Lifeboat Foundation

Abstract: In ecological systems, be it a garden or a galaxy, populations evolve from some initial value (say zero) up to a steady state equilibrium, when the mean number of births and deaths per unit time are equal. This equilibrium point is a function of the birth and death rates, as well as the carrying capacity of the ecological system itself. The growth curve is S-shaped, saturating at the carrying capacity for large birth-to-death rate ratios and tending to zero at the other end. We argue that our astronomical observations appear inconsistent with a cosmos saturated with ETIs, and thus SETI optimists are left presuming that the true population is somewhere along the transitional part of this S-curve. Since the birth and death rates are a-priori unbounded, we argue that this presents a fine-tuning problem. Further, we show that if the birth-to-death rate ratio is assumed to have a log-uniform prior distribution, then the probability distribution of the ecological filling fraction is bi-modal — peaking at zero and unity. Indeed, the resulting distribution is formally the classic Haldane prior, conceived to describe the prior expectation of a Bernoulli experiment, such as a technological intelligence developing (or not) on a given world. Our results formally connect the Drake Equation to the birth-death formalism, the treatment of ecological carrying capacity and their connection to the Haldane perspective.

From: David Kipping [view email].

While generative AI tools have been heralded as the future of education, more than 40 years of academic research suggests that it could also harm learning in realms from online tutoring to employee training for three reasons. First, the best student-teacher relationships are empathetic ones but it is biologically impossible for humans and AI to develop mutual empathy. Second, AI might help us bypass the boring task of knowledge accumulation but it is only through that process that we develop higher order thinking skills. Finally, digital tools are notoriously distracting and multitasking diminishes learning. As we think about the benefits of new technology, we must also consider the risks.

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Three fundamental problems with using LLMs as teachers, tutors, and trainers.

Touch, hit, and drag objects with VR-GS.

Study develops a ConvLSTM model that accurately predicts patient deterioration based on facial expressions, achieving 99.89% accuracy, with potential to improve early detection in healthcare settings.

A new method of detecting criticality from time-series data outperforms conventional metrics in the presence of variable noise levels for both simulated systems and real neural recordings.

👉 Researchers have developed an AI system called “The AI Scientist” that can perform scientific research on its own, from brainstorming and experimenting to writing full papers.

A new AI system called “The AI Scientist” can perform scientific research completely autonomously, from brainstorming and experimenting to writing complete papers.

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Continue reading “Automated research: The AI Scientist generates papers for 15 dollars each” »

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Almost 2.7 billion records of personal information for people in the United States were leaked on a hacking forum, exposing names, social security numbers, all known physical addresses, and possible aliases.

The data allegedly comes from National Public Data, a company that collects and sells access to personal data for use in background checks, to obtain criminal records, and for private investigators.

National Public Data is believed to scrape this information from public sources to compile individual user profiles for people in the US and other countries.

The striking object appeared as bright as Saturn in the vicinity of the constellation Cassiopeia, and historical chronicles from China and Japan recorded it as a “guest star.”

Chinese astronomers used this term to signify a temporary object in the sky, often a comet or, as in this case, a supernova — a cataclysmic explosion of a star at the end of its life.

The object, now known as SN 1,181, is one of a handful of supernovas documented before the invention of telescopes, and it has puzzled astronomers for centuries.