Lifeboat Foundation

Unifying machine learning and physics.

In this video, Dr. Ardavan (Ahmad) Borzou will discuss the history of unifications in physics and how we can unify physics and machine learning.

Continue reading “Unifying Physics and Machine Learning: The Next Big Breakthrough?” »

Child mortality in conflict settings was 8 percent, compared with 1.1 percent in peaceful countries.

It also said that 83.2 percent of the world’s poorest people live in sub-Saharan Africa and South Asia.

The index, compiled jointly with the Oxford Poverty and Human Development Initiative (OPHI), used indicators such as a lack of adequate housing, sanitation, electricity, cooking fuel, nutrition and school attendance to assess levels of “multidimensional poverty”

Documentary filmmaker Hans Busstra shares with us, with the aid of amazing and scientifically accurate animations of the molecular world, the background story of his journey from imaging the hardcore science of molecular biology to the fundamental insights of metaphysics.

Data is the new oil, as they say, and perhaps that makes Harvard University the new Exxon. The school announced Thursday the launch of a dataset containing nearly one million public domain books that can be used for training AI models. Under the newly formed Institutional Data Initiative, the project has received funding from both Microsoft and OpenAI, and contains books scanned by Google Books that are old enough that their copyright protection has expired.

Wired in a piece on the new project says the dataset includes a wide variety of books with “classics from Shakespeare, Charles Dickens, and Dante included alongside obscure Czech math textbooks and Welsh pocket dictionaries.” As a general rule, copyright protections last for the lifetime of the author plus an additional 70 years.

Foundational language models, like ChatGPT, that behave like a verisimilitude of a real human require an immense amount of high-quality text for their training—generally the more information they ingest, the better the models perform at imitating humans and serving up knowledge. But that thirst for data has caused problems as the likes of OpenAI have hit walls on how much new information they can find—without stealing it, at least.

Author(s): Jesus Rodriguez Originally published on Towards AI. Created Using IdeogramI recently started an AI-focused educational newsletter, that already has over 170,000 subscribers. TheSequence is a no-BS (meaning no hype, no news, etc) ML-oriented newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers, and concepts. Please give it a try by subscribing below:

The reliable control of traveling waves emerging from the coupling of oscillations and diffusion in physical, chemical and biological systems is a long-standing challenge within the physics community. Effective approaches to control these waves help to improve the present understanding of reaction-diffusion systems and their underlying dynamics.

Researchers at Université libre de Bruxelles (ULB) and Université de Rennes recently demonstrated a promising approach to control chemical waves in a type of fluid flow known as hyperbolic flow. Their experimental methods, outlined in Physical Review Letters recently, entail the control of chemical waves via the stretching and compression of fluids.

“At a summer school in Corsica, discussions between the Brussels and Rennes team triggered the curiosity to see how chemical waves studied at ULB in Brussels would behave in hyperbolic flows analyzed in Rennes,” Anne De Wit, senior author of the paper, told Phys.org. “The primary objective was to see how a non-trivial flow would influence the dynamics of waves.”

A study suggests that by the time H. sapiens expanded, the differentiation between the two species had progressed to the extent that they were distinct and recognizable as separate species.

A recent study conducted by researchers from London’s Natural History Museum and the Institute of Philosophy at KU Leuven has strengthened the argument that Neanderthals and modern humans (Homo sapiens) should be classified as distinct species to more accurately trace our evolutionary history.

Different researchers have different definitions as to what classifies as a species. It is undisputed that H. sapiens and Neanderthals originate from the same parental species, however studies into Neanderthal genetics and evolution have reignited the debate over whether they should be classed as separate from H. sapiens or rather a subspecies (H. sapiens neanderthalensis).

Mosasaurs are extinct marine lizards, spectacular examples of which were first discovered in 1766 near Maastricht in the Netherlands, fueling the rise of the field of vertebrate paleontology. Paleontologist Michael Polcyn presented the most comprehensive study to date on the early evolution and ecology of these extinct marine reptiles.

On 16 December, Polcyn will receive his Ph.D. from Utrecht University for his research into the evolution of the mosasaurs. Mosasaurs are a textbook example of macroevolution, the emergence of new and distinct groups of animals, above the level of species. Although they have been studied for centuries, new discoveries, novel research approaches, and the application of technology, are still teaching us about their relationships and behaviors, some of which continue to surprise us.

For example, through the use of detailed comparative anatomy aided by micro-CT scanning technology, we have gained a much better understanding of what group of lizards mosasaurs likely evolved from.

Dopamine is a powerful signal in the brain, influencing our moods, motivations, movements, and more. The neurotransmitter is crucial for reward-based learning, a function that may be disrupted in a number of psychiatric conditions, from mood disorders to addiction.

Now, researchers led by MIT Institute Professor Ann Graybiel have found surprising patterns of dopamine signaling that suggest neuroscientists may need to refine their model of how reinforcement learning occurs in the brain. The team’s findings were published recently in the journal Nature Communications.

Dopamine plays a critical role in teaching people and other animals about the cues and behaviors that portend both positive and negative outcomes; the classic example of this type of learning is the dog that Ivan Pavlov trained to anticipate food at the sound of bell.