Seattle's financial future is brighter than originally predicted, having taken a positive turn over the last five months according to a new budget forecast. Rantz: Sword, meth, trash remain as School Board refuses to sweep tents 44 minutes ago Sound Transit's dilemma: What to delay, cut, or scale with $11.5 billion hole 23 minutes ago Wyman: New voting law would'force us to make changes' in Washington 40 minutes ago Ross: Artificial intelligence is coming, like it or not 12 minutes ago Over 19,000 complaints against SPD from 2020 COVID updates: King County launches in-home vaccination program 25 minutes ago Sound Transit's dilemma: What to delay, cut, or scale with $11.5 billion hole 23 minutes ago Wyman: New voting law would'force us to make changes' in Washington 40 minutes ago What Aldon Smith's charge could mean for his Seahawks future Auburn considers tightening rules for homeless camping Six Seattle mayoral candidates lead the fundraising race What Aldon Smith's charge could mean for his Seahawks future What Aldon Smith's charge could mean for his Seahawks future Dave Ross Ross: Artificial intelligence is coming for cars, like it or not Artificial intelligence is coming, like it or not. Cornell philosophy professor Shaun Nichols even predicts you'll be able to select your driving algorithm. Chokepoints Sound Transit's dilemma: What to delay, cut, or scale with $11.5 billion hole With an $11.5 billion budget hole, the Sound Transit board has to make tough choices of cutting projects, delaying projects, and ways to make up the gap. Jason Rantz Rantz: Sword, meth, and trash remain as School Board refuses to sweep encampment A growing encampment that threatens student and staff safety at Seattle's Broadview-Thompson K-8 remains in place.
A small helicopter opened a new chapter of space exploration this morning when it lifted off the surface of Mars, marking humankind's first powered flight on another planet. The 19-inch-tall chopper called Ingenuity kicked up a little rusty red dust as it lifted about 10 feet off the ground, hovered in place, turned slightly, and slowly touched back down. The flight lasted only about 40 seconds, but it represents one of history's most audacious engineering feats. "A lot of people thought it was not possible to fly at Mars," says MiMi Aung, the project manager of Ingenuity at NASA's Jet Propulsion Laboratory (JPL). "There is so little air."
The European Commission will this week present its proposal on Artificial Intelligence (AI), seen as a step toward a new regulatory framework, promised by Commission President Ursula von der Leyen in her State of the Union, writes Marie-Françoise Gondard-Argenti. Marie-Françoise Gondard-Argenti is a member of the Employers' Group at the European Economic and Social Committee. It is clear that there is no country or company manager in Europe at the moment that does not support the development of a trustworthy and innovative AI ecosystem, which promotes a human-centric approach and that primarily services people, increasing their well-being. There is no company in Europe that does not understand the need to leverage the EU market to spread the EU's approach to AI regulation globally. However, at the moment, the EU lags behind.
Spoken dialogue is the most natural way for people to interact with complex autonomous agents such as robots. Future Army operational environments will require technology that allows artificial intelligent agents to understand and carry out commands and interact with them as teammates. Researchers from the U.S. Army Combat Capabilities Development Command, known as DEVCOM, Army Research Laboratory and the University of Southern California's Institute for Creative Technologies, a Department of Defense-sponsored University Affiliated Research Center, created an approach to flexibly interpret and respond to Soldier intent derived from spoken dialogue with autonomous systems. This technology is currently the primary component for dialogue processing for the lab's Joint Understanding and Dialogue Interface, or JUDI, system, a prototype that enables bi-directional conversational interactions between Soldiers and autonomous systems. "We employed a statistical classification technique for enabling conversational AI using state-of-the-art natural language understanding and dialogue management technologies," said Army researcher Dr. Felix Gervits. "The statistical language classifier enables autonomous systems to interpret the intent of a Soldier by recognizing the purpose of the communication and performing actions to realize the underlying intent."
Stepping out in public used to make a person largely anonymous. Unless you met someone you knew, nobody would know your identity. Cheap and widely available face recognition software means that's no longer true in some parts of the world. Police in China run face algorithms on public security cameras in real time, providing notifications whenever a person of interest walks by. China provides an extreme example of the possibilities stemming from recent improvements in face recognition technology.
As an archivist, I'm excited about what disruptive innovations like non-fungible tokens (NFTs) and artificial intelligence may mean for archives. These developments pose existential threats to our field, and by extension, to the survival of human history and culture. I give old films away for free. It started in 1999 when I was seduced by the promise, excitement, and just-felt-rightness of the gift economy. Not 30 seconds after we first met, Internet Archive founder Brewster Kahle asked me, "Want to put your film archives online for free?"
Scientists have developed a new machine learning tool that can identify Covid-19-related conspiracy theories on social media and predict how they evolved over time, an advance which may lead to better ways for public health officials to fight misinformation online. The study, published in the Journal of Medical Internet Research, analysed anonymised Twitter data to characterise four Covid-19 conspiracy theory themes – such as one that erroneously claims the Bill and Melinda Gates Foundation engineered or has malicious intent related to the pandemic. Using the AI tool's analysis of more than 1.8 million tweets that contained Covid-19 keywords, the scientists from the Los Alamos National Laboratory in the US categorised the posts as misinformation or not, and provided context for each of these conspiracy theories through the first five months of the pandemic. "From this body of data, we identified subsets that matched the four conspiracy theories using pattern filtering, and hand labeled several hundred tweets in each conspiracy theory category to construct training sets," explained Dax Gerts, a computer scientist and co-author of the study from the Los Alamos National Laboratory. The four major themes examined in the study were that 5G cell towers spread the virus; that the Bill and Melinda Gates Foundation engineered or have "malicious intent" related to Covid-19; that the novel coronavirus was bioengineered or was developed in a laboratory; and that vaccines for Covid-19, which were still in development during the study period, would be dangerous.
Hosted by Dylan Doyle-Burke and Jessie J Smith, Radical AI is a podcast featuring the voices of the future in the field of artificial intelligence ethics. In this episode Jess and Dylan chat to Kate Crawford about the Atlas of AI. What is the Atlas of AI? How is AI an industry of extraction? How is AI impacting the planet? To answer these questions and more we welcome to the show Dr Kate Crawford to discuss Kate's new book Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence.
Google is putting a bunch of iconic Japanese characters in Search as augmented reality objects you can interact with. The tech giant is giving you the chance to bring 14 familiar characters from anime, video games and TV shows into your environment, including Pac-Man and Hello Kitty. Apparently, Pac-Man remains the most-searched animated icon on Google, especially (for some reason) in Peru. Its worldwide search interest more than doubles the second-most searched character, Hello Kitty. Aside from those two, you'll also be able to summon Ultraman, Evangelion and Gundam robots, as well as Little Twin Stars characters into your space.
Machine learning, artificial intelligence, and other modern statistical methods are providing new opportunities to operationalise previously untapped and rapidly growing sources of data for patient benefit. Despite much promising research currently being undertaken, particularly in imaging, the literature as a whole lacks transparency, clear reporting to facilitate replicability, exploration for potential ethical concerns, and clear demonstrations of effectiveness. Among the many reasons why these problems exist, one of the most important (for which we provide a preliminary solution here) is the current lack of best practice guidance specific to machine learning and artificial intelligence. However, we believe that interdisciplinary groups pursuing research and impact projects involving machine learning and artificial intelligence for health would benefit from explicitly addressing a series of questions concerning transparency, reproducibility, ethics, and effectiveness (TREE). The 20 critical questions proposed here provide a framework for research groups to inform the design, conduct, and reporting; for editors and peer reviewers to evaluate contributions to the literature; and for patients, clinicians and policy makers to critically appraise where new findings may deliver patient benefit. Machine learning (ML), artificial intelligence (AI), and other modern statistical methods are providing new opportunities to operationalise previously untapped and rapidly growing sources of data for patient benefit. The potential uses include improving diagnostic accuracy,1 more reliably predicting prognosis,2 targeting treatments,3 and increasing the operational efficiency of health systems.4 Examples of potentially disruptive technology with early promise include image based diagnostic applications of ML/AI, which have shown the most early clinical promise (eg, deep learning based algorithms improving accuracy in diagnosing retinal pathology compared with that of specialist physicians5), or natural language processing used as a tool to extract information from structured and unstructured (that is, free) text embedded in electronic health records.2 Although we are only just …