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3D printing: Invisible tags turn simple objects into gaming controllers

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Adding invisible tags to 3D printed objects could link the objects to information or turn them into controllers for gaming



Technology



11 May 2022

An invisible tag embedded in a coffee cup

An invisible tag embedded in a coffee cup

Mustafa Dogan

A 3D printing technique can incorporate invisible tags into objects. The process could be used to keep the convenience of QR codes without making them visible, as well as to turn simple objects into videogame controllers.

Tags, such as QR codes, can be used to easily reveal information from an object when scanned. The information could be anything from a restaurant’s menu to details about the object that would help a robot in a warehouse work out what to do with it. …



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Is DeepMind’s Gato AI really a human-level intelligence breakthrough?

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Gato

DeepMind’s Gato may or may not be a major breakthrough for AI

DeepMind

DeepMind has released what it calls a “generalist” AI called Gato, which can play Atari games, accurately caption images, chat naturally with a human and stack coloured blocks with a robot arm, among 600 other tasks. But is Gato truly intelligent having artificial general intelligence or is it just an AI model with a few extra tricks up its sleeve?

What is artificial general intelligence (AGI)?

Outside science fiction, AI is limited to niche tasks. It has seen plenty of success recently in solving a huge range of problems, from writing software to protein folding and even creating beer recipes, but individual AI models have limited, specific abilities. A model trained for one task is of little use for another.

AGI is a term used for a model that can learn any intellectual task that a human being can. Gary Marcus at US software firm Robust.AI says the term is shorthand. “It’s not a single magical thing,” he says. “But roughly, we mean systems that can flexibly, resourcefully solve problems that they haven’t seen before, and do so in a reliable way.”

How will we know if AGI has been achieved?

Various tests have been proposed that would grant an AI the status of AGI, although there is no universally accepted definition. Alan Turing famously suggested that an AI should have to pass as human in a text conversation, while Steve Wozniak, co-founder of Apple, has said he will consider AGI to be real if it can enter a random house and figure out how to make a cup of coffee. Other proposed tests are sending an AI to university and seeing if it can pass a degree, or testing whether it can carry out real-world jobs successfully.

Does AGI exist yet?

Yann LeCun, chief AI scientist at Facebook’s owner Meta, says there is no such thing because even humans are specialised. In a recent blog post, he said that a “human level AI” may be a useful goal to aim for, where AI can learn jobs as needed like a human would, but that we aren’t there yet. “We still don’t have a learning paradigm that allows machines to learn how the world works, like human and many non-human babies do,” he wrote. “The solution is not just around the corner. We have a number of obstacles to clear, and we don’t know how.”

One of the driving forces behind the current success of AI research is scale; more and more computer power is being used to train ever-larger models on increasingly large sets of data. The discovery that simple scaling-up provides such power is surprising, and we are yet to see any signs that more power, more data and larger models won’t keep providing more capable AI. But many researchers are sceptical that it will lead to a conscious, or even general AI.

Is Gato an AGI?

Nando de Freitas at DeepMind tweeted that “the game is over” when Gato was released, and suggested that achieving AGI was now simply a matter of making AI models bigger and more efficient, and feeding more training data in. But others aren’t so sure.

Marcus says Gato was trained to do each and every one of the tasks it can do, and that faced with a new challenge it wouldn’t be able to logically analyse and solve that problem. “These are like parlour tricks,” he says. “They’re cute, they’re magician’s tricks. They’re able to fool unsophisticated humans who aren’t trained to understand these things. But that doesn’t mean that they’re actually anywhere near [AGI].”

Oliver Lemon at Heriot-Watt University in Edinburgh, UK, says the claim that the “game is over” isn’t accurate, and that Gato is not AGI. “These models do really impressive things,” he says. “However, a lot of the really cool examples you see are cherry-picked; they get exactly the right input to lead to impressive output.”

So what has Gato achieved?

Even DeepMind’s own scientists are sceptical of the claims being made by some about Gato. David Pfau, a staff research scientist at DeepMind, tweeted: “I genuinely don’t understand why people seem so excited by the Gato paper. They took a bunch of independently trained agents, and then amortized all of their policies into a single network? That doesn’t seem in any way surprising.”

But Lemon says the new model, and others like it, are creating surprisingly good results, and that training an AI to accomplish varied tasks may eventually create a solid foundation of general knowledge on which a more adaptable model could be based. “I’m sure deep learning is not the end of the story,” he says. “There’ll be other innovations coming along that fill in some of the gaps that we currently have in creativity and interactive learning.”

DeepMind wasn’t available for comment.

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Robotic drones with suction pads can fly, swim or hitch a ride

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A robotic drone that can travel through air and water, and also attach itself to larger objects with a suction cup, could be useful for tagging wild animals, say its creators. The suction cup is inspired by the remora fish, which attaches itself to larger marine creatures in a symbiotic relationship where the remora eats parasites that would irritate its host and also gets a ride in return.

 

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Robot can fly, swim or hitch a ride by sticking to other objects

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An amphibious drone that can attach itself to other objects with a suction cup could be used to track marine animals such as whales



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18 May 2022


A robotic drone that can travel through air and water, and also attach itself to larger objects with a suction cup, could be useful for tagging wild animals, say its creators.

The suction cup is inspired by the remora fish, which attaches itself to larger marine creatures in a symbiotic relationship where the remora eats parasites that would irritate its host and also gets a ride in return.

“My original thought was ‘let’s find a point where we can beat nature’,” says Li Wen at Beihang University in Beijing. “Let’s do a robot that can not only swim and stick underwater, but also can fly into the air and stick in the air. I don’t think there are any animals that can do this.”

Wen and his colleagues created a 3D-printed replica of a remora fish suction pad. The small rubber-like pad has a segmented layout that can create a tight seal even when part of the pad isn’t in contact with a surface.

By changing the volume of each segment once a seal has been made – hydraulically in the robot, but by muscular contraction in the fish – strong suction can be created.

Wen says he was also inspired by the way that kingfishers can fly into water and catch prey, folding their wings as they hit the surface. The drone’s rotors have hinged blades that automatically fold and unfold as the RPM is changed between the high speeds needed for air flight and the lower speeds that work more efficiently in water.

In laboratory tests, the drone, which is 40 centimetres long and wide, successfully attached itself to a moving submersible robot, hitched a ride for a short period and detached again. While attached, it consumed roughly 5 per cent of the power it would have used under its own propulsion.

It can also hitch a ride on objects in the air, where it uses around 2 per cent of the energy required to fly under its own power. The robot can breach the surface of the water, fly stably in air and resubmerge many times in a single journey.

Drone with fish-inspired suction disc

The drone has hinged rotor blades and a segmented suction cup

Lei Li, Yiyuan Zhang, and Nianru Mo

It works at depths of up to 2.2 metres, which is limited by its onboard communications with controllers outside the water. But researchers say that future autonomous devices would be able to operate at much greater depths.

Wen suggests that the drone could be useful in research expeditions and wildlife surveys in remote environments. For example, it could fly high enough to spot whales, dive into the water to attach a GPS tag and then repeat the process many times.

Journal reference: Science Robotics, DOI: 10.1126/scirobotics.abm6695

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