I will be on tour of North America, UK & EU talking about my latest book, religion, life on earth and beyond. I will be joined on stage by a range of friends…
Category: robotics/AI – Page 344
Patreon: https://bit.ly/3v8OhY7Sean Carroll is Homewood Professor of Natural Philosophy at Johns Hopkins University and fractal faculty at the Santa Fe Insti…
Want to join the debate? Check out the Intelligence Squared website to hear about future live events and podcasts: http://www.intelligencesquared.com.
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How come there are conscious minds?
How do language and culture evolve?
Should we still teach children things which computers can do better?
Will our smart electronic devices rob us of our intelligence?
Will human intelligence and AI co-evolve?
These are some of the intriguing questions that Daniel Dennett, one of the most influential and provocative thinkers of modern times, sought to answer when he came to the Intelligence Squared stage to discuss his lifetime’s work on the evolution of the human mind. Dennett’s cross-disciplinary approach – encompassing neuroscience, evolutionary biology and artificial intelligence – has been widely acclaimed and helped redefine the role of the philosopher for our age.
In this exclusive event, Dennett explored the major themes of his forthcoming book, ‘From Bacteria to Bach and Back’, including how our minds came into existence, how our brains work, and how ideas are culturally transmitted. He exploded many of the notions we take for granted about how we think – such as the idea of the individual – offering instead a bold new explanation of human consciousness which views it largely as a product of cultural evolution built up over millennia.
Sharing the stage with Dennett were key figures from the next generation of scientists, AI experts, philosophers and artists, with whom he will engage on what it means to be human.
An international collaborative research team has developed an image recognition technology that can accurately determine the elemental composition and the number of charge and discharge cycles of a battery by examining only its surface morphology using AI learning.
Professor Seungbum Hong from the Korea Advanced Institute of Science and Technology (KAIST) Department of Materials Science and Engineering, in collaboration with the Electronics and Telecommunications Research Institute (ETRI) and Drexel University in the United States, has developed a method to predict the major elemental composition and charge-discharge state of NCM cathode materials with 99.6% accuracy using convolutional neural networks (CNN).
The paper is published in the journal npj Computational Materials.
Living brain cells wired into organoid-on-a-chip biocomputers can now learn to drive robots, thanks to an open-source intelligent interaction system called MetaBOC. This remarkable project aims to re-home human brain cells in artificial bodies.
Most of our progress in disease treatment and prevention to date has been the product of the linear process of hit-or-miss efforts to find useful interventions. Because we have lacked tools for systematically exploring all possible treatments, discoveries under this paradigm have owed a lot to chance. Likely the most notable chance breakthrough in medicine was the accidental discovery of penicillin — which opened up the antibiotic revolution and has since saved perhaps as many as 200 million lives. But even when discoveries aren’t literally accidental, it still takes good fortune for researchers to achieve breakthroughs with traditional methods. Without the ability to exhaustively simulate possible drug molecules, researchers have to rely on high-throughput screening and other painstaking laboratory methods, which are much slower and more inefficient.
To be fair, this approach has brought great benefits. A thousand years ago, European life expectancy at birth was just in the twenties, since so many people died in infancy or youth from diseases like cholera and dysentery, which are now easily preventable. By the middle of the nineteenth century, life expectancy in the United Kingdom and the United States had increased to the forties. As of 2023, it has risen to over eighty in much of the developed world. So, we have nearly tripled life expectancy in the past thousand years and doubled it in the past two centuries. This was largely achieved by developing ways to avoid or kill external pathogens — bacteria and viruses that bring disease from outside our bodies.
Today, though, most of this low-hanging fruit has been picked. The remaining sources of disease and disability spring mostly from deep within our own bodies. As cells malfunction and tissues break down, we get conditions like cancer, atherosclerosis, diabetes, and Alzheimer’s. To an extent we can reduce these risks through lifestyle, diet, and supplementation — what I call the first bridge to radical life extension. But those can only delay the inevitable. This is why life expectancy gains in developed countries have slowed since roughly the middle of the twentieth century. For example, from 1,880 to 1900, life expectancy at birth in the United States increased from about thirty-nine to forty-nine, but from 1980 to 2000 — after the focus of medicine had shifted from infectious disease to chronic and degenerative disease — it only increased from seventy-four to seventy-six.
With the pending arrival of AI agents, we will even more effectively join the always-on interconnected world, both for personal use and for work. In this way, we will increasingly dialog and interact with digital intelligence everywhere.
The path to AGI and superintelligence remains shrouded in uncertainty, with experts divided on its feasibility and timeline. However, the rapid evolution of AI technologies is undeniable, promising transformative advancements. As businesses and individuals navigate this rapidly changing landscape, the potential for AI-driven innovation and improvement remains vast. The journey ahead is as exciting as it is unpredictable, with the boundaries between human and artificial intelligence continuing to blur.
By mapping out proactive steps now to invest and engage in AI, upskill our workforce and attend to ethical considerations, businesses and individuals can position themselves to thrive in the AI-driven future.
In the 1800s, a conflict between the founding fathers of evolution divided the community. Charles Darwin believed sexual selection drove the variation in butterfly colors and patterns of males, while contemporary rival Alfred Russel Wallace disagreed, predicting that broader natural selection played as important a role.
Darwin was adamant that sexual selection was not part of natural selection but solely related to differences in mating success. Natural selection covers a broader range of factors that contribute to an individual’s overall ‘fitness.’
In 2,024,150 years or so after these two iconic British evolutionary scientists began their heated rivalry over who was right, researchers have employed machine learning to settle the score. Scientists from the University of Essex, in collaboration with the Natural History Museum and AI research institute Cross Labs, Cross Compass, have used AI to analyze “sexual and interspecific variation” found across 16,734 dorsal and ventral images of birdwing butterflies.
Walmart showed off its use of augmented reality and artificial intelligence in its retail operations. It turns out that AR is leading to better digital sales and cool new applications that haven’t been done before.
The techniques include virtual try-on of outfits, virtual showroom experiences and digital twins, said Desirée Gosby, vice president of emerging technology at Walmart Global Tech, in an interview with VentureBeat.
She emphasized the importance of AR and related technologies for enhancing customer experiences and improve productivity.