GITAI is a robotics startup with offices in Japan and the United States that's developing tech to put humanoid telepresence robots in space to take over for astronauts. Today, GITAI is announcing a joint research agreement with JAXA (the Japanese Aerospace Exploration Agency) to see what it takes for robots to be useful in orbit, with the goal of substantially reducing the amount of money spent sending food and air up to those demanding humans on the International Space Station. It's also worth noting that GITAI has some new hires, including folks from the famous (and somewhat mysterious) Japanese bipedal robot company SCHAFT. A quick reminder about SCHAFT: The company was founded by members of the JSK Laboratory at the University of Tokyo in order to build a robot to compete in the DARPA Robotics Challenge Trials in 2013. SCHAFT won the DRC Trials by a substantial margin, scoring 27 points out of a possible 32, 7 more points than the second place team (IHMC).
Government usually isn't the place to look for innovation in IT or new technologies like artificial intelligence. But Ott Velsberg might change your mind. As Estonia's chief data officer, the 28-year-old graduate student is overseeing the tiny Baltic nation's push to insert artificial intelligence and machine learning into services provided to its 1.3 million citizens. "We want the government to be as lean as possible," says the wiry, bespectacled Velsberg, an Estonian who is writing his PhD thesis at Sweden's Umeå University on how to use AI in government services. Estonia's government hired Velsberg last August to run a new project to introduce AI into various ministries to streamline services offered to residents.
AI has a data quality problem. In a survey of 179 data scientists, over half identified addressing issues related to data quality as the biggest bottleneck in successful AI projects. Big data is so often improperly formatted, lacking metadata, or "dirty," meaning incomplete, incorrect, or inconsistent, that data scientists typically spend 80 percent of their time on cleaning and preparing data to make it usable, leaving them with just 20 percent of their time to focus on actually using data for analysis. This means organizations developing and using AI must devote huge amounts of resources to ensuring they have sufficient amounts of high-quality data so that their AI tools are not useless. As policymakers pursue national strategies to increase their competitiveness in AI, they should recognize that any country that wants to lead in AI must also lead in data quality.
Thinking about the fantastic pie-in-the-sky future is always a fun exercise. I, too, want a self-driving car. But some weeks, it's clear everyone needs to come down to earth. This was one of them. Tesla sued two other electric vehicle companies focusing on self-driving for trade secret theft, proving that building this tech will be a grind.
The patentability of artificial intelligence (AI) has been increasingly scrutinized in light of the surge in AI technology development and the ambiguity regarding the interpretation of software-related patents. The Federal Circuit has gradually refined the criteria for determining subject matter eligibility for software-related patents, and based in part on such jurisprudence, earlier this year the U.S. Patent and Trademark Office (USPTO) released revised guidance on examining patent subject matter eligibility under 35 U.S.C. §101. See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Considering the advances in AI technology and intellectual property law, how do these recent developments shape the outlook of AI patentability?
In a March 21 Slatest, Mark Joseph Stern misstated that the April 2019 Wisconsin Supreme Court election could give Democratic justices a majority. That opportunity will not arise until the 2020 election. Due to an editing error, a March 20 Future Tense Newsletter incorrectly stated that the National Institute of Standards and Technology has been using nonconsensually obtained images to train its Facial Recognition Verification Testing program. The NIST does not develop or train facial recognition systems. It provides independent government evaluations of prototype face recognition technologies.
LIKU baby humanoid robots are demonstrated on the Torooc Inc. stand on the opening day of the MWC Barcelona in Barcelona, Spain, on Monday, Feb. 25, 2019. At the wireless industry's biggest conference, over 100,000 people are set to see the latest innovations in smartphones, artificial intelligence devices and autonomous drones exhibited by more than 2,400 companies. On February 11, 2019, President Trump signed an executive order on Maintaining American Leadership in Artificial Intelligence and in February 2019, a survey by Protiviti called Artificial Intelligence and Machine Learning indicated that only 16% of business leaders surveyed are getting significant value from advanced artificial intelligence (AI) in their companies. The report also found that companies of all sizes and across industries are investing heavily in advanced AI with an average of $36M spent in the fiscal year 2018. Of those same companies surveyed, 10% plan to increase their budgets over the next two years.
I saw "Apollo 11" in the Los Angeles suburb of Alhambra, sitting in an IMAX theatre with ten or so other freelancers and retirees who could see a documentary about NASA in the middle of a Thursday. The director and editor, Todd Douglas Miller, tells the story of the moon launch using archival footage, including a trove of 70-mm. The film has no voice-over narration. Instead its story is relayed by the newscasts of Walter Cronkite and the radio transmissions of Edwin (Buzz) Aldrin, Neil Armstrong, Michael Collins, and their interlocutors on Earth. The result is a visual museum about America in July, 1969, in which Aldrin's famous 16-mm.
Walking around without being constantly identified by AI could soon be a thing of the past, legal experts have warned. The use of facial recognition software could signal the end of civil liberties if the law doesn't change as quickly as advancements in technology, they say. Software already being trialled around the world could soon be adopted by companies and governments to constantly track you wherever you go. Shop owners are already using facial recognition to track shoplifters and could soon be sharing information across a broad network of databases, potentially globally. Previous research has found that the technology isn't always accurate, mistakenly identifying women and individuals with darker shades of skin as the wrong people.
Stanford University launched its Institute for Human-Centered AI on Monday. Known as Stanford HAI, the institute's charter is to develop new technologies while guiding AI's impact on the world, wrestle with ethical questions, and come up with helpful public policies. The Institute intends to raise US $1 billion to put towards this effort. The university kicked off Stanford HAI (pronounced High) with an all-day symposium that laid out some of the issues the institute aims to address while showcasing Stanford's current crop of AI researchers. The most anticipated speaker on the agenda was Microsoft co-founder Bill Gates.