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Welcome to Impact Theory, I’m Tom Bilyeu and in today’s episode, Nick Bostrom and I dive into the moral and societal implications of AI as it becomes increasingly advanced.

Nick Bostrom is a leading philosopher, author, and expert on AI here to discuss the future of AI, its challenges, and its profound impact on society, meaning, and our pursuit of happiness.

We touch on treating AI with moral consideration, the potential centralization of power, automation of critical sectors like police and military, and the creation of hyper-stimuli that could impact society profoundly.

Continue reading ““Life Will Get Weird The Next 3 Years!” — Future of AI, Humanity & Utopia vs Dystopia | Nick Bostrom” | >

Scientists say a phenomenon called “skin conductance,” which changes when you sweat, is a surprisingly accurate method for detecting emotions — with future robots that detect this able to tell your emotions.

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Summary: A study reveals how brain cell interactions influence aging, showing that rare cell types either accelerate or slow brain aging. Neural stem cells provide a rejuvenating effect on neighboring cells, while T cells drive aging through inflammation. Researchers used advanced AI tools and a spatial single-cell atlas to map cellular interactions across the lifespan in mice.

This work sheds light on how interventions, such as enhancing neural stem cells, might combat neurodegeneration. By understanding these cellular dynamics, scientists can explore tailored therapies to slow aging and promote brain resilience. The findings also offer insights into conditions like Alzheimer’s disease, highlighting the importance of cell-to-cell interactions.

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A Chinese robotics firm has started mass-producing humanoid robots for general use, while its US counterparts, like Tesla, are aiming for such a feat in 2026.

Agibot, or Zhiyuan Robotics, showcased footage of its manufacturing facility on its official website and revealed that it’s on course to produce 1,000 units by the end of the year, according to a Chinese online news outlet.

Founded in February 2023 by Peng Zhihui, a former participant in Huawei’s “Genius Youth” program, the Shanghai-based startup launched its first humanoid robot model, the Raise A1, in August 2023.

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Scientists used AI to estimate the brain age of 739 healthy seniors and found that lifestyle and health conditions impact brain aging.

Researchers at Karolinska Institutet have used an AI tool to estimate the biological age of brains from MRI scans of 70-year-olds. Their analysis revealed that factors harmful to vascular health, such as inflammation and high blood sugar levels, are linked to older-looking brains, while a healthy lifestyle was associated with younger-looking brains. These findings were published today (December 20) in Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association.

Leveraging AI to determine brain age.

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Run by the team at orchestration, AI, and automation platform Tines, the Tines library contains pre-built workflows shared by real security practitioners from across the community, all of which are free to import and deploy via the Community Edition of the platform.

Their bi-annual “You Did What with Tines?!” competition highlights some of the most interesting workflows submitted by their users, many of which demonstrate practical applications of large language models (LLMs) to address complex challenges in security operations.

One recent winner is a workflow designed to automate CrowdStrike RFM reporting. Developed by Tom Power, a security analyst at The University of British Columbia, it uses orchestration, AI and automation to reduce the time spent on manual reporting.

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Crafting a unique and promising research hypothesis is a fundamental skill for any scientist. It can also be time consuming: New PhD candidates might spend the first year of their program trying to decide exactly what to explore in their experiments. What if artificial intelligence could help?

MIT researchers have created a way to autonomously generate and evaluate promising research hypotheses across fields, through human-AI collaboration. In a new paper, they describe how they used this framework to create evidence-driven hypotheses that align with unmet research needs in the field of biologically inspired materials.

Published Wednesday in Advanced Materials, the study was co-authored by Alireza Ghafarollahi, a postdoc in the Laboratory for Atomistic and Molecular Mechanics (LAMM), and Markus Buehler, the Jerry McAfee Professor in Engineering in MIT’s departments of Civil and Environmental Engineering and of Mechanical Engineering and director of LAMM.

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Research published in The American Journal of Human Genetics has identified a previously unknown genetic link to autism spectrum disorder (ASD). The study found that variants in the DDX53 gene contribute to ASD, providing new insights into the genetic underpinnings of the condition.

ASD, which affects more males than females, encompasses a group of neurodevelopmental conditions that result in challenges related to communication, social understanding and behavior. While DDX53, located on the X chromosome, is known to play a role in brain development and function, it was not previously definitively associated with autism.

In the study, researchers from The Hospital for Sick Children (SickKids) in Canada and the Istituto Giannina Gaslini in Italy clinically tested 10 individuals with ASD from eight different families and found that variants in the DDX53 gene were maternally inherited and present in these individuals. Notably, the majority were male, highlighting the gene’s potential role in the male predominance observed in ASD.

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