Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Artificial intelligence (AI) plays an important role in many systems, from predictive text to medical diagnoses. Inspired by the human brain, many AI systems are implemented based on artificial neural networks, where electrical equivalents of biological neurons are interconnected, trained with a set of known data, such as images, and then used to recognize or classify new data points.

In traditional neural networks used for , the image of the target object is first formed on an , such as the in a smart phone. Then, the image sensor converts light into , and ultimately into the , which can then be processed, analyzed, stored and classified using computer chips. Speeding up these abilities is key to improving any number of applications, such as face recognition, automatically detecting text in photos, or helping self-driving cars recognize obstacles.

While current, consumer-grade image classification technology on a digital chip can perform billions of computations per second, making it fast enough for most applications, more sophisticated image classification such as identifying moving objects, 3D object identification, or classification of microscopic cells in the body, are pushing the computational limits of even the most powerful technology. The current speed limit of these technologies is set by the clock-based schedule of computation steps in a computer processor, where computations occur one after another on a linear schedule.

Read more | >

Electro-optic modulators, which control aspects of light in response to electrical signals, are essential for everything from sensing to metrology and telecommunications. Today, most research into these modulators is focused on applications that take place on chips or within fiber optic systems. But what about optical applications outside the wire and off the chip, like distance sensing in vehicles?

Current technologies to modulate light in are bulky, slow, static, or inefficient. Now, researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), in collaboration with researchers at the department of Chemistry at the University of Washington, have developed a compact and tunable electro-optic for free space applications that can modulate light at gigahertz speed.

“Our work is the first step toward a class of free-space electro-optic modulators that provide compact and efficient intensity modulation at gigahertz speed of free-space beams at telecom wavelengths,” said Federico Capasso, Robert L. Wallace Professor of Applied Physics and Vinton Hayes Senior Research Fellow in Electrical Engineering, senior author of the paper.

Read more | >

Researchers have pioneered a technique that can dramatically accelerate certain types of computer programs automatically, while ensuring program results remain accurate.

Their system boosts the speeds of programs that run in the Unix shell, a ubiquitous programming environment created 50 years ago that is still widely used today. Their method parallelizes these programs, which means that it splits program components into pieces that can be run simultaneously on multiple computer processors.

This enables programs to execute tasks like web indexing, , or analyzing data in a fraction of their original runtime.

Read more | >

Schizophrenia is a disorder that affects how people act, think, and perceive reality. It is often very difficult to treat because it has many different causes and symptoms. In a study published last month in Cell Reports Medicine, researchers from Tokyo Medical and Dental University (TMDU) have identified an autoantibody—a protein that is produced by the immune system to attach to a specific substance from the individual’s own body, rather than to a foreign substance like a virus or bacteria—in some patients with schizophrenia. Notably, they also found that this autoantibody caused schizophrenia-like behaviors and changes in the brain when they injected it into mice.

When considering possible autoantibodies that might cause schizophrenia, the research team had a specific protein in mind. Previous research has suggested that neural cell adhesion molecule (NCAM1), which helps cells in the brain talk to one another via specialized connections known as synapses, may have a role in the development of schizophrenia.

“We decided to look for autoantibodies against NCAM1 in around 200 healthy controls and 200 patients with schizophrenia,” explains lead author of the study Hiroki Shiwaku. “We only found these autoantibodies in 12 patients, suggesting that they may be associated with the disorder in just a small subset of schizophrenia cases.”

Read more | >

Methylation clocks are taking the longevity community by storm, but why are they so useful?

Do you know how old you really are? I am not doubting your ability to remember your birthday or questioning the honesty of your parents. Do you, on a fundamental level, know how ‘old’ your body truly is? Now surely that is just the same as the number of years you have been around, which would be your chronological age? Well in reality the answer to how ‘old’ your body is comes down to much more than simply how long you have been around for.

Allow me to explain by falling back to the commonly used automobile analogy. Let’s imagine I bought two identical Ford Escorts in 1982, and then proceeded to place one of them inside a time capsule, where it would be kept at a constant temperature in a non-reactive atmosphere. I then proceeded to drive the second car for the next 40 years. Over that 40 years, this car is going to experience wear and tear, and will most likely break down several times which will require mechanical intervention (analogous to medical intervention). Now, after this 40-year period I am going to take the first car out of storage and compare the two cars side by side. Which car is in the better condition? Well, the car that was preserved, obviously. Which car is likely to last the longest from that point onward? Well, the car which has been preserved, obviously.

Read more | >

Understanding the early universe has been a goal for scientists for decades. And, now with NASA’s James Webb space telescope, and other technology, we’re finally making some decent strides. A new simulation on early galaxy formation could be another key stepping stone, too.

Researchers created the simulation using machine learning. It then completed over 100,000 hours of computations to create the one-of-a-kind simulation. The researchers named the algorithm responsible for the project Hydo-BAM. They published a paper with the simulation’s findings earlier this year.

Creating a simulation of early galaxy formation has allowed researchers to chart the earliest moments of our universe. These important moments began just after the Big Bang set everything into motion. Understanding these key moments of the formation of the early universe could help us better understand how galaxies form in the universe today.

Read more | >

One day soon, buildings could become more energy-efficient—and environmentally sustainable—with insulating material developed from wood by researchers in Sweden. The newly-developed material offers as good or even better thermal performance than ordinary plastic-based insulation materials, according to researchers reporting recently in ACS Applied Materials & Interfaces.

Yuanyuan Li, an assistant professor at Wallenberg Wood Science Center, KTH Royal Institute of Technology in Stockholm, says that the new insulating material is an aerogel integrated wood which is made without adding additional substances.

Wood cellulose aerogels themselves are nothing new—researchers have been developing advanced types of aerogels and other composites for the last several years in the Wallenberg Wood Science Center at KTH—but Li says the new method represents a breakthrough in controlled creation of insulating nanostructures in the pores of wood.

Read more | >