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This prevents Alzheimer's?

FOX News

Do you find yourself making multiple trips to Starbucks daily? Well, those caffeine headaches and jitters may be worth it in the long run. New research from the Institute for Scientific Information on Coffee found that people who drink between three and five cups of coffee daily may lower their risk of Alzheimer's, dementia, and Parkinson's disease by up to 27 percent. "Moderate coffee consumption could play a significant role in reducing cognitive decline which would impact health outcomes and healthcare spending," said professor Rodrigo A. Cunha of University of Coimbra in Portugal. The combination of caffeine, antioxidants, and polyphenol naturally found in coffee are the likely contributing factors to this scientific discovery.


Robots of the future may be given digital serotonin pills to 'stop them getting depressed'

Daily Mail - Science & tech

Getting depressed might seem a strange affliction for a robot, but artificially intelligent brains may also suffer from similar mental health problems to people. That's the claim put forward by an American neuroscientist, who says that machines could even hallucinate, if not monitored correctly. Developers will need to create software equivalents to anti-depressants, which help to control levels of the neurotransmitter serotonin in the brain, he recommends. Artificial intelligence and robotic brains may suffer from some of the mental health issues traditionally associated with humans. Zachary Mainen works at the Champalimaud Centre for the Unknown in Lisbon and studies how the brain makes decisions.


Novel Math Theory Could Upgrade Machine Vision

#artificialintelligence

A team of Italian mathematicians, including one who is also a neuroscientist from the Champalimaud Centre for the Unknown (CCU), in Lisbon, Portugal, has shown that artificial vision machines can learn to recognize complex images spectacularly faster by using a mathematical theory that was developed 25 years ago by one of this new study's co-authors. Their results have been published in the journal Nature Machine Intelligence. During the last decades, machine vision performance has exploded. For example, these artificial systems can now learn to recognise virtually any human face – or to identify any individual fish moving in a tank, in the midst of a large number of other almost identical fish which are also moving. The machines we're talking about are, in fact, electronic models of networks of biological neurons, and their aim is to simulate the functioning of our brain, which is as good as it gets at performing these visual tasks – and this, without any conscious effort on our part.


Novel math could bring machine learning to the next level

#artificialintelligence

A team of Italian mathematicians, including a neuroscientist from the Champalimaud Centre for the Unknown (CCU), in Lisbon, Portugal, has shown that artificial vision machines can learn to recognize complex images more quickly by using a mathematical theory that was developed 25 years ago by one of this new study's co-authors. Their results have been published in the journal Nature Machine Intelligence. In recent decades, machine vision performance has vastly improved. Artificial systems can now learn to recognize virtually any human face or to identify any individual fish moving in a tank. Such machines are, in fact, electronic models of networks of biological neurons, and their aim is to simulate the functioning of the brain, which excels at these visual tasks without any conscious effort on our part.


Novel math could bring machine learning to the next level

#artificialintelligence

A team of Italian mathematicians, including a neuroscientist from the Champalimaud Centre for the Unknown (CCU), in Lisbon, Portugal, has shown that artificial vision machines can learn to recognize complex images more quickly by using a mathematical theory that was developed 25 years ago by one of this new study's co-authors. Their results have been published in the journal Nature Machine Intelligence. In recent decades, machine vision performance has vastly improved. Artificial systems can now learn to recognize virtually any human face or to identify any individual fish moving in a tank. Such machines are, in fact, electronic models of networks of biological neurons, and their aim is to simulate the functioning of the brain, which excels at these visual tasks without any conscious effort on our part.