Neither the machine or nor the professional human debaters were given prior knowledge of the subject of the on-stage debate, which took place in San Francisco on Monday.
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Nature article presents an AI developed by Google’s Medical Brain team which outperforms hospitals’ own warning system in predicting the death risk among hospit…al patients.
Google’s Medical Brain team is now training its AI to predict the death risk among hospital patients — and its early results show it has slightly higher accuracy than a hospital’s own warning system.
Bloomberg describes the healthcare potential of the Medical Brain’s findings, including its ability to use previously unusable information in order to reach its predictions. The AI, once fed this data, made predictions about the likelihood of death, discharge, and readmission.
In a paper published in Nature in May, from Google’s team, it says of its predictive algorithm:
Glossing over the fact ageing is a chronic decline in function won’t help with anything, let alone ending ageism.
At times, I think that I have written enough rejuvenation advocacy articles and that every time I write a new one, I’m just repeating myself. I sometimes say to myself that I’ve written about concerns and misconceptions from so many angles that I’ve probably exhausted all the options. However, from time to time, there comes the bittersweet reassurance that I’m not going to be out of a job any time soon.
The culprit
I came across a Refinery29 article titled “‘Anti-Aging’ Is Officially Being Phased Out—& That’s Good News For Women.” The article summarizes, and wholeheartedly agrees with, a report by the Royal Society For Public Health, “That Age Old Question”. The report endeavors to expose ageism and help end discrimination against older people, but while it does make a handful of valid points, it seems to suggest that sweeping the true nature of aging under the rug will help to end ageism.
A contentious proposal to link oversight of California’s electric grid with other western states faces a crucial test Tuesday in a state Senate committee.
Supporters say regionalizing the grid would make it easier and cheaper to deploy renewable energy across the western United States. But critics, including some environmentalists and consumer advocates, say California would jeopardize its efforts to require the expansion of renewables.
California has greatly expanded the use of renewable energy sources, particularly wind and solar, but that’s brought new challenges for grid operators to manage supply and demand as weather patterns and sunlight vary.
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For the first time, astronomers have directly imaged the formation and expansion of a fast-moving jet of material ejected when the powerful gravity of a supermassive black hole ripped apart a star that wandered too close to the massive monster.
The scientists tracked the event with radio and infrared telescopes, including the National Science Foundation’s Very Long Baseline Array (VLBA) and NASA’s Spitzer Space Telescope, in a pair of colliding galaxies called Arp 299. The galaxies are nearly 150 million light-years from Earth. At the core of one of the galaxies, a black hole 20 million times more massive than the Sun shredded a star more than twice the Sun’s mass, setting off a chain of events that revealed important details of the violent encounter. The researchers also used observations of Arp 299 made by NASA’s Hubble space telescope prior to and after the appearance of the eruption.
Only a small number of such stellar deaths, called tidal disruption events, or TDEs, have been detected. Theorists have suggested that material pulled from the doomed star forms a rotating disk around the black hole, emitting intense X-rays and visible light, and also launches jets of material outward from the poles of the disk at nearly the speed of light.
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Neural networks running on GPUs have achieved some amazing advances in artificial intelligence, but the two are accidental bedfellows. IBM researchers hope a new chip design tailored specifically to run neural nets could provide a faster and more efficient alternative.
It wasn’t until the turn of this decade that researchers realized GPUs (graphics processing units) designed for video games could be used as hardware accelerators to run much bigger neural networks than previously possible.
That was thanks to these chips’ ability to carry out lots of computations in parallel rather than having to work through them sequentially like a traditional CPU. That’s particularly useful for simultaneously calculating the weights of the hundreds of neurons that make up today’s deep learning networks.
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