Lifeboat Foundation

Circa 2021 face_with_colon_three

Welwitschia mirabilis is a unique plant that only has two leaves, but it can survive in hostile conditions of the African desert. Here, the authors report its chromosome-level genome assembly and discuss how gene function and regulation have given rise to its unique morphology and environmental adaptions.

Training a machine-learning model to effectively perform a task, such as image classification, involves showing the model thousands, millions, or even billions of example images. Gathering such enormous datasets can be especially challenging when privacy is a concern, such as with medical images. Researchers from MIT and the MIT-born startup DynamoFL have now taken one popular solution to this problem, known as federated learning, and made it faster and more accurate.

Federated learning is a collaborative method for training a machine-learning model that keeps sensitive user data private. Hundreds or thousands of users each train their own model using their own data on their own device. Then users transfer their models to a central server, which combines them to come up with a better model that it sends back to all users.

A collection of hospitals located around the world, for example, could use this method to train a machine-learning model that identifies brain tumors in medical images, while keeping patient data secure on their local servers.

The head of Google parent company Alphabet chose an funny example to allay fears of artificial intelligence.

Scientists have detected a sunspot that’s so huge it’s changing the way our sun vibrates.

Sunspots appear as dark blotches on the sun’s surface because they are cooler than the surrounding areas. They form where magnetic fields are particularly strong, driven by the electrically charged gases that constantly swirl inside our nearest star.

Sometimes these magnetic fields can be so intense that they prevent some heat from reaching the surface, forming a sunspot.

According to research from the Center for Genomic Regulation (CRG) published in the journal Nature, immature human egg cells bypass a critical metabolic process believed to be necessary for producing energy.

The cells modify their metabolism to stop producing reactive oxygen species, dangerous molecules that can accumulate, damage DNA

DNA, or deoxyribonucleic acid, is a molecule composed of two long strands of nucleotides that coil around each other to form a double helix. It is the hereditary material in humans and almost all other organisms that carries genetic instructions for development, functioning, growth, and reproduction. Nearly every cell in a person’s body has the same DNA. Most DNA is located in the cell nucleus (where it is called nuclear DNA), but a small amount of DNA can also be found in the mitochondria (where it is called mitochondrial DNA or mtDNA).

A look at revolutionary new materials with seemingly impossible properties.
Start protecting your internet experience today with 77% off a 3 year plan by using code ‘ISAAC’ at http://www.NordVPN.com/ISAAC
Metamaterials offer many properties normally not found in nature, from superior lenses and communications to stealth applications, potentially offering invisibility. Today we’ll examine the science behind that and look at many other possible applications.

AMA thread tonight (Thursday March 29) at 6 PM EST over at /r/space on reddit: https://www.reddit.com/r/space/comments/881rbl/ama_this_is_i…_anything/

Continue reading “Advanced Metamaterials” »

As demonstrated by breakthroughs in various fields of artificial intelligence (AI), such as image processing, smart health care, self-driving vehicles and smart cities, this is undoubtedly the golden period of deep learning. In the next decade or so, AI and computing systems will eventually be equipped with the ability to learn and think the way humans do—to process continuous flow of information and interact with the real world.

However, current AI models suffer from a performance loss when they are trained consecutively on new information. This is because every time new data is generated, it is written on top of existing data, thus erasing previous information. This effect is known as “catastrophic forgetting.” A difficulty arises from the stability-plasticity issue, where the AI model needs to update its memory to continuously adjust to the new information, and at the same time, maintain the stability of its current knowledge. This problem prevents state-of-the-art AI from continually learning from real world information.

Edge computing systems allow computing to be moved from the cloud storage and data centers to near the original source, such as devices connected to the Internet of Things (IoTs). Applying continual learning efficiently on resource limited edge computing systems remains a challenge, although many continual learning models have been proposed to solve this problem. Traditional models require high computing power and large memory capacity.

It was all quite predictable, really. Meta, Facebook’s parent company, released the latest version of its groundbreaking AI chatbot in August 2022. Immediately, journalists around the world began peppering the system, called BlenderBot3, with questions about Facebook. Hilarity ensued.

Wolfgang “Wolfi” Mittig and Yassid Ayyad began their search for dark matter—also referred to as the missing mass of the universe—in the heart of an atom.

An atom is the smallest component of an element. It is made up of protons and neutrons within the nucleus, and electrons circling the nucleus.