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Alethea AI and BeingAI are collaborating with the Binance NFT marketplace to introduce the AI game characters that are based on nonfungible tokens (NFTs).

Alethea AI creates smart avatars who use AI to hold conversations with people, and it has launched its own NFT collectible AI characters. NFTs use the transparency and security of the digital ledger of blockchain to authenticate unique digital items. The companies see this as the underlying AI infrastructure for iNTFs, or intelligent nonfungible tokens, on the path to the metaverse, the universe of virtual worlds that are all interconnected, like in novels such as Snow Crash and Ready Player One.

Being AI, meanwhile, is on a quest to create AI characters who can interact and talk in real time with users. Both companies are working with the NFT marketplace of Binance to launch intelligent IGO (Initial Game Offering), featuring a hundred intelligent NFTs characters.

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A Canadian biotech firm is reporting positive results from a large study of its COVID-19 vaccine. What makes it unusual is that the key ingredient of the vaccine is grown in plants. Medicago has already developed an experimental flu vaccine in Nicotiana benthamian, a plant related to tobacco. When the pandemic struck, the company decided to try to make a COVID-19 vaccine.

Now it appears those efforts have succeeded. “This is an incredible moment for Medicago and for novel vaccine platforms,” Medicago CEO and President Takashi Nagao said in a statement.

A COVID-19 vaccine from a Canadian biotech firm has been found effective at preventing moderate to severe disease. It could soon become the first plant-based vaccine authorized for human use.

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The double-helix structure has practically become synonymous with DNA, but it isn’t the only way long strands of genetic information squeeze themselves into a tight space.

When a double-strand of DNA doubles back on itself or attaches to another double-strand, it can actually create a quadruple-stranded knot, known as a G-quadruplex.

Scientists first discovered these ‘double-double-helixes’ in living human cells in 2013, and in the years since, these knots have been found in high concentrations in cancerous cells.

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Warp drive pioneer Dr. Harold G “Sonny” White has reported the successful manifestation of an actual, real-world “Warp Bubble.”

Warp drive pioneer and former NASA warp drive specialist Dr. Harold G “Sonny” White has reported the successful manifestation of an actual, real-world “Warp Bubble.” And, according to White, this first of its kind breakthrough by his Limitless Space Institute (LSI) team sets a new starting point for those trying to manufacture a full-sized, warp-capable spacecraft.

“To be clear, our finding is not a warp bubble analog, it is a real, albeit humble and tiny, warp bubble,” White told The Debrief, quickly dispensing with the notion that this is anything other than the creation of an actual, real-world warp bubble. “Hence the significance.”

In 1994, Mexican Mathematician Miguel Alcubierre proposed the first mathematically valid solution to the warp drive. More specifically, he outlined a spacecraft propulsion system previously only envisioned in science fiction that can traverse the cosmos above the speed of light without violating currently accepted laws of physics.

Continue reading “DARPA Funded Researchers Accidentally Create The World’s First Warp Bubble” | >

Humans are pretty good at looking at a single two-dimensional image and understanding the full three-dimensional scene that it captures. Artificial intelligence agents are not.

Yet a machine that needs to interact with objects in the world—like a robot designed to harvest crops or assist with surgery—must be able to infer properties about a 3D from observations of the 2D images it’s trained on.

While scientists have had success using neural networks to infer representations of 3D scenes from images, these machine learning methods aren’t fast enough to make them feasible for many real-world applications.

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Games have a long history of serving as a benchmark for progress in artificial intelligence. Recently, approaches using search and learning have shown strong performance across a set of perfect information games, and approaches using game-theoretic reasoning and learning have shown strong performance for specific imperfect information poker variants. We introduce, a general-purpose algorithm that unifies previous approaches, combining guided search, self-play… See more.

Games have a long history of serving as a benchmark for progress in.

Artificial intelligence. Recently, approaches using search and learning have.

Shown strong performance across a set of perfect information games, and.

Continue reading “Player of Games” | >

The idiom “actions speak louder than words” first appeared in print almost 300 years ago. A new study echoes this view, arguing that combining self-supervised and offline reinforcement learning (RL) could lead to a new class of algorithms that understand the world through actions and enable scalable representation learning.

Machine learning (ML) systems have achieved outstanding performance in domains ranging from computer vision to speech recognition and natural language processing, yet still struggle to match the flexibility and generality of human reasoning. This has led ML researchers to search for the “missing ingredient” that might boost these systems’ ability to understand, reason and generalize.

In the paper Understanding the World Through Action, UC Berkeley assistant professor in the department of electrical engineering and computer sciences Sergey Levine suggests that a general, principled, and powerful framework for utilizing unlabelled data could be derived from RL to enable ML systems leveraging large datasets to better understand the real world.

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A huge asteroid the size of the Eiffel Tower is approaching our planet. The asteroid is named 4,660 Nereus and has been flagged ‘Potentially Hazardous’ by NASA. Nereus is 330 meters long and will break into Earth’s orbit on Saturday, December 11. The colossal asteroid is traveling at 23,700 km/h towards our planet.

On December 11, the asteroid will make its closest approach to Earth. It will come within 3.86 million km, about ten times the distance between Earth and the Moon. Although it sounds like an enormous gap on cosmic scales, it is actually a stone’s throw away.

How to watch comet Leonard: https://bit.ly/3xYv2Od

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To set some benchmarks for their simulator, the researchers tried out three different design algorithms working in conjunction with a deep reinforcement learning algorithm that learned to control the robots through many rounds of trial and error.

The co-designed bots performed well on the simpler tasks, like walking or carrying things, but struggled with tougher challenges, like catching and lifting, suggesting there’s plenty of scope for advances in co-design algorithms. Nonetheless, the AI-designed bots outperformed ones design by humans on almost every task.

Intriguingly, many of the co-design bots took on similar shapes to real animals. One evolved to resemble a galloping horse, while another, set the task of climbing up a chimney, evolved arms and legs and clambered up somewhat like a monkey.

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