AI: The history of a problem – Becoming Human


AI, Neural Networks, Machine Learning and other buzzwords are not new; they are with us from late 50s, but why did they become so much of a trend only now? The business focus changed from investing into so-called "artificial intelligence" to development of systems that could work with already gathered data, process and re-structurize it. Bayes was widely used in anti-spam, Markov's chains predicted criminal structure behavior, search engines developed decision trees to predict user input, speech and image recognition was no miracle anymore, and it was good. Basically, we returned to 50s -- we are trying to create universal structures, mimic human brain, and create entities that can process mixed data as our brains do.

Autism Test: Eye Movement May Help Diagnose Developmental Disorder

International Business Times

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.

Utilizing A.I., Machine Learning to Better Understand Schizophrenia


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.

Grant Gochnauer: Awesome Humans -- Issue #100 – Awesome Humans – Medium


Dementia: Mediterranean Diet Could Help Stop Alzheimer's -- New research suggests a Mediterranean diet could cut the risk for dementia and Alzheimer's. Despite executing the best growth practices, picking the low hanging fruit, and having a great team, they struggle to grow. AI investment has turned into a race for patents and intellectual property (IP) among the world's leading tech companies. "If you wanted to power the entire United States with solar panels, it would take a fairly small corner of Nevada or Texas or Utah; you only need about 100 miles by 100 miles of solar panels to power the entire United States," Musk said during his keynote conversation on Saturday at the event in Rhode Island.

Career of the Future: Robot Psychologist

Wall Street Journal

One subset that has taken off is neural networks, systems that "learn" as humans do through training, turning experience into networks of simulated neurons. "A big problem is people treat AI or machine learning as being very neutral," said Tracy Chou, a software engineer who worked with machine learning at Pinterest Inc. "And a lot of that is people not understanding that it's humans who design these models and humans who choose the data they are trained on." It is a difficult enough problem to crack that the Defense Advanced Research Projects Agency, better known as Darpa, is funding researchers working on "explainable artificial intelligence." Here's why we're in this pickle: A good way to solve problems in computer science is for engineers to code a neural network--essentially a primitive brain--and train it by feeding it enormous piles of data.

Artificial intelligence can help better diagnose schizophrenia, says U of A and IBM researchers


The research, published in May's npj Schizophrenia, with University of Alberta postdoctoral researcher Mina Gheiratmand as the primary author, was able to predict instances of schizophrenia with 74 per cent accuracy. Mina Gheiratmand, primary author of the research study using brain MRI scans to identify schizophrenia in patients, in Edmonton, July 20, 2017. These are still the early stages, Gheiratmand said, of using these technologies in practice. "If you have a model that can predict the disease at earlier stages, then you can intervene earlier," she said.

AI and Deep Learning, Explained Simply


AI trained to win at poker games learned to bluff, handling missing and potentially fake, misleading information. Machine learning (ML), a subset of AI, make machines learn from experience, from examples of the real world: the more the data, the more it learns. Each method might make different errors, so averaging their results can win, at times, over single methods. So it should be the "smaller" AI to claim that the human brain as not real intelligence, but only brute force computation.

IBM's AI Is Improving Healthcare By Advancing Cancer, Schizophrenia Research

International Business Times

A team of researchers from the University of Alberta, Canada and tech giant IBM has developed artificial intelligence and machine learning algorithms, which can diagnose schizophrenia by studying the blood flow of the brain. The study of the human brain has been a challenging medical field, especially brain related ailments such as Schizophrenia. The team behind the research also aims to employ the algorithm in research for other diseases such as Huntington's disease, and provide a better insight into a brain afflicted with them. The company's AI software called Watson is being employed in genomics research for cancer.

Connecting our Brain to Machines: the Final Barrier? - OpenMind


The connection will be achieved through the so-called brain-to-computer interface.Credit: Natural Science Foundation Javier Mínguez and Luis Montesano, researchers from BitBrain, a company specializing in applied neuro-technologies, explain to OpenMind that "it is not that we are close to connecting our brains to technologies to interact with the exterior. Leading centres in Europe and the United States have been working in this discipline for years, including big technology companies such as Facebook or Neuralink from the magnate Elon Musk, the founder of Tesla and SpaceX. What is new is that the connection of a human brain to a computer with implantable microelectrodes is now a real scientific option," explained Jens Caluse of the Institute of Ethics and History of Medicine at the University of Tübingen (Germany) in a publication in the journal Nature. The connection of a human brain to a computer with implantable microelectrodes is now a real scientific option.

Intel Movidius Neural Compute Stick brings AI brains to USB port


With a USB hub, you can plug several Intel Movidius Neural Compute Sticks into your laptop. Intel's $80 Movidius Neural Compute Stick lets you plug some computing brains into your laptop's USB port. That's the kind of thing that can be handy if you're trying to work out computer vision in your drone or help your cleaning robot tell the difference between a cat and a coffee table. Intel announced the device at the conference on Computer Vision and Pattern Recognition on Thursday.