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Category: robotics/AI – Page 1315

Virusight Diagnostic, an Israeli company that combines artificial intelligence software and spectral technology announced the results of a study that found that its Pathogens Diagnostic device detects COVID-19 with 96.3 percent accuracy in comparison to the common RT-PCR.

The study was conducted by researchers from the Department of Science and Technology, University of Sannio, Benevento, Italy with partner company TechnoGenetics S.p. A.

The Virusight solution was tested on 550 saliva samples and found to be safe and effective.

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Recent technological advances, such as the development of increasingly sophisticated machine learning algorithms and robots, have sparked much debate about artificial intelligence (AI) and artificial consciousness. While many of the tools created to date have achieved remarkable results, there have been many discussions about what differentiates them from humans.

More specifically, computer scientists and neuroscientists have been pondering on the difference between and “consciousness,” wondering whether machines will ever be able to attain the latter. Amar Singh, Assistant Professor at Banaras Hindu University, recently published a paper in a special issue of Springer Link’s AI & Society that explores these concepts by drawing parallels with the fantasy film “Being John Malkovich.”

“Being John Malkovich” is a 1999 film directed by Spike Jonze and featuring John Cusack, Cameron Diaz, and other famous Hollywood stars. The film tells the story of a puppeteer who discovers a portal through which he can access the mind of the movie star John Malkovich, while also altering his being.

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Lack of a robotic hand that can match a human hand will continue to delay full automation.

SINGAPORE, May 30 (Reuters) — After struggling to find staff during the pandemic, businesses in Singapore have increasingly turned to deploying robots to help carry out a range of tasks, from surveying construction sites to scanning library bookshelves.

The city-state relies on foreign workers, but their number fell by 235,700 between December 2019 and September 2021, according to the manpower ministry, which notes how COVID-19 curbs have sped up “the pace of technology adoption and automation” by companies.

At a Singapore construction site, a four-legged robot called “Spot”, built by U.S. company Boston Dynamics, scans sections of mud and gravel to check on work progress, with data fed back to construction company Gammon’s control room.

Continue reading “From baristas to inspectors: Singapore’s robot workforce plugs labour gaps” | >

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[Alexander] created codex_py2cpp as a way of experimenting with Codex, an AI intended to translate natural language into code. [Alexander] had slightly different ideas, however, and created codex_py2cpp as a way to play with the idea of automagically converting Python into C++. It’s not really intended to create robust code conversions, but as far as experiments go, it’s pretty neat.

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Spike-based neuromorphic hardware holds the promise to provide more energy efficient implementations of Deep Neural Networks (DNNs) than standard hardware such as GPUs. But this requires to understand how DNNs can be emulated in an event-based sparse firing regime, since otherwise the energy-advantage gets lost. In particular, DNNs that solve sequence processing tasks typically employ Long Short-Term Memory (LSTM) units that are hard to emulate with few spikes. We show that a facet of many biological neurons, slow after-hyperpolarizing (AHP) currents after each spike, provides an efficient solution. AHP-currents can easily be implemented in neuromorphic hardware that supports multi-compartment neuron models, such as Intel’s Loihi chip. Filter approximation theory explains why AHP-neurons can emulate the function of LSTM units.

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Classifying celestial objects is a long-standing problem. With sources at near unimaginable distances, sometimes it’s difficult for researchers to distinguish between objects such as stars, galaxies, quasars or supernovae.

Instituto de Astrofísica e Ciências do Espaço’s (IA) researchers Pedro Cunha and Andrew Humphrey tried to solve this classical problem by creating SHEEP, a that determines the nature of astronomical sources. Andrew Humphrey (IA & University of Porto, Portugal) comments: “The problem of classifying is very challenging, in terms of the numbers and the complexity of the universe, and is a very promising tool for this type of task.”

The first author of the article, now published in the journal Astronomy & Astrophysics, Pedro Cunha, a Ph.D. student at IA and in the Dept. of Physics and the University of Porto, says, “This work was born as a side project from my MSc thesis. It combined the lessons learned during that time into a unique project.”

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