I never met Ursula K. Le Guin, who died on January 22, 2018, at the age of eighty-eight, in Portland, Oregon, her home for many years. And yet we became good friends during the last two months of her life, entirely by way of e-mail. I inaugurated the correspondence on November 21, 2017, and she replied on November 24th. One of the things I like least about being very old is the unreliability of my energy. Working at poetry or a story is, always has been, the job I want to be doing, the work that keeps me steady and content.
This month, we discuss AI education. Joining the discussion this time are: Tom Dietterich (Oregon State University), Sabine Hauert (University of Bristol), Holger Hoos (Leiden University) and Oskar von Stryk (Technische Universität Darmstadt). Sabine Hauert: As we are starting the new term, the question is how should we do AI education and what should students be learning? Thinking more broadly, how should we rethink AI education for the general population? There will be huge swaths of the public that will need to gain an understanding of AI, or be trained in the use of AI.
The US city of Portland, Maine on Wednesday voted to ban the use of facial recognition by police and city officials. The Bangor Daily News reported that voters passed a ballot initiative "bolstering a ban on facial recognition by city agencies". The initiative follows a city council vote in August, which put a preliminary ban in place as an ordinance. The citizens are entitled to a minimum of $1,000 in fines if they are subjected to a facial recognition scan by police. Portland joins Boston, San Francisco; Portland, Oregon and the city of Oakland in Northern California in banning the use of facial recognition technology by the authorities.
In order to hold police accountable when they try to hide their identities, a growing number of activists are developing facial recognition tools that identify cops, The New York Times reports -- a striking inversion of the way cops tend to use facial recognition on protestors and suspects. Police are hiding their identities while cracking down on protests, in other words, just to be outed by the same invasive technology that they use to surveil the populace. One of the projects was a shower thought for self-taught programmer Christopher Howell. He's identifying cops in Portland, Oregon because they were permitted to cover their names while responding to protests. Portland banned facial recognition for cops and companies, but the NYT reports that Howell's project is permitted because he's an individual working on a passion project.
Video games are playing a big part in helping people cope during the coronavirus pandemic. Since earlier this spring with the onset of stay-at-home orders meant to stem the spread of COVID-19, more Americans have pressed play on video games. For some, games are an entertaining way to pass the time not spent on other pursuits. Others use them to stay connected with friends they used to see in person – and to bond with family members. Jennifer Fidler, 47, and her husband of Portland, Oregon, have been playing "Animal Crossing: New Horizons" with her two middle school-aged daughters since the pandemic led to school closings.
Portland, Maine is the latest in the growing list of cities in the US to ban facial recognition technologies. According to Bangor Daily News, people voted in favor of of passing a new measure that strengthens Portland's existing ban on the use of facial recognition tech by law enforcement agencies and public officials. City councilors originally agreed on a ban back in August with the understanding that the voter referendum would replace their ordinance if it passes. Now that it has passed, it can't be touched for at least five years. Back in September, Portland, Oregon passed what could be the strictest municipal ban on facial recognition in the country -- one that prohibits even private businesses from deploying the technology in public spaces.
The year 2020 continues to be difficult here on Earth, where the pandemic is exploding again in regions of the world that were once successful in containing it. Germany reported a record number of cases this week alongside Poland and the Czech Republic, as the U.S. counted 500,000 new cases. It's the backdrop to a tumultuous U.S. election, which experts fear will turn violent on election day. Meanwhile, Western and Southern states like Oregon, Washington, California, and Louisiana are reeling from historically destructive wildfires, severe droughts, and hurricanes. Things are calmer in outer space, where scientists are applying AI to make exciting new finds.
Ellen is Technical Evangelist at H2O.ai. She is an international speaker, author, and scientist with a PhD in biochemistry from Rice University. Ellen has been a committer for Apache Drill and Apache Mahout projects and previously a laboratory researcher in molecular biology. In addition to authoring publications in technical fields from genetics to oceanography, she is co-author of data-related books published by O'Reilly Media, including AI & Analytics in Production, Machine Learning Logistics, Streaming Architecture, Introduction to Apache Flink and the Practical Machine Learning series. Ellen has been an invited speaker for keynotes at JFokus in Stockholm, Big Data London, the University of Sheffield Methods Institute (UK) and NoSQL Matters in Barcelona as well as invited talks at Nike Tech Talks (Portland OR), Berlin Buzzwords and Strata Data conferences in San Jose CA and London.
Fifty million artificial neurons--a number roughly equivalent to the brain of a small mammal--were delivered from Portland, Oregon-based Intel Corp. to Sandia National Laboratories last month, said Sandia project leader Craig Vineyard. The neurons will be assembled to advance a relatively new kind of computing, called neuromorphic, based on the principles of the human brain. Its artificial components pass information in a manner similar to the action of living neurons, electrically pulsing only when a synapse in a complex circuit has absorbed enough charge to produce an electrical spike. "With a neuromorphic computer of this scale," Vineyard said, "we have a new tool to understand how brain-based computers are able to do impressive feats that we cannot currently do with ordinary computers." Improved algorithms and computer circuitry can create wider applications for neuromorphic computers, said Vineyard. Sandia manager of cognitive and emerging computing John Wagner said, "This very large neural computer will let us test how brain-inspired processors use information at increasingly realistic scales as they come to actually approximate the processing power of brains.
Image matting plays a key role in image and video editing and composition. Although existing deep learning approaches can produce acceptable image matting results, their performance suffers in real-world applications, where the input images are mostly high resolution. To address this, a group of researchers from UIUC, Adobe Research and the University of Oregon have proposed HDMatt, the first deep learning-based image matting approach for high-resolution image inputs. Generally, deep learning approaches take an entire input image and an associated trimap to infer the alpha matte using convolutional neural networks. Such methods however may fail when dealing with high-resolution input images in sizes of 5000 5000 pixels or higher due to hardware limitations. The researchers designed HDMatt to crop an input image and trimap into patches, then estimate the alpha values of each patch.