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In a recent study in Nature Communications, researchers increased synaptic serotonin through a selective serotonin-releasing agent (SSRA), fenfluramine, to investigate its impact on human behavior.

Neuroscience research concentrates on the function of central serotonin (5HT) in human behavior, specifically the impact of selective serotonin reuptake inhibitors (SSRIs). Serotonin is necessary for several actions, including eating, sexual function, and goal-directed cognition.

It is difficult to determine the causal relationship between increased synaptic 5-HT and behavior in humans via SSRIs due to SSRIs’ complicated effects on 5-HT and colocalized neurotransmitter systems. A low dose of fenfluramine, approved for the treatment of Dravet epilepsy in 2020, directly and swiftly elevates synaptic 5-HT without altering extracellular dopamine concentrations in mood control areas.

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Microsoft on Tuesday shipped fixes to address a total of 90 security flaws, including 10 zero-days, of which six have come under active exploitation in the wild.

Of the 90 bugs, seven are rated Critical, 79 are rated Important, and one is rated Moderate in severity. This is also in addition to 36 vulnerabilities that the tech giant resolved in its Edge browser since last month.

The Patch Tuesday updates are notable for addressing six actively exploited zero-days.

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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].

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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.

Page-utils class= article-utils—vertical hide-for-print data-js-target= page-utils data-id= tag: blogs.harvardbusiness.org, 2007/03/31:999.387329 data-title= The Limits of GenAI Educators data-url=/2024/07/the-limits-of-genai-educators data-topic= AI and machine learning data-authors= Jared Cooney Horvath data-content-type= Digital Article data-content-image=/resources/images/article_assets/2024/07/Jul24_17_545985287-383x215.jpg data-summary=

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

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👉 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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Researchers from the University of British Columbia, University of Oxford, and AI startup Sakana AI have developed an AI system capable of conducting scientific research independently. Named “The AI Scientist,” the system can generate new research ideas, write code, perform experiments, visualize results, and even compose complete scientific papers.

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