Lifeboat Foundation

New study demonstrates the potential for machine learning to accelerate the development of innovative drug delivery technologies.

Scientists at the University of Toronto have successfully tested the use of machine learning models to guide the design of long-acting injectable drug formulations. The potential for machine learning algorithms to accelerate drug formulation could reduce the time and cost associated with drug development, making promising new medicines available faster.

The study will be published today (January 10, 2023) in the journal Nature Communications.

— If human-level AGI is created in the next 10 yrs, whaddaya guess will be the underlying tech? — Deep NNs? Hybrid neural/symbolic/evolutionary cognitive arch. e.g. OpenCog Hyperon? Comp. Neuroscience? Something wild and utterly new?

The science of dinosaur resurrection: using AI to bring prehistoric creatures back to life.

Humans have the genes to grow hair all over their bodies like chimpanzees but evolution has disabled them, according to new findings which could lead to new ways of regrowing hair after balding The discovery of “caveman genes” could help scientists come up with a new cure for baldness.

Summary: Astrocytes play a crucial role in spatial learning, researchers discovered.

Source: University of Bonn.

There are two fundamentally different cell types in the brain, neurons and glial cells. The latter, for example, insulate the “wiring” of nerve cells or guarantee optimal working conditions for them.

https://www.youtube.com/watch?v=6ndGrWXoEbc

In this video I discuss the Future of Reality… What will be the Next Quadrillion Dollar Company in Tech? A company like Synchron.

MY GEAR (af links):
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Continue reading “This is Quadrillion Dollar Technology” »

Metaculus is a community dedicated to generating accurate predictions about future real-world events by aggregating the collective wisdom, insight, and intelligence of its participants.

Researchers at DeepMind in London have shown that artificial intelligence (AI) can find shortcuts in a fundamental type of mathematical calculation, by turning the problem into a game and then leveraging the machine-learning techniques that another of the company’s AIs used to beat human players in games such as Go and chess.

The AI discovered algorithms that break decades-old records for computational efficiency, and the team’s findings, published on 5 October in Nature¹, could open up new paths to faster computing in some fields.

“It is very impressive,” says Martina Seidl, a computer scientist at Johannes Kepler University in Linz, Austria. “This work demonstrates the potential of using machine learning for solving hard mathematical problems.”

Accessing Wolfram|Alpha’s computational knowledge with ChatGPT—an ideal alliance of precise combination with human-like expression of ideas. Stephen Wolfram explains how.