The weird and wonderful art created when AI and humans unite BBC Will AI kill art? Not likely, says the artist Alexander Reben, who has been working with AI for years. "I knew I had hit upon the right recipe when I got the following output by GPT-3 (which made me laugh a little too hard alone in my studio in lockdown):" "The sculpture contains a plunger, a toilet plunger, a plunger, a plunger, a plunger, and a plunger, each of which has been modified. The first plunger is simply a normal plunger, but the rest represent a series of plungers with more and more of the handle removed until just the rubber cup is left. The title of the artwork is "A Short History of Plungers and Other Things That Go Plunge in the Night" by the artists known as "The Plungers" (whose identity remains unknown). "The Plungers", were a collective of anonymous artists, founded in 1972. They were dedicated to the "conceptualization and promotion of a new art form called Plungism." Plungism was a creative interpretation of the idea of Plungerism, which was defined by The Plungers as "a state of mind wherein the mind of an artist is in a state of flux and able to be influenced by all things, even plungers." The Plungers' works were displayed in New York galleries and included such titles as "Plunger's Progress," "The Plungers," "The Plungers Strike Back," and "Big Plunger 4: The Final Plunger," all of which featured plungers, and "Plungers on Parade," which showed images of plungers in public spaces. The Plungers disappeared and left no trace of their identity."

Do not keep calm and carry on, girls!'' Do we really care more about Van Gogh's sunflowers than real ones? Gedorfge Monbiot The Guardian The response by the media and government to the two Just Stop Oil activists who threw soup at Vincent van Gogh's Sunflowers in the National Gallery in London speaks volumes. Decorating the glass protecting the painting with tomato soup (the painting itself was, as the protesters calculated, undamaged) appears to horrify some people more than the collapse of our planet, which these campaigners are seeking to prevent. Everywhere I see claims that the "extreme" tactics of environmental campaigners will prompt people to "stop listening". But how could we listen any less to the warnings of scientists and campaigners and eminent committees?

And some, like Nate, had more modest goals: automatically filling out shoppers' contact and payment information on retailers' websites. In exchange for sparing them a minute or two of data entry on their phones, Nate charged shoppers $1 per transaction. But it struggled to turn even that vision into reality. While the company said it was using artificial intelligence to populate customer information during the checkout process, it had actually hired workers in the Philippines to manually enter the data on retailers' sites for a significant portion of the transactions Nate facilitated in 2021, according to two people with direct knowledge of the company's practices. Go read this report on an AI shopping app that was actually just using humans The Verge Instead of using high-tech methods to complete purchases, Nate transactions were often handled manually by workers in the Philippines, according to a deep dive by The Information. Speaking to two people with direct access to Nate's internal data, The Information reports that "the share of transactions Nate handled manually rather than automatically ranged between 60 percent and 100 percent" throughout 2021.

Quantum Wittgenstein Timothy Andersen AEON In his Philosophical Investigations, Wittgenstein rejects the theory of meaning entirely while making one of his most powerful contributions to it. All language, he says, gains its definitions from how it is used in specific cases. All language is a game like chess or poker – we learn the rules by playing, not theorising or defining. So the very notion of a universal definition is an artifice, a bit of subterfuge. One cannot talk about what words really mean; one can only use them.

DeepMind: Why is AI so good at language? It's something in language itself ZDNet How is it that a program such as OpenAI's GPT-3 neural network can answer multiple choice questions, or write a poem in a particular style, despite never being programmed for those specific tasks? It may be because the human language has statistical properties that lead a neural network to expect the unexpected, according to new research by DeepMind, the AI unit of Google. Natural language, when viewed from the point of view of statistics, has qualities that are "non-uniform," such as words that can stand for multiple things, known as "polysemy," like the word "bank," meaning a place where you put money or a rising mound of earth. And words that sound the same can stand for different things, known as homonyms, like "here" and "hear." Those qualities of language are the focus of a paper posted on arXiv this month, "Data Distributional Properties Drive Emergent Few-Shot Learning in Transformers," by DeepMind scientists.

Impressive results were achieved in activities as diverse as autonomous driving, game playing, molecular recombination, and robotics. In all these fields, computer programs have taught themselves to solve difficult problems. They have learned to fly model helicopters and perform aerobatic manoeuvers such as loops and rolls. In some applications they have even become better than the best humans, such as in Atari, Go, poker and StarCraft. The way in which deep reinforcement learning explores complex environments reminds us of how children learn, by playfully trying out things, getting feedback, and trying again.

'Ik snap nog steeds niet waarom kunstmatige neurale netwerken zo verbazingwekkend succesvol zijn.' Techgoeroe Chriet Kopjes: 'In dat geval beveel ik je...

From 2012 to 2018, for instance, the computational cost of advanced AI applications that use deep-learning models increased by 300,000 times, causing a significant rise in electric power consumption and resource utilization. The emerging green AI, or environmentally friendly AI, on the other hand, addresses the issue by minimizing ML's computational demand and reducing its carbon footprint.

Deep Learning isn't deep enough unless it copies from the brain interview with Jeff Hawkins, author of'A Thousand Brains: A New Theory of Intelligence' IEEE Spectrum Could an AI really understand why humans do the things they do if it doesn't understand the fear of death? Hawkins: "I've had cats, and I don't think my cats really understood my emotional states. And I didn't really understand theirs. But we still got along quite well."

Iedereen weet toch dat we parasieten zijn op een hele grote ui?';) New research indicates the whole universe could be a giant neural network TNW (...) If we're all nodes in a neural network, what's the network's purpose? Is the universe one giant, closed network or is it a single layer in a grander network? Or perhaps we're just one of trillions of other universes connected to the same network. When we train our neural networks we run thousands or millions of cycles until the AI is properly "trained." Are we just one of an innumerable number of training cycles for some larger-than-universal machine's greater purpose?