Lifeboat Foundation

When you have, your symptoms depend on where in your body you have the condition.

What is spinal stenosis? It is the narrowing of the spine. This narrowing puts pressure on the spinal cord and nerves and can cause pain.

A novel approach in the field of Alzheimer’s research is emerging that could potentially transform how we tackle this debilitating disease. Recent studies have revealed a paradigm shift in understanding Alzheimer’s pathology, emphasizing the importance of targeting the early-stage aggregation of the pathogenic amyloid beta (A-beta) protein, specifically focusing on its soluble oligomeric form.

Over the past three decades, conventional treatments for Alzheimer’s have largely been ineffective, primarily due to their focus on combating the fibrillar form of A-beta. However, emerging research suggests that it is the soluble oligomeric form of A-beta that poses the greatest threat to neuronal health, leading to cognitive decline and neurotoxicity.

A recent breakthrough in Alzheimer’s treatment has come from the development of an antibody capable of recognizing both oligomeric and fibrillar forms of A-beta, offering newfound hope to the field. This innovative therapy has demonstrated promising results in delaying disease progression by up to 36% in individuals with early-to-mild cognitive impairment.

“They remove some of the magic,” said Dimitris Papailiopoulos, a machine learning researcher at the University of Wisconsin, Madison. “That’s a good thing.”

Training Transformers

Large language models are built around mathematical structures called artificial neural networks. The many “neurons” inside these networks perform simple mathematical operations on long strings of numbers representing individual words, transmuting each word that passes through the network into another. The details of this mathematical alchemy depend on another set of numbers called the network’s parameters, which quantify the strength of the connections between neurons.

“The Most Powerful Type Of Computing Machine That Is Possible In This Universe”

Aka Hyper Computers they are based on Quantum Computing & Gravity. They are agnostic to Causality i.e. they have Indefinite Causality (Cause & Effect Relationships)

Automatski is 5,000 years ahead of everyone else. It built the worlds first Quantum Gravity Computer in ~2006.

We perceive space and time to be continuous, but if the amazing theory of loop quantum gravity is correct, they actually come in discrete pieces.

By Lee Smolin

Want to know the answer to a problem before you even try to solve it? New Scientist has the computer for you.

I am, I’m slightly embarrassed to admit, quoted pretty extensively in the cover story of this week’s New Scientist magazine (alas, only available to subscribers or those willing to shell out $4.95). The story, by Michael Brooks, is about an interesting recent paper by Lucien Hardy of Perimeter Institute, on the power of “quantum gravity computers.” Lucien’s paper considers the following question: by exploiting quantum fluctuations in the causal structure of spacetime, can one efficiently solve problems that are not efficiently solvable with a garden-variety quantum computer?

As I told Brooks, I really do think this is a hell of a question, one that’s intimately related to the challenge of understanding quantum gravity itself. The trouble is that, until an actual quantum theory of gravity chooses to make itself known to us, almost everything we can say about the question is pure speculation.

But of course, pure speculation is what New Scientist gobbles up with french fries and coleslaw. And so, knowing what kind of story they were going to run, I did my best to advocate giving reality at least a few column inches. Fortunately, the end result isn’t quite as bad as I’d feared.

Everyone loves a two-for-one deal—even physicists looking to tackle unanswered questions about the cosmos. Now, scientists at the Department of Energy’s SLAC National Accelerator Laboratory are getting just such a twofer: Particle detectors originally developed to look for dark matter are now in a position to be included aboard the Line Emission Mapper (LEM), a space-based X-ray probe mission proposed for the 2030s.

I think AI agent workflows will drive massive AI progress this year — perhaps even more than the next generation of foundation models. This is an important trend, and I urge everyone who works in AI to pay attention to it.