Using artificial intelligence, scientists have confirmed that birds are more colourful near the equator. According to the study's author Christopher Cooney, ''We found that colourfulness was highest in birds from dense, closed forest habitats.'' "In vibrant rainforests, having colours that stand out from the crowd may help tropical species to distinguish themselves from others", he added. The researchers have proved a theory proposed by biologists Charles Darwin, Alexander von Humboldt, and Alfred Russel Wallace in 1850. After comparing the flora and fauna of northern Europe with the tropical region, they were all stunned.

When gravitational waves were first detected in 2015 by the advanced Laser Interferometer Gravitational-Wave Observatory (LIGO), they sent a ripple through the scientific community, as they confirmed another of Einstein's theories and marked the birth of gravitational wave astronomy. As LIGO and its international partners continue to upgrade their detectors' sensitivity to gravitational waves, they will be able to probe a larger volume of the universe--making the detection of gravitational wave sources a daily occurrence rather than weekly or monthly. Scientists hope this will launch a new era of precision astronomy, because combining information from multiple kinds of signals from space is a much more powerful way to study the universe. But realizing this goal will require a radical re-thinking of existing methods used to search for and find gravitational waves. Recently, Argonne National Laboratory computational scientist Eliu Huerta, along with collaborators from the University of Chicago, the University of Illinois at Urbana-Champaign, NVIDIA and IBM, developed a new artificial intelligence framework that allows for accelerated, scalable and reproducible detection of gravitational waves.

When gravitational waves were first detected in 2015 by the advanced Laser Interferometer Gravitational-Wave Observatory (LIGO), they sent a ripple through the scientific community, as they confirmed another of Einstein's theories and marked the birth of gravitational wave astronomy. Five years later, numerous gravitational wave sources have been detected, including the first observation of two colliding neutron stars in gravitational and electromagnetic waves. As LIGO and its international partners continue to upgrade their detectors' sensitivity to gravitational waves, they will be able to probe a larger volume of the universe, thereby making the detection of gravitational wave sources a daily occurrence. This discovery deluge will launch the era of precision astronomy that takes into consideration extrasolar messenger phenomena, including electromagnetic radiation, gravitational waves, neutrinos and cosmic rays. Realizing this goal, however, will require a radical re-thinking of existing methods used to search for and find gravitational waves.

Furthermore, these AI algorithms would only require an inexpensive GPU—like those found in video gaming systems—to process data faster than real …

IMAGE: Scientific visualization of a numerical relativity simulation that describes the collision of two black holes consistent with the binary black hole merger GW170814. The simulation was done on the Theta... view more When gravitational waves were first detected in 2015 by the advanced Laser Interferometer Gravitational-Wave Observatory (LIGO), they sent a ripple through the scientific community, as they confirmed another of Einstein's theories and marked the birth of gravitational wave astronomy. Five years later, numerous gravitational wave sources have been detected, including the first observation of two colliding neutron stars in gravitational and electromagnetic waves. As LIGO and its international partners continue to upgrade their detectors' sensitivity to gravitational waves, they will be able to probe a larger volume of the universe, thereby making the detection of gravitational wave sources a daily occurrence. This discovery deluge will launch the era of precision astronomy that takes into consideration extrasolar messenger phenomena, including electromagnetic radiation, gravitational waves, neutrinos and cosmic rays.

When gravitational waves were first detected in 2015 by the advanced Laser Interferometer Gravitational-Wave Observatory (LIGO), they sent a ripple through the scientific community, as they confirmed another of Einstein's theories and marked the birth of gravitational wave astronomy. Five years later, numerous gravitational wave sources have been detected, including the first observation of two colliding neutron stars in gravitational and electromagnetic waves. As LIGO and its international partners continue to upgrade their detectors' sensitivity to gravitational waves, they will be able to probe a larger volume of the universe, thereby making the detection of gravitational wave sources a daily occurrence. This discovery deluge will launch the era of precision astronomy that takes into consideration extrasolar messenger phenomena, including electromagnetic radiation, gravitational waves, neutrinos and cosmic rays. Realizing this goal, however, will require a radical re-thinking of existing methods used to search for and find gravitational waves.

It's no secret that Los Angeles is notorious for its traffic jams, typically ranking first in studies of the nation's traffic hot spots. Estimates suggest that Angelinos spend an extra 120 hours a year stuck in them. While a nightmare for drivers, the L.A. transportation system does have its advantages if you're devising a new system to quickly predict and potentially redirect that traffic. Researchers from across the U.S. Department of Energy's (DOE) Argonne National Laboratory set out to do just that under the umbrella of a larger project on the design and planning of mobility systems led by collaborators at DOE's Lawrence Berkeley National Laboratory (LBNL). Using an artificial intelligence (AI) technique called machine learning, the team leveraged Argonne's supercomputers to digest traffic patterns from nearly a year's worth of data taken from 11,160 sensors along the large California highway system.

Scientists have harnessed artificial intelligence to translate brain signals into speech, in a step toward brain implants that one day could let people with impaired abilities speak their minds, according to a new study. In findings published Wednesday in the journal Nature, a research team at the University of California, San Francisco, introduced an experimental brain decoder that combined direct recording of signals from the brains of research subjects with artificial intelligence, machine learning and a speech synthesizer.

A new artificial intelligence could help sort normal cells from diseased cells, researchers report in a new study. The Human Cell Atlas is a deep learning algorithm method that uses single-cell RNA sequencing to distinguish activated and deactivated cells within humans at any point, according to a study published Wednesday in Nature Communications. The ability to pinpoint healthy cells from diseased cells at a given time within a person's life cycle. "From a methodological point of view, this represents an enormous leap forward. Previously, such data could only be obtained from large groups of cells because the measurements required so much RNA," Maren Büttner, a researcher at the Institute of Computational Biology of the Helmholtz Zentrum München, said in a news release.

Scientists teamed up to use artificial intelligence to discover new alternatives to steel in record time. As a result, they discovered three new blends to form metallic glass and did this 200 times faster than it has ever been done before. Fang Ren, who developed algorithms to analyze data on the fly while a postdoctoral scholar at SLAC, at a Stanford Synchrotron Radiation Lightsource beamline where the system has been put to use. Metallic glass is essentially an alloy of the future. Normally, a few metals can be mixed together so that the ideal properties of each metal are'added' together to make a'super-metal'.