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Category: robotics/AI – Page 1,070

How long until AI can replace a singer? It’s already happening

Can AI capture the emotion that a singer today can convey, or dupe us into believing they’re not human? Can Ronnie James Dio’s voice be brought back from the dead? In this episode of The Singing Hole, we explore where AI’s technology is today, how creators are harnessing the technology and how we can better prepare for the eventual future with music.

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Discovery in nanomachines within living organisms — cytochromes P450 (CYP450s) unleashed as living soft robots

Study reveals an important discovery in the realm of nanomachines within living systems. Prof. Sason Shaik from the Hebrew University of Jerusalem and Dr. Kshatresh Dutta Dubey from Shiv Nadar University, conducted molecular-dynamics simulations of Cytochromes P450 (CYP450s) enzymes, revealing that these enzymes exhibit unique soft-robotic properties.

Cytochromes P450 (CYP450s) are enzymes found in living organisms and play a crucial role in various biological processes, particularly in the metabolism of drugs and xenobiotics. The researchers’ simulations demonstrated that CYP450s possess a fourth dimension — the ability to sense and respond to stimuli, making them soft-robot nanomachines in “living matters.”

In the catalytic cycle of these enzymes, a molecule called a substrate binds to the enzyme. This leads to a process called oxidation. The enzyme’s structure has a confined space that allows it to act like as a sensor and a soft robot. It interacts with the substrate using weak interactions, like soft impacts. These interactions transfer energy, causing parts of the enzyme and the molecules inside it to move. This movement generates ultimately a special substance called oxoiron species, which serves the enzyme to oxidize a variety of different substances.

This German Unicorn Is Trying To Take On Google Translate And ChatGPT

AI-based translation software, DeepL, is making its first appearance on the Forbes Cloud 100 list this year thanks to a machine learning translation model that users say is more precise than Google’s.

Jaroslaw Kutylowski speaks German, Polish and English (and he can order a Coke in French). With DeepL, his startup’s AI-powered translation tool, he can read and write in about 30 more.

Founded in 2017, DeepL has developed translation software that it says is far more accurate than rival products offered by Google and others, thanks to some powerful artificial intelligence working in concert with human native language speakers.

Is Generative AI Stealing From Artists?

When an artist – whether they are a painter, writer, photographer, poet, etc. – creates a piece of work, they automatically own the copyright to it. This means they get to choose how that work of art can be used and, of course, get paid for it. But what happens when a piece of art is created by a computer?

This is a problem that we’ve only had to deal with in the last year – since Generative AI took the world by storm. Tools like ChatGPT can write stories, songs or plays, while Stable Diffusion or DALL-E 2 can produce images of anything we can describe to them.

But should the credit (and royalties) go to the person who used the tool to create the art or to the company that built the AI tool?… More.

Delve into the contentious debate around ownership, credit, and financial compensation for art created by AI tools, exploring artists’ rights and IP laws.

Mathematical theory predicts self-organized learning in real neurons

An international collaboration between researchers at the RIKEN Center for Brain Science (CBS) in Japan, the University of Tokyo, and University College London has demonstrated that self-organization of neurons as they learn follows a mathematical theory called the free energy principle.

The principle accurately predicted how real neural networks spontaneously reorganize to distinguish incoming information, as well as how altering neural excitability can disrupt the process. The findings thus have implications for building animal-like artificial intelligences and for understanding cases of impaired learning. The study was published August 7 in Nature Communications.

When we learn to tell the difference between voices, faces, or smells, networks of neurons in our brains automatically organize themselves so that they can distinguish between the different sources of incoming information. This process involves changing the strength of connections between neurons, and is the basis of all learning in the .

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