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Blog – Page 107

Researchers at Northwestern University and Israel’s Tel Aviv University have overcome a major barrier to achieving a low-cost solution for advanced robotic touch. The authors argue that the problem that has been lurking in the margins of many papers about touch sensors lies in the robotic skin itself.

In the study, inexpensive silicon rubber composites used to make skin were observed to host an insulating layer on the top and bottom surfaces, which prevented direct electrical contact between the sensing polymer and the monitoring surface electrodes, making accurate and repeatable measurements virtually impossible. With the error eliminated, cheap robotic skins could allow robots to mimic human touch, allowing them to sense an object’s curves and edges, necessary to properly grasp it.

Researchers provide accurate, more reliable method to measure touch reception.

Researchers at Northwestern University and Israel’s Tel Aviv University have discovered a problem with robotic skin, that, once eliminated, could allow robots to better mimic human touch.

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Today, we’re launching Anthropic’s AI for Science program – a new initiative designed to accelerate scientific research and discovery through access to our API. This program will provide free API credits to support researchers working on high-impact scientific projects, with a particular focus on biology and life sciences applications.

Why AI for Science? At Anthropic, we believe that AI has the potential to significantly accelerate scientific progress. Advanced AI reasoning and language capabilities can help researchers analyze complex scientific data, generate hypotheses, design experiments, and communicate findings more effectively. By reducing the time and resources needed for scientific discovery, we can help address some of humanity’s most pressing challenges.

Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems.

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We, of course, feel “internal experiences,” that thing we call self, and we know very well when we’ve woken up. Consciousness, in fact, is what we lose when we fall asleep and regain when we wake up. ChatGPT 4.0 is emulating those human feelings. That doesn’t mean it actually feels them. But what if it does feel them one day? Will we listen to it then?

Schneider is among the intellectuals who believe that the question of machine consciousness is worth examining in depth. Not because she believes we’re already there, but because she believes it will happen sooner or later. Like Hassabis, she estimates that artificial general intelligence (AGI) — the name computer scientists give to something close enough to human intelligence to escape the simulacrum label and access a qualitatively different level — is a few decades away.

AGI will be a system capable of learning from experience without having to swallow the entire internet before breakfast; capable of abstracting information, projecting actions, and understanding situations it has never encountered before. And yes, perhaps capable of having “inner experiences,” or what we might call a form of consciousness. Don’t take it out on me; it’s philosophers who are examining this question.

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A high-resolution imaging system captures distant objects by shining laser light on them and detecting the reflected light.

One of astronomers’ tricks for observing distant objects is intensity interferometry, which involves comparing the intensity fluctuations recorded at two separate telescopes. Researchers have now applied this technique to the imaging of remote objects on Earth [1]. They developed a system that uses multiple laser beams to illuminate a distant target and uses a pair of small telescopes to collect the reflected light. The team demonstrated that this intensity interferometer can image millimeter-wide letters at a distance of 1.36 km, a 14-fold improvement in spatial resolution compared with a single telescope.

Interferometry is common in radio astronomy, where the signal amplitudes from a large array of radio telescopes are summed together in a way that depends on the relative phases of the radio waves. Intensity interferometry is something else. It doesn’t involve addition of amplitudes or preservation of phases. Instead, light is recorded from a single source at two separate detectors (or telescopes), and the fluctuations in the intensities of the two signals are compared. Spatial information on the source comes from analyzing how these fluctuations are correlated in time and how this correlation depends on the detector separation.

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An atomic magnetometer uses lasers and a gas of atoms, such as rubidium, to detect magnetic fields. The atoms behave like tiny magnetic compasses, with their spins moving in response to magnetic forces. Using two atomic species—in so-called comagnetometers—boosts performance and opens the possibility of detecting exotic spin interactions predicted in theories that go beyond the standard model of particle physics (see Viewpoint: Spin Gyroscope is Ready to Look for New Physics). Now a new design using a pulsed laser rather than a continuous-laser beam has the potential to improve performance even further [1].

Atomic magnetometry requires two light beams: a pump beam that aligns the atomic spins in a certain direction and a probe beam that detects the movement of those spins relative to that alignment direction. With a single species of atoms, one can measure the local magnetic field. With two species of atoms, one can cancel the magnetic-field signal and other background effects and search for possible spin-dependent signals from dark matter or from other hypothetical particles.

Jingyao Wang from Princeton University and her colleagues have developed a comagnetometer based on a bell-shaped vapor cell filled with rubidium and neon atoms. By applying their pump laser in a repeating pulse pattern (on for 6 ms, off for 20 ms), the researchers can make spin measurements “in the dark” and avoid the noise of the laser. With further improvements, the team predicts its comagnetometer will be 4 times more sensitive than current continuous-laser comagnetometers to potential signals from axions or from other hypothetical particles.

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Humans are the only species on Earth known to use language. They do this by combining sounds into words and words into sentences, creating infinite meanings.

This process is based on linguistic rules that define how the meaning of calls is understood in different sentence structures. For example, the word “ape” can be combined with other words to form compositional sentences that add meaning: “the ape eats” or append meaning: “big ape,” and non-compositional idiomatic sentences that create a completely new meaning: “go ape.”

A key component of language is syntax, which determines how the order of words affects meaning. For instance, how “go ape” and “ape goes” convey different meanings.

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A way to greatly enhance the efficiency of a method for correcting errors in quantum computers has been realized by theoretical physicists at RIKEN. This advance could help to develop larger, more reliable quantum computers based on light.

Quantum computers are looming large on the horizon, promising to revolutionize computing within the next decade or so.

“Quantum computers have the potential to solve problems beyond the capabilities of today’s most powerful supercomputers,” notes Franco Nori of the RIKEN Center for Quantum Computing (RQC).

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New research from a team of cognitive scientists and evolutionary biologists finds that chimpanzees drum rhythmically, using regular spacing between drum hits. Their results, published in Current Biology, show that eastern and western chimpanzees—two distinct subspecies—drum with distinguishable rhythms.

The researchers say these findings suggest that the building blocks of human musicality arose in a common ancestor of chimpanzees and humans.

“Based on our previous work, we expected that western chimpanzees would use more hits and drum more quickly than eastern chimpanzees,” says lead author Vesta Eleuteri of the University of Vienna, Austria. “But we didn’t expect to see such clear differences in or to find that their drumming rhythms shared such clear similarities with human .”

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