Lifeboat Foundation

Soon, you might not need anything more specialized than a readily accessible touchscreen device and any existing data sets you have access to in order to build powerful prediction tools. A new experiment from MIT and Brown University researchers have added a capability to their ‘Northstar’ interactive data system that can “instantly generate machine-learning models” to use with their exiting data sets in order to generate useful predictions.

One example the researchers provide is that doctors could make use of the system to make predictions about the likelihood their patients have of contracting specific diseases based on their medial history. Or, they suggest, a business owner could use their historical sales data to develop more accurate forecasts, quickly and without a ton of manual analytics work.

Researchers are calling this feature the Northstar system’s “virtual data scientist,” (or VDS) and it sounds like it could actually replace the human equivalent, especially in settings where one would never actually be readily available or resourced anyway. Your average doctor’s office doesn’t have a dedicated data scientist headcount, for instance, and nor do most small- to medium-sized businesses for that matter. Independently owned and operated coffee shops and retailers definitely wouldn’t otherwise have access to this kind of insight.

One simple pro mod for better aerial images

Multirotors and sports cameras are very nearly synonymous at this point in time. The popularity of one has undoubtedly boosted the popularity of the other. I bought my first DJI Phantom in part because I already owned a GoPro and wanted to see if I could make it fly. For others, it may be that they already owned a quadcopter and wanted to see if they could lift a camera with it. Yet this mutually beneficial symbiosis hasn’t led to any significant changes in the way sports cameras are made, notably the lens. But with a simple modification, you can make that camera even more sky-worthy.

Fishes don’t fly.

The discovery could help overcome a major quantum computing hurdle.

Walking the show floor at Amazon re: MARS.

Scientific collaborators from Carnegie Mellon University and University of Minnesota have created a way for people to control a robotic arm using a non-invasive brain-computer interface (BCI). Previously, electrode array implants in the brain have been necessary to give severely disabled people the ability to manipulate an external robot. That is because implants can gather more actionable signal information by being placed right on the surface of the brain. Avoiding dangerously invasive brain surgery to place these implants, though, is a big goal in the field of brain-computer interfaces.

The Carnegie Mellon team turned to newly developed sensing and machine learning methods to accurately read signals coming from deep within the brain, relying only on an external electroencephalography cap for signal gathering. The system can quickly improve both its performance and that of the person using it, to achieve drastically better results than previous solutions. Volunteers using the technology were put through a pursuit task and a training regimen to improve their engagement, while the system was performing an analysis of their brain signals.

Continue reading “Severely Disabled People Mind-Control a Robotic Arm via EEG” »

Although the exact causes of multiple sclerosis still remain unknown, it is assumed that the disease is triggered by a combination of genetic and environmental risk factors. But which? In a mouse model of the disease, researchers at the University of Geneva (UNIGE) and the Geneva University Hospitals (HUG), Switzerland, studied the potential link between transient cerebral viral infections in early childhood and the development of this cerebral autoimmune disease later in life. Indeed, the brain area affected by viral infection during childhood undergoes a change that can call, a long time later, on the immune system to turn against itself at this precise location, triggering autoimmune lesions. These results, which are published in the journal Science Translational Medicine, provide a first step in answering one of the possible environmental causes of this serious disease.

Multiple sclerosis affects one in 1,000 people in Switzerland, two-thirds of whom are women. It is the most common auto-immune disease affecting the brain. Up to date, there is still neither a cure available, nor a clear understanding of the factors that trigger this disease at around 30 years of age. “We asked ourselves whether brain viral infections that could be contracted in early childhood were among the possible causes,” says Doron Merkler, a professor in the Department of Pathology and Immunology in UNIGE’s Faculty of Medicine and senior consultant in the Clinical Pathology Service of the HUG. Such transient brain infections can be controlled quickly by the immune system, without the affected individual even noticing any symptoms. “But these transient infections may, under certain circumstances, leave a local footprint, an inflammatory signature, in the brain,” continues the researcher.

On June 27, 2019, NASA announced a new mission to Saturn’s moon Titan featuring a rotorcraft lander. — Mission was proposed in 2017: https://www.space.com/36598-dragonfly-quadcopter-saturn-moon-titan-explorer.html

Credit: NASA

Calico is a research and development company whose mission is to harness advanced technologies to increase our understanding of the biology that controls lifespan.

A 3D-printed prosthetic hand controlled using a new AI-based approach could significantly lower the cost of bionic limbs for amputees.

Real need: There are approximately 540,000 upper-limb amputees in the United States, but sophisticated “myoelectric” prosthetics, controlled by muscle contractions, are still very expensive. Such devices cost between $25,000 and $75,000 (not including maintenance and repair), and they can be difficult to use because it is hard for software to distinguish between different muscle flexes.

Handy invention: Researchers in Japan came up with a cheaper, smarter myoelectric device. Their five-fingered, 3D-printed hand is controlled using a neural network trained to recognize combined signals—or, as they call them, “muscle synergies.” Details of the bionic hand are published today in the journal Science Robotics.