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Michael Levin is a Distinguished Professor in the Biology department at Tufts University. He holds the Vannevar Bush endowed Chair and serves as director of the Allen Discovery Center at Tufts and the Tufts Center for Regenerative and Developmental Biology. To explore the algorithms by which the biological world implemented complex adaptive behavior, he got dual B.S. degrees, in CS and in Biology and then received a PhD from Harvard University. He did post-doctoral training at Harvard Medical School, where he began to uncover a new bioelectric language by which cells coordinate their activity during embryogenesis. The Levin Lab works at the intersection of developmental biology, artificial life, bioengineering, synthetic morphology, and cognitive science.

✅EPISODE LINKS:
👉Round 1: https://youtu.be/v6gp-ORTBlU
👉Mike’s Website: https://drmichaellevin.org/
👉New Website: https://thoughtforms.life.
👉Mike’s Twitter: https://twitter.com/drmichaellevin.
👉Mike’s YouTube: https://youtube.com/@drmichaellevin.
👉Mike’s Publications: https://tinyurl.com/yc388vvk.
👉The Well: https://www.youtube.com/watch?v=0a3xg4M9Oa8 & https://youtu.be/XHMyKOpiYjk.
👉Aeon Essays: https://aeon.co/users/michael-levin.

✅TIMESTAMPS:
0:00 – Introduction.
1:27 – The Prisoner’s Dilemma (Game Theory applied to Life)
7:55 – Computational Boundary of the Self.
10:17 – “Goal States” & “Cognitive Light Cones”
13:55 – To Naturalise Cognition.
19:00 – The Hard Problem of Consciousness.
23:10 – Defining Consciousness.
27:14 – The Field of Diverse Intelligence.
43:25 – Who inspired Mike within his field.
46:52 – Is Mike a Panpsychist?
52:09 – Thoughts on Illusionism.
55:44 – Links to IIT
57:56 – Technological Approach to Mind Everywhere (TAME 2.0)
1:02:14 – Proof of Humanity Certification.
1:10:00 – Phase Transitions in Mathematics.
1:15:26 – Bioelectric Medicine.
1:21:06 – Can Cells Think? What is the Self? Is Man a Machine?
1:28:55 – Metacognition & Cloning.
1:35:49 – Teleology, Teleonomy & Teleophobia.
1:50:08 – All Intelligence is Collective Intelligence.
1:54:33 — Conclusion.

Video Title: What is The Field of Diverse Intelligence? Hacking the Spectrum of Mind & Matter | Michael Levin.

Catastrophic forgetting, an innate issue with backpropagation learning algorithms, is a challenging problem in artificial and spiking neural network (ANN and SNN) research.

The brain has somewhat solved this problem using multiscale plasticity. Under global regulation through specific pathways, neuromodulators are dispersed to target , where both synaptic and neuronal plasticity are modulated by neuromodulators locally. Specifically, neuromodulators modify the capacity and property of neuronal and . This modification is known as metaplasticity.

Researchers led by Prof. Xu Bo from the Institute of Automation of the Chinese Academy of Sciences and their collaborators have proposed a novel brain-inspired learning method (NACA) based on neural modulation dependent plasticity, which can help mitigate catastrophic forgetting in ANN and SNN. The study was published in Science Advances on Aug. 25.

Consciousness is usually ascribed to a specific set of mechanisms and functional capabilities of the complex brain. Importantly, those mechanisms (ion channels, electrical networks, neurotransmitter machinery) long pre-date the evolutionary innovation of nervous systems. Moreover, the algorithms and competencies such as memory, decision-making, and information integration likewise have an ancient evolutionary origin: before they controlled moving the body through 3D space, electrical networks moved body configurations through anatomical morphospace. In this talk, I will describe how we view the morphogenesis during embryonic development and regeneration as the behavior of a collective intelligence, which has many problem-solving capacities. I will describe the tools we have developed, paralleling neuroscientists’ attempts to read and write mental content by control of electrophysiology, to decode and re-write the pattern memories of the body. This has significant implications not only for biomedicine and evolutionary biology, but also for questions about consciousness and the scaling of coherent Selves from agential materials. I will conclude with some conjectures about what this new field offers the science of consciousness, in the form of new embodied living creatures that are outside the natural evolutionary stream of Earth, and the quest for theories of consciousness.-https://www.drmichaellevin.org/ Participate in our online research survey-Survey on Diverse intelligence-https://tufts.qualtrics.com/jfe/form/SV_eE51vKE34q3hexo (takes 9 minutes). Thank you.

Edited by Emilio Manzotti.
https://github.com/emilim/

In an era of growing digitalisation, data centers have emerged as the fundamental support of our technological framework. However, worries persist over the ecological effects due to their swift growth and power-demanding activities. These data centers rank among the planet’s most energy-intensive establishments, drawing substantial electricity to fuel servers, cooling mechanisms, and auxiliary apparatus vital for their operations. Such elevated energy usage significantly affects the environment by adding to greenhouse gas discharges and ushering climate change.

The AI Power Consumption Challenge

The growing surge of AI (Artificial Intelligence) in recent years has been a remarkable and transformative phenomenon. However, AI models and algorithms are highly resource-intensive and consume significant amounts of power. Training AI models involve massive computational workloads, often requiring specialised hardware accelerators like GPUs, which consume substantial energy. This power consumption is a major concern when it comes to making data centers greener.

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Welcome to our latest educational video, “The 9 AI Skills You Need NOW to Stay Ahead of 97% of People.” This video is designed for anyone eager to take a deep dive into the world of artificial intelligence and machine learning. Our goal is to provide you with the most essential AI skills needed to excel in this rapidly evolving field, keeping you ahead of the curve and well-positioned in the job market.

In this comprehensive guide, we explore nine fundamental AI skills, ranging from understanding algorithms to deep learning, data science, natural language processing, computer vision, robotics, and more. We also provide practical tips on how to apply these skills in real-world scenarios, whether you’re an AI enthusiast or a seasoned professional.

AI is not just the future; it’s here NOW. By acquiring these nine essential AI skills, you can position yourself among the top 3% of people who are ready to shape the future. Don’t be left behind as AI transforms industries, from healthcare and finance to entertainment and transportation.

This video is a must-watch for anyone interested in AI, machine learning, data analysis, robotics, or any related field. Whether you’re just starting out, looking to upskill, or aiming to stay ahead in your career, these nine AI skills are your key to success.

It sometimes presents incorrect steps to arrive at the answer, because it is designed to base conclusions on precedent. And a precedent based on a given data set is limited to the confines of the data set. This, says Microsoft, leads to “increased costs, memory, and computational overheads.”

AoT to the rescue. The algorithm evaluates whether the initial steps—” thoughts,” to use a word generally associated only with humans—are sound, thereby avoiding a situation where an early wrong “thought” snowballs into an absurd outcome.

Though not expressly stated by Microsoft, one can imagine that if AoT is what it’s cracked up to be, it might help mitigate the so-called AI “hallucinations”—the funny, alarming phenomenon whereby programs like ChatGPT spits out false information. In one of the more notorious examples, in May 2023, a lawyer named Stephen A. Schwartz admitted to “consulting” ChatGPT as a source when conducting research for a 10-page brief. The problem: The brief referred to several court decisions as legal precedents… that never existed.

This post is also available in: he עברית (Hebrew)

At a crucial time when the development and deployment of AI are rapidly evolving, experts are looking at ways we can use quantum computing to protect AI from its vulnerabilities.

Machine learning is a field of artificial intelligence where computer models become experts in various tasks by consuming large amounts of data, instead of a human explicitly programming their level of expertise. These algorithms do not need to be taught but rather learn from seeing examples, similar to how a child learns.

This book, ‘The Singularity Is Near’, predicts the future. However, unlike most best-selling futurology books, its author, Kurzweil, is a renowned technology expert. His insights into the future are not technocratic wild fantasies but are rooted in his profound contemplation of technological principles.

This audio informs us that, due to Moore’s Law, the pace of human technological advancement in the future will far exceed our expectations. By 2045, we will reach the technological ‘Singularity’, which will profoundly alter our human condition, and technology may even enable humans to conquer the universe within a millennium.

The author, Ray Kurzweil, is a true tech maestro. He has been inducted into the National Inventors Hall of Fame in the U.S., is a recipient of the National Medal of Technology, holds 13 honorary doctorates, has been lauded by three U.S. presidents, and is dubbed by the media as the ‘rightful heir to Thomas Edison’.

In the audio, you will hear:

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Welcome to our channel! In this exciting video, we delve into the fascinating realm of artificial intelligence (AI) and explore the question that has intrigued tech enthusiasts and experts alike: “How powerful will AI be in 2030?” Join us as we embark on a captivating journey into the future of AI, examining the possibilities, advancements, and potential impact that await us.

In the next decade, AI is poised to revolutionize numerous industries and transform the way we live and work. As we peer into the crystal ball of technological progress, we aim to shed light on the potential power and capabilities that AI could possess by 2030. Brace yourself for mind-blowing insights and expert analysis that will leave you in awe.

We begin by exploring the current state of AI and its rapid advancements. From machine learning algorithms to neural networks and deep learning models, AI has already demonstrated exceptional prowess in various fields, including healthcare, finance, transportation, and more. By building upon these achievements, AI is set to evolve exponentially, opening doors to a future where intelligent machines collaborate seamlessly with humans.

Throughout this video, we delve into key areas where AI is expected to make significant strides by 2030. We discuss advancements in natural language processing, computer vision, robotics, and autonomous systems. Witness the potential of AI-powered virtual assistants, autonomous vehicles, medical diagnostics, and even the integration of AI in our daily lives.