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Category: robotics/AI – Page 1,317

Aging is driven by unbalanced genes

Northwestern University researchers have discovered a previously unknown mechanism that drives aging.

In a new study, researchers used artificial intelligence to analyze data from a wide variety of tissues, collected from humans, mice, rats and killifish. They discovered that the length of genes can explain most molecular-level changes that occur during aging.

All cells must balance the activity of long and short genes. The researchers found that longer genes are linked to longer lifespans, and shorter genes are linked to shorter lifespans. They also found that aging genes change their activity according to length. More specifically, aging is accompanied by a shift in activity toward short genes. This causes the gene activity in cells to become unbalanced.

Thanks to AI, it’s probably time to take your photos off the Internet

If you’re one of the billions of people who have posted pictures of themselves on social media over the past decade, it may be time to rethink that behavior. New AI image-generation technology allows anyone to save a handful of photos (or video frames) of you, then train AI to create realistic fake photos that show you doing embarrassing or illegal things. Not everyone may be at risk, but everyone should know about it.

Photographs have always been subject to falsifications—first in darkrooms with scissors and paste and then via Adobe Photoshop through pixels. But it took a great deal of skill to pull off convincingly. Today, creating convincing photorealistic fakes has become almost trivial.

Once an AI model learns how to render someone, their image becomes a software plaything. The AI can create images of them in infinite quantities. And the AI model can be shared, allowing other people to create images of that person as well.

AI, Robots & the Future

Robots and AI are already real products and services. But will they take our jobs? Or even take over? In this video I discuss these questions in a pragmatic fashion, as well as how we may usefully define “artificial intelligence”. Also covered are cloud AI services, and the role AI in digital transformation.

REFERENCES & OTHER LINKS:

Alan Turing’s 1950 paper in “Mind” on ‘Computing Machinery and Intelligence’:
https://www.csee.umbc.edu/courses/471/papers/turing.pdf.

IBM Watson (cloud AI):
https://www.ibm.com/watson.

Google AI & Machine Learning Products:
https://cloud.google.com/products/ai.

Microsoft Azure Cognitive Services: https://azure.microsoft.com/en-gb/services/cognitive-services/

Continue reading “AI, Robots & the Future” | >

ChatGPT Is A Huge Fan Of Elon Musk, Donald Trump And AI, But Not Google, Amazon And Apple

Silicon Valley has been obsessed with ChatGPT since it launched on Nov. 30. The clever chatbot, created by Elon Musk-founded startup OpenAI, has racked up more than a million users in its first five days and is likely to report strong engagement as people dive deeper into the charms of its impressive AI.

You can chat with it for free at chat.openai.com and ask it anything it deems appropriate. It doesn’t have access to the internet and can only respond based on the data set it was trained on, but its answers can be quite imaginative.

The Tesla and SpaceX founder is always the hero in this chatbot sensation’s stories.

The Jaw-Dropping New Plan To Send A Robot On A 1,000 Years Journey To An Alien Planet

Finding alien planets orbiting other stars is easy. Astronomers have found over 6,000 of them in just the last decade, but very few are considered even possibly habitable. Scientists have dozens of telescopes on the ground and in space that can find them and now even study their atmospheres for signs of life. Most are around small, dim red dwarf stars simply because current technology makes it difficult to study objects around bright Sun-like stars.

The next great objective in planetary science? Send a spacecraft to explore the surface of one of them, of course.

If we want to find Earth 2.0 we’re going to have to play the long game and visit star systems most like our own, says a white paper proposing a multi-century mission.

A new discovery in genes could help researchers understand longevity

Researchers used AI to analyze genes and discovered that aging is caused by unbalanced genes.

Researchers have discovered a breakthrough in what causes people to age. The research team, from Northwestern University in Evanston, Illinois, found a previously unknown factor that leads to aging.

The research team used AI to analyze tissue samples.

Tylim/iStock.

The team discovered that the length of genes can account for most molecular-level changes that happen as animals get older. The study used artificial intelligence to assess data from various tissue that was collected from humans, rodents, and fish.

Is ChatGPT a ‘virus that has been released into the wild’?

More than three years ago, this editor sat down with Sam Altman for a small event in San Francisco soon after he’d left his role as the president of Y Combinator to become CEO of the AI company he co-founded in 2015 with Elon Musk and others, OpenAI.

At the time, Altman described OpenAI’s potential in language that sounded outlandish to some. Altman said, for example, that the opportunity with artificial general intelligence — machine intelligence that can solve problems as well as a human — is so great that if OpenAI managed to crack it, the outfit could “maybe capture the light cone of all future value in the universe.” He said that the company was “going to have to not release research” because it was so powerful. Asked if OpenAI was guilty of fear-mongering — Musk has repeatedly called all organizations developing AI to be regulated — Altman talked about the dangers of not thinking about “societal consequences” when “you’re building something on an exponential curve.”

The audience laughed at various points of the conversation, not certain how seriously to take Altman. No one is laughing now, however. While machines are not yet as intelligent as people, the tech that OpenAI has since released is taking many aback (including Musk), with some critics fearful that it could be our undoing, especially with more sophisticated tech reportedly coming soon.

OpenAI’s attempts to watermark AI text hit limits

It’s proving tough to reign in systems like ChatGPT

Did a human.

Did a human write that, or ChatGPT? It can be hard to tell — perhaps too hard, its creator OpenAI thinks, which is why it is working on a way to “watermark” AI-generated content.

In a lecture at the University of Austin, computer science professor Scott Aaronson, currently a guest researcher at OpenAI, revealed that OpenAI is developing a tool for “statistically watermarking the outputs of a text [AI system].” Whenever a system — say, ChatGPT — generates text, the tool would embed an “unnoticeable secret signal” indicating where the text came from.

OpenAI engineer Hendrik Kirchner built a working prototype, Aaronson says, and the hope is to build it into future OpenAI-developed systems.

Evolutionary computation: Keith Downing at TEDxTrondheim

Keith Downing is a professor of Computer Science at the Norwegian University of Science and Technology, specializing in Artificial Intelligence and Artificial Life. He has a particular interest in evolutionary algorithms, which have applications ranging from the development of the Mars Rover antenna, patented circuits, early driverless cars, to even art. For computer scientists to learn from nature, he believes there needs to be a shift in our traditional ways thinking.

About TEDx, x = independently organized event.
In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations).

Neural networks will help manufacture carbon nanotubes

Thin films made of carbon nanotubes hold a lot of promise for advanced optoelectronics, energy and medicine, however with their manufacturing process subject to close supervision and stringent standardization requirements, they are unlikely to become ubiquitous anytime soon.

“A major hindrance to unlocking the vast potential of nanotubes is their multiphase which is extremely difficult to manage. We have suggested using (ANN) to analyze and predict the efficiency of single-walled carbon nanotubes synthesis,” explains one of the authors of the study and Skoltech researcher, Dmitry Krasnikov.

In their work published in the prestigious Carbon journal, the authors show that machine learning methods, and, in particular, ANN trained on experimental parameters, such as temperature, gas pressure and , can help monitor the properties of the carbon nanotube films produced.