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Category: information science – Page 103

Michael Levin: Cognition and diverse intelligence in non-neural cellular collectives

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/

A Sustainable Strategy to Create Eco-friendlier Datacenters

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.

The 9 AI Skills You Need NOW to Stay Ahead of 97% of People

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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.

Remember to subscribe to our channel for more valuable content and hit the notification bell so you never miss an update. Join the conversation in the comments section — we’d love to hear your thoughts on AI and how you plan to incorporate these skills into your career or studies.

So get ready, click play, and let’s take a step towards the future together, learning the 9 AI skills you need NOW to stay ahead of 97% of people. Your AI journey starts here.

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What Is an “Algorithm of Thoughts” (AoT)? Microsoft’s Human-like AI Training Method

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.

Quantum Computing May Help Protect AI From Attack

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.

What is the next wave after artificial intelligence｜The Singularity Is Near｜#audiobooks

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:

Moore’s Law has been around for 40 years; can it continue?
Why is it said that by 2045, humans will reach a technological Singularity?
Why are future humans described as a set of algorithms?
Is artistic creation the last bastion between humans and artificial intelligence?

BookLink：https://amzn.to/45akzPk.

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How Powerful Will AI Be In 2030?

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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.

To provide a comprehensive perspective, we draw insights from leading AI researchers, industry pioneers, and thought leaders who offer their expert opinions on the future trajectory of AI. Their invaluable insights help us paint a vivid picture of the exciting possibilities that await us in the next decade.

Join us on this thought-provoking journey into the future, as we ponder the ethical implications, challenges, and potential risks that arise with the growing power of AI. By understanding the trajectory of AI development, we can prepare ourselves for a future where humans and intelligent machines coexist harmoniously.

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What if AI becomes self-aware?

A glimpse into the dynamics between a man and a self-conscious machine.

Artificial Intelligence (AI) in a nutshell

Artificial intelligence (AI) and Cognitive robotics are the two stalwart fields of design and engineering, seizing all the spotlight lately. Artificial intelligence is a human intelligence simulation processed by machines, whereas cognitive robotics is the corollary of robotics and cognitive science that deals with cognitive phenomena like learning, reasoning, perception, anticipation, memory, and attention. Robotics is a part of AI, where the robots are programmed with artificial intelligence to perform the tasks, and AI is the program or algorithm that a robot employs to perform cognitive functions. In simpler terms, a robot is a machine, and AI is the intellect fuel fortified to ignite perceptual abilities in a machine.

IBM develops a new 64-core mixed-signal in-memory computing chip

For decades, electronics engineers have been trying to develop increasingly advanced devices that can perform complex computations faster and consuming less energy. This has become even more salient after the advent of artificial intelligence (AI) and deep learning algorithms, which typically have substantial requirements both in terms of data storage and computational load.

A promising approach for running these algorithms is known as analog in-memory computing (AIMC). As suggested by its name, this approach consists of developing electronics that can perform computations and store data on a . To realistically achieve both improvements in speed and energy consumption, this approach should ideally also support on-chip digital operations and communications.

Researchers at IBM Research Europe recently developed a new 64-core mixed-signal in-memory computing chip based on phase-change memory devices that could better support the computations of deep neural networks. Their 64-core chip, presented in a paper in Nature Electronics, has so far attained highly promising results, retaining the accuracy of deep learning algorithms, while reducing computation times and energy consumption.