Lifeboat Foundation

Back pain is a common condition with numerous causes, including poor posture, overexertion, constant stress at work or at home, lack of exercise, and poor posture. For a considerable number of patients, the symptoms are chronic, meaning they last a long period or reoccur repeatedly. However, port and exercise therapy, when done properly, can provide alleviation.

Physiotherapy, as well as strength and stability exercises, are common treatment options. But how can the treatment be as effective as possible? Which method reduces pain the most effectively? A recent meta-analysis published in the Journal of Pain by Goethe University Frankfurt revealed new insights.

The researchers began with data from 58 randomized controlled trials (RCTs) involving over 10,000 individuals suffering from chronic low back pain throughout the globe. The relevant data from the original manuscripts were first filtered out and then analyzed in groups. When analyzing this data, the researchers looked at whether and how conventional forms of therapy and individualized treatment varied in terms of outcome. “Individualized” refers to some kind of personal coaching where therapists precisely target the needs and potentials of each patient and collaborate with them to choose the course of their treatment.

To show how computer chips are improving a bit, my first computer, an Apple II+ based on the 6,502 chip, had 7 bytes of memory on the chip. Nvidia’s H100 chip has 85,986,377,728 bytes of memory on it!

The 6,502 was a very successful chip and is still made today, with over 6 billion units sold!

Continue reading “MOS Technology 6502” »

The James Webb Space Telescope’s first images of the distant universe shocked astronomers. Is the discovery of unimaginably distant galaxies a mirage or a revolution?

A bit concerning cellular reprogramming after a few minutes, and stating a goal just before 7:00 a stated goal of reversing aging across the entire human.

AI-generated art has arrived.

With a presentation making its debut this week at The Museum of Modern Art in New York City — perhaps the world’s premier institution devoted to modern and contemporary art — the AI technologies that have upended trillion-dollar industries worldwide over the past decade will get a formal introduction.

Created by pioneering artist Refik Anadol, the installation in the museum’s soaring Gund Lobby uses a sophisticated machine-learning model to interpret the publicly available visual and informational data of MoMA’s collection.

“There are no hard limits imposed by biology or by physics that says that we can’t live better longer,” Kristen Fortney, CEO of San Francisco-based BioAge Labs, told the outlet. Focused on discerning the markers of aging, BioAge Labs is using large amounts of biobank blood and tissue samples to do so.

The company has already found a drug target that slows aging-linked muscle loss in mice.

“There is a protein called apelin that circulates in the blood, and we saw that middle-aged people with higher levels of apelin in their blood were living longer, with better muscle function and better cognitive function as they age,” Fortney said, according to Express.

Astronomers believed in a different sequence in solar system formation with stars igniting before planets began to form. New data says no!

Its why we should reverse engineer lab rat brains, crow brains, pigs, and chimps, ending on fully reverse engineering the human brain. even if its a hassle. i still think could all be done by end of 2025.

Last year, MIT researchers announced that they had built “liquid” neural networks, inspired by the brains of small species: a class of flexible, robust machine learning models that learn on the job and can adapt to changing conditions, for real-world safety-critical tasks, like driving and flying. The flexibility of these “liquid” neural nets meant boosting the bloodline to our connected world, yielding better decision-making for many tasks involving time-series data, such as brain and heart monitoring, weather forecasting, and stock pricing.

But these models become computationally expensive as their number of neurons and synapses increase and require clunky computer programs to solve their underlying, complicated math. And all of this math, similar to many physical phenomena, becomes harder to solve with size, meaning computing lots of small steps to arrive at a solution.

Continue reading “Solving brain dynamics gives rise to flexible machine-learning models” »