Lifeboat Foundation

An interdisciplinary team of University of Minnesota Twin Cities scientists and engineers has developed a first-of-its-kind, plant-inspired extrusion process that enables synthetic material growth. The new approach will allow researchers to build better soft robots that can navigate hard-to-reach places, complicated terrain, and potentially areas within the human body.

The paper is published in the Proceedings of the National Academy of Sciences (PNAS), a peer-reviewed, multidisciplinary, high-impact scientific journal.

Continue reading “Engineers discover new process for synthetic material growth, enabling soft robots that grow like plants” »

Blainjett Aviation announced that initial testing of its hemi-rotor aerodynamic concept has confirmed its potential to deliver faster, more efficient performance in VTOL aircraft. Subscale tests demonstrated the novel configuration’s net positive lift and low drag through the ascent/hover, cruise, and descent/hover phases of flight.

The startup is applying the hemi-rotor concept to a subscale drone as part of a path to demonstrating that the configuration can scale to larger unmanned or manned aircraft in eVTOL applications from package delivery and cargo to transport and tactical military roles. Blainjett’s hemi-rotor design situates familiar vertical lift rotors partially inside opposite sides of an enclosed fuselage. The airfoil-shaped fuselage also houses a pair of electric motors to drive the lift-rotors. Situated in the empennage above an inverted V-tail, the third motor powers a pusher prop.

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Circa 2015 face_with_colon_three

Researchers have built the world’s first artificial neuron that’s capable of mimicking the function of an organic brain cell — including the ability to translate chemical signals into electrical impulses, and communicate with other human cells.

Continue reading “Scientists Have Built Artificial Neurons That Fully Mimic Human Brain Cells” »

This post is also available in: עברית (Hebrew)

As everyday technologies get more and more advanced, cyber security must be at the forefront of every customer. Cyber security services have become common and are often used by private companies and the public sector in order to protect themselves from potential cyber attacks.

One of these services goes under the name Darktrace and has recently been acquired by Cybersprint, a Dutch provider of advanced cyber security services and a manufacturer of special tools that use machine learning algorithms to detect cyber vulnerabilities. Based on attack path modeling and graph theory, Darktrace’s platform represents organizational networks as directional, weighted graphs with nodes where multi-line segments meet and edges where they join. In order to estimate the probability that an attacker will be able to successfully move from node A to node B, a weighted graph can be used. Understanding the insights gained will make it easier for Darktrace to simulate future attacks.

At 2022 Tesla AI Day, Elon Musk gave the public its first look at his company’s humanoid robot nicknamed Optimus. He expects the production model to cost less than $20,000.

Today we’ll take a look at Tesla’s AI Day and the real star of the show. But first…

Tesla has unveiled its Optimus humanoid robot at its AI Day 2022 today and Elon Musk believes Tesla can bring it to market for “less than $20,000”.

As expected, the event started with Tesla unveiling a working prototype of its humanoid robot – a project first announced at Tesla’s AI day in 2021.

There were two prototypes unveiled at the event.

Brain-age (BA) estimates based on deep learning are increasingly used as neuroimaging biomarker for brain health; however, the underlying neural features have remained unclear. We combined ensembles of convolutional neural networks with Layer-wise Relevance Propagation (LRP) to detect which brain features contribute to BA. Trained on magnetic resonance imaging (MRI) data of a population-based study (n = 2,637, 18–82 years), our models estimated age accurately based on single and multiple modalities, regionally restricted and whole-brain images (mean absolute errors 3.37–3.86 years). We find that BA estimates capture ageing at both small and large-scale changes, revealing gross enlargements of ventricles and subarachnoid spaces, as well as white matter lesions, and atrophies that appear throughout the brain. Divergence from expected ageing reflected cardiovascular risk factors and accelerated ageing was more pronounced in the frontal lobe. Applying LRP, our study demonstrates how superior deep learning models detect brain-ageing in healthy and at-risk individuals throughout adulthood.

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