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Category: robotics/AI – Page 1500

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A company called Tombot thinks it’s come up with a way to improve the quality of life for seniors facing challenges when it comes to being social: a robotic companion dog that behaves and responds like a real pup, but without all the responsibilities of maintaining a living, breathing animal. The company even enlisted the talented folks at the Jim Henson’s Creature Shop to help make the robo-dog look as lifelike as possible. It’s a noble effort, but it also raises lots of questions.

For starters, can robots actually be a good substitute for an animal companion? Replacing people with robots is a massive technological challenge—and one we’re not even close to accomplishing. Every time a multi-million dollar humanoid robot like Boston Dynamics’ ATLAS takes a nasty spill, we’re reminded that they’re nowhere near ready to interact with the average consumer. But robotic animals are a different story. It’s hard not to draw comparisons to a well-trained dog when seeing Boston Dynamics’ SpotMini in action. And even though it still comes with a price tag that soars to hundreds of thousands of dollars, there are robotic pets available on the other end of the affordability spectrum.

Continue reading “Shockingly Realistic AI Robot Dog “Jennie”” | >

I think SENS did this last year but now AlphaFold2 will make it easier and faster.

Hey it’s Han from WrySci HX discussing how breakthroughs in the protein folding problem by AlphaFold 2 from DeepMind could combine with the SENS research foundation’s approach of allotopic mitochondrial gene expression to fight aging damage. More below ↓↓↓

Subscribe! =]

Continue reading “A Specific Example of How AlphaFold 2 From DeepMind Could Help Us Achieve Immortality” | >

It’s no secret that AI is everywhere, yet it’s not always clear when we’re interacting with it, let alone which specific techniques are at play. But one subset is easy to recognize: If the experience is intelligent and involves photos or videos, or is visual in any way, computer vision is likely working behind the scenes.

Computer vision is a subfield of AI, specifically of machine learning. If AI allows machines to “think,” then computer vision is what allows them to “see.” More technically, it enables machines to recognize, make sense of, and respond to visual information like photos, videos, and other visual inputs.

Over the last few years, computer vision has become a major driver of AI. The technique is used widely in industries like manufacturing, ecommerce, agriculture, automotive, and medicine, to name a few. It powers everything from interactive Snapchat lenses to sports broadcasts, AR-powered shopping, medical analysis, and autonomous driving capabilities. And by 2,022 the global market for the subfield is projected to reach $48.6 billion annually, up from just $6.6 billion in 2015.

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I would say this is probably aimed at a few things. It’s a work around to the national fight to raise the minimum wage. These will be out of sight out of mind, so no one, besides the workers, will see as they are gradually automated to 100% by around 2027. And, the delivery is gradually fully automated with long distance drones and self driving vehicles. Also, be sure every other chain is working on the same stuff.

The ‘ghost kitchens’ are coming to the UK, US and Canada.

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A radical collaboration between a biologist and an engineer is supercharging efforts to protect grape crops. The technology they’ve developed, using robotics and AI to identify grape plants infected with a devastating fungus, will soon be available to researchers nationwide working on a wide array of plant and animal research.

The biologist, Lance Cadle-Davidson, Ph.D. ‘03, an adjunct professor in the School of Integrative Plant Science (SIPS), is working to develop that are more resistant to powdery mildew, but his lab’s research was bottlenecked by the need to manually assess thousands of grape leaf samples for evidence of infection.

Powdery mildew, a fungus that attacks many plants including wine and table grapes, leaves sickly white spores across leaves and fruit and costs grape growers worldwide billions of dollars annually in lost fruit and fungicide costs.

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For many years now, China has been the world’s factory. Even in 2,020 as other economies struggled with the effects of the pandemic, China’s manufacturing output was $3.854 trillion, up from the previous year, accounting for nearly a third of the global market.

But if you are still thinking of China’s factories as sweatshops, it’s probably time to change your perception. The Chinese economic recovery from its short-lived pandemic blip has been boosted by its world-beating adoption of artificial intelligence (AI). After overtaking the U.S. in 2,014 China now has a significant lead over the rest of the world in AI patent applications. In academia, China recently surpassed the U.S. in the number of both AI research publications and journal citations. Commercial applications are flourishing: a new wave of automation and AI infusion is crashing across a swath of sectors, combining software, hardware and robotics.

As a society, we have experienced three distinct industrial revolutions: steam power, electricity and information technology. I believe AI is the engine fueling the fourth industrial revolution globally, digitizing and automating everywhere. China is at the forefront in manifesting this unprecedented change.

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We’ve seen a lot of electric vehicle growth and success stories in the past several years, but one area that’s been a bit of a letdown has been the semi truck market. Unfortunately, we still don’t have the Tesla Semi, and it was recently delayed until 2,022 and a big side area of that market that “futurists” have long been excited about is potential self-driving trucks. Platoons of self-driving semi trucks are especially exciting since tight, train-like caravans of semi trucks would use far less energy than the current system, and those trucks could much more easily be cost-competitive electric trucks with zero tailpipe emissions. Anyway, though, we’re getting ahead of ourselves again.

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Doubtful. But, i hope so, it will convince them to spend more money here to move AI research faster.

TOKYO — China is overtaking the U.S. in artificial intelligence research, setting off alarm bells on the other side of the Pacific as the world’s two largest economies jockey for AI supremacy.

In 2,020 China topped the U.S. for the first time in terms of the number of times an academic article on AI is cited by others, a measure of the quality of a study. Until recently, the U.S. had been far ahead of other countries in AI research.

One reason China is coming on strong in AI is the ample data it generates. By 2,030 an estimated 8 billion devices in China will be connected via the Internet of Things — a vast network of physical objects linked via the internet. These devices, mounted on cars, infrastructure, robots and other instruments, generate a huge amount of data.

Continue reading “China overtakes US in AI research” | >

In other words, the mix of positives and negatives puts this potent new suite of technologies on a knife-edge. Do we have confidence that a handful of companies that have already lost public trust can take AI in the right direction? We should have ample reason for worry considering the business models driving their motivations. To advertising-driven companies like Google and Facebook, it’s clearly beneficial to elevate content that travels faster and draws more attention—and misinformation usually does —while micro-targeting that content by harvesting user data. Consumer product companies, such as Apple, will be motivated to prioritize AI applications that help differentiate and sell their most profitable products—hardly a way to maximize the beneficial impact of AI.

Yet another challenge is the prioritization of innovation resources. The shift online during the pandemic has led to outsized profits for these companies, and concentrated even more power in their hands. They can be expected to try to maintain that momentum by prioritizing those AI investments that are most aligned with their narrow commercial objectives while ignoring the myriad other possibilities. In addition, Big Tech operates in markets with economies of scale, so there is a tendency towards big bets that can waste tremendous resources. Who remembers IBM’s Watson initiative? It aspired to become the universal, go-to digital decision tool, especially in healthcare—and failed to live up to the hype, as did the trendy driverless car initiatives of Amazon and Google parent Alphabet. While failures, false starts, and pivots are a natural part of innovation, expensive big failures driven by a few enormously wealthy companies divert resources away from more diversified investments across a range of socially productive applications.

Despite AI’s growing importance, U.S. policy on how to manage the technology is fragmented and lacks a unified vision. It also appears to be an afterthought, with lawmakers more focused on Big Tech’s anti-competitive behavior in its main markets—from search to social media to app stores. This is a missed opportunity, because AI has the potential for much deeper societal impacts than search, social media, and apps.

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Tesla has started updating its Autopark feature with its new Tesla Vision computer vision system, which now powers Autopilot and its Full Self-Driving Beta.

Like many other premium (and even non-premium) vehicles, Tesla vehicles have been equipped with an autonomous parking feature called ‘ Autopark.

Tesla’s Autopark has been relying on ultrasonic sensors around the vehicles.

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