When it comes to the possibilities and possible perils of artificial intelligence (AI), learning and reasoning by machines without the intervention of humans, there are lots of opinions out there. "Anything that could give rise to smarter-than-human intelligence--in the form of Artificial Intelligence, brain-computer interfaces, or neuroscience-based human intelligence enhancement - wins hands down beyond contest as doing the most to change the world. Follow that out further to, say, 2045, we will have multiplied the intelligence, the human biological machine intelligence of our civilization a billion-fold." It's really an attempt to understand human intelligence and human cognition."
Sea levels are already rising, and if nations around the world continue on emitting greenhouse gases without greatly cutting emissions, that sea level rise could be devastating. Nuclear war could kill millions and alter the Earth's climate, making parts of our planet uninhabitable. According to a 2016 report, outbreaks of infectious diseases in the future pose a major risk to human life and world economies. The largest refugee crisis since World War II is currently taking place because of rampant inequality, religious strife, armed conflict, discrimination, and the search for better lives in the West.
Knowing the historical statistical performance, the manager may choose to replace the current pitcher with someone who has better historical performance against the batter. A study recently published in the journal Nature documents how Stanford researchers developed a machine learning algorithm to detect potential cases of skin cancer. Put simply, good predictive analytics require a large sampling of data to work well. Analyzing historic data to predict future outcomes only works if the past is truly representative of the future.
The research comes from the Center for Neuroprosthetics and Brain Mind Institute, School of Life Sciences, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland. The regathers behind the development are hopeful it will lead to better outcomes for patients undergoing rehabilitation following incidences like a stroke or a spinal cord injury or strokes. READ MORE: Mayo Clinic's new startup to tackle diseases using AI Recovery plans for spinal cord injuries and strokes typically require usually many hours of supported walking, using devices like treadmills, with the walking aid pre-programmed by a medic to provide a steady pace. The new development has been described in the journal Science Translational Medicine, with the research paper headed "A multidirectional gravity-assist algorithm that enhances locomotor control in patients with stroke or spinal cord injury."
They genetically engineered mice with neurons that glow yellow when activated during memory storage, and red when activated during memory recall. But in the Alzheimer's mice, different cells glowed red during recall, suggesting that they were calling up the wrong memories. Using a genetic engineering technique called optogenetics, Denny's team went on to reactivate the lemon-shock memory in the Alzheimer's mice. The next step will be to confirm that the same memory storage and retrieval mechanisms exist in people with Alzheimer's disease, because mouse models do not perfectly reflect the condition in humans, says Martins.
Closely linked to artificial intelligence (AI), it is helping machines do many things that used to be in the human domain alone. "We use artificial intelligence and machine learning to try to teach computers how to interpret images," Rueckert explains. So Rueckert and his team don't just use machine learning to teach their IT systems to spot lesions. In the Imperial College case, one system tries to make fake scans that are so good the other system thinks they are real.
The University of Rochester Medical Center explained that the researchers designed their experiment so that a person's eyes would naturally overshoot the target as they tried to track the visual. As the experiment went on, a healthy person's eyes would adjust to overcome that design and make more precise movements, while people with autism did not -- their eyes kept missing the target. "The inability of the brain to adjust the size of eye movement may not only be a marker for cerebellum dysfunction, but it may also help explain the communication and social interaction deficits that many individuals with [autism spectrum disorder] experience." Doctors might be able to track eye movements to detect the developmental disorder autism, which would help them diagnose the condition earlier.
Earlier this year, IBM scientists collaborated with researchers at the University of Alberta and the IBM Alberta Centre for Advanced Studies (CAS) to publish new research regarding the use of AI and machine learning algorithms to predict instances of schizophrenia with a 74 percent accuracy. Using AI and machine learning, 'computational psychiatry' can be used to help clinicians more quickly assess – and therefore treat – patients with schizophrenia. In this schizophrenia research, we have learned that powerful technology can be used to predict the likelihood of a previously-unseen patient having schizophrenia. This kind of innovative collaboration is just one example of the work being done between IBM and the University of Alberta through the IBM Alberta Centre for Advanced Studies.
The algorithms sifted through de-identified brain functional Magnetic Resonance Imaging (fMRI) data from an initiative called the Function Biomedical Informatics Research Network. The neuroimaging information used in this study was of 95 patients diagnosed with schizophrenia and schizoaffective disorders as well as individuals that served as a healthy control group. Essentially, the machine learning algorithms were able to explore these scans to create a model of schizophrenia that pinpoints brain connections most associated with the illness. The data also indicated that the diagnostic could distinguish between patients with schizophrenia and the control group with 74 percent accuracy, even as these images were collected from multiple sites through different means.
Autism is characterized by social and communicative difficulties, specific interests that people with autism are capable of speaking about for hours (like meteorological modelling, in Sophie's case), and stereotyped behaviors. To diagnose autism spectrum disorder (ASD), doctors and psychologists evaluate quantitative criteria using tests and questionnaires, but also qualitative criteria, like interests, stereotyped movements, difficulties with eye contact and language and isolation. But while autistic girls show similar test results to autistic boys, the clinical manifestation of their condition differs, at least in cases where language has been acquired. Since September 2016, the Francophone Association of Autistic Women (Association francophone des femmes autistes, or AFFA) has been fighting for recognition of the specific ways autism manifests in women.