elite forces. Meanwhile, Luke Skywalker begins his major Jedi training with Yoda, after an instruction from Obi-Wan Kenobi’s spirit. In an emotional and near-fatal confrontation with Vader, Luke is presented with a horrific revelation and must face his destiny.

Continue reading “Engineer born with one hand makes a prosthetic one out of plastic bottles for 0” | >

On September 1 and 2, 1859, telegraph systems around the world failed catastrophically. The operators of the telegraphs reported receiving electrical shocks, telegraph paper catching fire, and being able to operate equipment with batteries disconnected. During the evenings, the aurora borealis, more commonly known as the northern lights, could be seen as far south as Colombia. Typically, these lights are only visible at higher latitudes, in northern Canada, Scandinavia, and Siberia.

What the world experienced that day, now known as the Carrington Event, was a massive geomagnetic storm. These storms occur when a large bubble of superheated gas called plasma is ejected from the surface of the sun and hits the Earth. This bubble is known as a coronal mass ejection.

The plasma of a coronal mass ejection consists of a cloud of protons and electrons, which are electrically charged particles. When these particles reach the Earth, they interact with the magnetic field that surrounds the planet. This interaction causes the magnetic field to distort and weaken, which in turn leads to the strange behavior of the aurora borealis and other natural phenomena. As an electrical engineer who specializes in the power grid, I study how geomagnetic storms also threaten to cause power and internet outages and how to protect against that.

Continue reading “Massive Geomagnetic Storm: Coronal Mass Ejection From the Sun Could Knock Out the Power Grid and Internet” | >

In 2020, OpenAI introduced GPT-3 and, a year later, DALL.E, a 12 billion parameter model, built on GPT-3. DALL.E was trained to generate images from text descriptions, and the latest release, DALL.E 2, generates even more realistic and accurate images with 4x better resolution. The model takes natural language captions and uses a dataset of text-image pairings to create realistic images. Additionally, it can take an image and create different variations inspired by original images.

DALL.E leverages the ‘diffusion’ process to learn the relationship between images and text descriptions. In diffusion, it starts with a pattern of random dots and tracks it towards an image when it recognises aspects of it. Diffusion models have emerged as a promising generative modelling framework and push the state-of-the-art image and video generation tasks. The guidance technique is leveraged in diffusion to improve sample fidelity for images and photorealism. DALL.E is made up of two major parts: a discrete autoencoder that accurately represents images in compressed latent space and a transformer that learns the correlations between language and this discrete image representation. Evaluators were asked to compare 1,000 image generations from each model, and DALL·E 2 was preferred over DALL·E 1 for its caption matching and photorealism.

DALL-E is currently only a research project, and is not available in OpenAI’s API.

Continue reading “Top 4 DALL.E alternatives, text-to-image generators” | >

Summary: People with depression who responded to psilocybin therapy showed an increase in brain connectivity for up to three weeks following treatment. The increased brain connectivity was correlated with self-reported improvements in depression symptoms.

Source: Imperial College London.

Psilocybin, the psychedelic compound found in magic mushrooms, helps to “open up” depressed people’s brains, even after use, enabling brain regions to talk more freely to one another.

Continue reading “Psilocybin Increases Brain Connectivity in People With Depression After Use” | >

A team of researchers at Stanford University, working with a colleague at the Chinese Academy of Sciences, has built an AI-based filtration system to remove noise from seismic sensor data in urban areas. In their paper published in the journal Science Advances, the group describes training their application and testing it against real data from a prior seismic event.

In order to provide advance warning when an earthquake is detected, scientists have placed seismometers in earthquake-prone areas, including where quakes do the most damage and harm or kill the most people. But seismologists have found it troublesome to sort out related to natural ground movements from data related to city life. They note that human activities in cities, such as vehicles and trains, produce a lot of seismic noise. In this new effort, the researchers developed a deep learning application that determines which seismic data is natural and which is man-made and filters out those that are non-natural.

The researchers call their new application UrbanDenoiser. It was built using a deep-learning application and trained on 80,000 samples of urban seismic noise along with 33,751 samples from recorded natural seismic activity. The team applied their filtering system to seismic data recorded in Long Beach, California, to see how well it worked. They found it improved the level of desired signals compared to background noise by approximately 15 decibels. Satisfied with the results, they used UrbanDenoiser to analyze data from an earthquake that struck a nearby area in 2014. They found the application was able to detect four times the amount of data compared to the sensors without the filtering.

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