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Category: robotics/AI – Page 1,313

Meta is developing a machine learning model that scans these citations and cross-references their content to Wikipedia articles to verify that not only the topics line up, but specific figures cited are accurate.

This isn’t just a matter of picking out numbers and making sure they match; Meta’s AI will need to “understand” the content of cited sources (though “understand” is a misnomer, as complexity theory researcher Melanie Mitchell would tell you, because AI is still in the “narrow” phase, meaning it’s a tool for highly sophisticated pattern recognition, while “understanding” is a word used for human cognition, which is still a very different thing).

Meta’s model will “understand” content not by comparing text strings and making sure they contain the same words, but by comparing mathematical representations of blocks of text, which it arrives at using natural language understanding (NLU) techniques.

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A new study in Science overthrew the whole gamebook. Led by Dr. David Baker at the University of Washington, a team tapped into an AI’s “imagination” to dream up a myriad of functional sites from scratch. It’s a machine mind’s “creativity” at its best—a deep learning algorithm that predicts the general area of a protein’s functional site, but then further sculpts the structure.

As a reality check, the team used the new software to generate drugs that battle cancer and design vaccines against common, if sometimes deadly, viruses. In one case, the digital mind came up with a solution that, when tested in isolated cells, was a perfect match for an existing antibody against a common virus. In other words, the algorithm “imagined” a hotspot from a viral protein, making it vulnerable as a target to design new treatments.

The algorithm is deep learning’s first foray into building proteins around their functions, opening a door to treatments that were previously unimaginable. But the software isn’t limited to natural protein hotspots. “The proteins we find in nature are amazing molecules, but designed proteins can do so much more,” said Baker in a press release. The algorithm is “doing things that none of us thought it would be capable of.”

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Well, now we have a robot version of this classic Serengeti scene.

The fawn in this case is a robotic dog at the University of California, Berkeley. And it’s likewise a surprisingly quick learner (relative to the rest of robot-kind). The robot is also special because, unlike other flashier robots you might have seen online, it uses artificial intelligence to teach itself how to walk.

Beginning on its back, legs waving, the robot learns to flip itself over, stand up, and walk in an hour. A further ten minutes of harassment with a roll of cardboard is enough to teach it how to withstand and recover from being pushed around by its handlers.

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Findings from a machine learning study suggest that some of the speech differences associated with autism are consistent across languages, while others are language-specific. The study, published in the journal PLOS One, was conducted among separate samples of English speakers and Cantonese speakers.

Autism spectrum disorder (ASD) is often accompanied by differences in speech prosody. Speech prosody describes aspects of speech, like rhythm and intonation, that help us express emotions and convey meaning with our words. Atypical speech prosody can interfere with a person’s communication and social abilities, for example, by causing a person to misunderstand others or be misunderstood themselves. The reason these speech differences commonly present among autistic people is not fully understood.

Study author Joseph C. Y. Lau and his team wanted to shed light on this topic by studying prosodic features associated with autism across two typologically distinct languages.

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This is just one of many military advancements the nation has made against its arch-rival.

Back in July, South Korea undertook a 33-minute flight of its homegrown KF-21 fighter jet for the first time flaunting its military might and perhaps sending a message to North Korea.

South Korea is pursuing stealth drones that could take out North Korean air defenses as part of a “manned-unmanned teaming system.”

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Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Watch here.

We’re in the midst of a data revolution. The volume of digital data created within the next five years will total twice the amount produced so far — and unstructured data will define this new era of digital experiences.

Unstructured data — information that doesn’t follow conventional models or fit into structured database formats — represents more than 80% of all new enterprise data. To prepare for this shift, companies are finding innovative ways to manage, analyze and maximize the use of data in everything from business analytics to artificial intelligence (AI). But decision-makers are also running into an age-old problem: How do you maintain and improve the quality of massive, unwieldy datasets?

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WEST LAFAYETTE, Ind. — When the human brain learns something new, it adapts. But when artificial intelligence learns something new, it tends to forget information it already learned.

As companies use more and more data to improve how AI recognizes images, learns languages and carries out other complex tasks, a paper published in Science this week shows a way that computer chips could dynamically rewire themselves to take in new data like the brain does, helping AI to keep learning over time.

“The brains of living beings can continuously learn throughout their lifespan. We have now created an artificial platform for machines to learn throughout their lifespan,” said Shriram Ramanathan, a professor in Purdue University’s School of Materials Engineering who specializes in discovering how materials could mimic the brain to improve computing.

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It’s rare that Western disinformation efforts are discovered and exposed. This week, the Stanford Internet Observatory and social media analysis firm Graphika detailed a five-year operation that was pushing pro-Western narratives. The research follows Twitter, Facebook, and Instagram as they remove a series of accounts from their platforms for “coordinated inauthentic behavior.” The propaganda accounts used memes, fake news websites, online petitions, and various hashtags in an attempt to push pro-Western views and were linked to both overt and covert influence operations. The accounts, some of which appear to use AI-generated profile pictures, targeted internet users in Russia, China, and Iran, among other countries. The researchers say the accounts “heavily criticized” Russia following its nvasion of Ukraine in February and also “promoted anti-extremism messaging.” Twitter said the activity it saw is likely to have originated in the US and the UK, while Meta said it was the US.

#WesternPropaganda

Plus: An Iranian hacking tool steals inboxes, LastPass gets hacked, and a deepfake scammer targets the crypto world.

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A sci fi documentary looking at a timelapse of future spacecraft. From the future of AI spaceships, Starship orbital refuelling, and space station worlds, to Mars colonization and in-space manufacturing.

Other topics include: SpaceX and the launch of their fleet of Starships — waiting in parking orbit around Earth, ready for the launch window to open to Mars. NASA and the mission of landing on the Martian Moon Phobos. Advances in spacecraft technology for protecting humans during multi-year interstellar journeys.

While the year 2100 and beyond, brings wormhole exploration, artificial intelligence based planets, and the possible need for a stellar engine — to protect the solar system.

Main narration by: Alexander Masters (www.alexander-masters.com)

Starship Artwork – used with permission and licensed from:
Erc X: https://twitter.com/ErcXspace.
Caspar Stanley: https://twitter.com/Caspar_Stanley.
Alex Svan: https://twitter.com/AlexSvanArt.

Additional footage sourced from: SpaceX, NASA, ESO, Ken Crawford, Nick Risinger, Northrop Grumman, SpinLaunch, Redwire Space.

Continue reading “TIMELAPSE OF FUTURE SPACECRAFT: 2025 — 3000+” | >

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Watch here.

There hasn’t been a revolution quite like this before, one that’s shaken the talent industry so dramatically over the past few years. The pandemic, the Great Resignation, inflation and now talk of looming recessions are changing talent strategies as we know them.

Such significant changes, and the challenge of staying ahead of them, have brought artificial intelligence (AI) to the forefront of the minds of HR leaders and recruitment teams as they endeavor to streamline workflows and identify suitable talent to fill vacant positions faster. Yet many organizations are still implementing AI tools without proper evaluation of the technology or indeed understanding how it works — so they can’t be confident they are using it responsibly.

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