Abstract: This paper describes neural-fortran, a parallel Fortran framework for neural networks and deep learning. It features a simple interface to construct feed-forward neural networks of arbitrary structure and size, several activation functions, and stochastic gradient descent as the default optimization algorithm. Neural-fortran also leverages the Fortran 2018 standard collective subroutines to achieve data-based parallelism on shared- or distributed-memory machines. First, I describe the implementation of neural networks with Fortran derived types, whole-array arithmetic, and collective sum and broadcast operations to achieve parallelism. Second, I demonstrate the use of neural-fortran in an example of recognizing hand-written digits from images.

I posted here a few weeks back looking for members to join me in putting together an AI research organization. As of today, we've got the groundwork laid for another round of recruitment, so here we go again! We currently have six figures of compute funding and several deep learning experts (as well as domain experts like scientists, doctors, executives, and engineers) on our team. Our goal is to work together to do what we otherwise couldn't alone, and create opportunities for people of all backgrounds to work on research that they are passionate about while publishing work that is valuable to the world. We can provide technical and moral support as well as huge amounts of compute for research projects.

Artificial intelligence is having a significant impact on mainstream business and computing after years of being in the hype cycle. Companies such as Amazon and Netflix have saved billions of dollars a year, and AI is expected to boost the global economy by trillions of dollars over the next several years. Concerns about AI's use remain, however, including security risks and biases it could introduce into hiring and society as a whole as well as bad decisions it might make due to poor underlying data quality. Here's a snapshot of the present and future of AI, told in 11 statistics: That's a 14 percent increase, more than the current economic output of China and India combined, a PwC study projects. Some $6.6 trillion of the boost will come from increased productivity, while $9.1 trillion will arrive as a result of increased economic consumption.

These days you'll be hard-pressed to find someone who hasn't interrogated Siri (or Alexa), enjoyed the movie Netflix suggested, or fallen victim to purchasing that additional item Amazon recommended--all of which are only possible due to artificial intelligence. AI has been a field of study as far back as the 1950s, but advances have skyrocketed in recent years. These days AI is everywhere and has increasingly become part of all of our everyday lives. Thanks to AI, once tedious tasks are now simple, single-click activities. And as technology becomes even more pervasive, it will only continue to impact our personal and professional lives.

When it comes to teaching people a little something about humanity at large, the science fiction genre manages to enlighten our minds time and again. From Ray Bradbury's "Fahrenheit 451" to Aldous Huxley's "Brave New World," this type of literature offers an intimate commentary on both human nature and our modern world. Thanks to the works of these writers and the success of iconic films like the Star Wars, sci-fi has become apart of the mainstream. Because of that, it's now a genre regarded for its sweeping visions of where we're headed as a society. And Tal M. Klein's book, The Punch Escrow, a thrilling story about a future society where teleportation has run amok, is no exception The Punch Escrow tackles life in the 22nd century (2147 to be exact), where current problems such as pollution and diseases are managed by a plethora of technological advances.

Humans and machines worked together to help train an artificial intelligence -- AI -- model that outperformed other clickbait detectors, according to researchers at Penn State and Arizona State University. In addition, the new AI-based solution was also able to tell the difference between clickbait headlines that were generated by machines -- or bots -- and ones written by people, they said. In a study, the researchers asked people to write their own clickbait -- an interesting, but misleading, news headline designed to attract readers to click on links to other online stories. The researchers also programmed machines to generate artificial clickbaits. Then, the headlines made by both people and machines were used as data to train a clickbait-detection algorithm.

This AI is one step ahead of... itself. Researchers at Harvard University and the MIT-IBM Watson AI Lab have created a tool to help combat the spread of misinformation. The tool, called GLTR (for Giant Language Model Test Room), uses artificial intelligence to detect the very statistical text patterns that give AI away, according to the team's June report. GLTR highlights words in the text based on the likelihood that they'll appear again -- green is the most predictable, red and yellow are less predictable, and the least predictable is purple. A tool like that could come in handy for social media sites like Twitter and Facebook that have to contend with rampant content created by bots.

That student with the heart of the world was born, My data burns the same stars in a window. No human would ever mistake these lines for award-winning verse. If they're a bit fanciful and lack coherence, that's because they were composed by a computer algorithm trained on more than 20 million words of 19th century poetry. The seed word in this case was "student." The resulting word salad makes it clear that as powerful as AI is, it still can't create like a human.

Fox News Flash top headlines for August 29 are here. Check out what's clicking on Foxnews.com A Pennsylvania court ruled Tuesday that making a "gunlike hand gesture" is a crime after a man made the hand motion during an argument with his neighbor -- an act which reportedly made several nearby residents nervous and prompted a call to police. Stephen Kirchner, 64, made the gesture toward his neighbor in Manor Township in June 2018, according to surveillance video. Kirchner, walking alongside a female neighbor, "stopped, made eye contact with [the male neighbor] and then made a hand gesture at him imitating the firing and recoiling of a gun," according to court documents.

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