Artificial intelligence (AI) is creeping into our everyday lives, often without us realizing it. Today, AI can be found in the digital assistants we use such as Apple's (NASDAQ:AAPL) Siri and Amazon's (NASDAQ:AMZN) Alexa to check our schedules and search for things on the internet; in the cars we own that now park themselves as they are able to recognize space around the vehicle; and in the small robots we use to clean our houses, such as the Roomba vacuum. Artificial intelligence is becoming more a part of our lives all the time, and will only grow in importance in coming years. In the not too distant future, AI will influence everything from how we shop for groceries to how diseases are diagnosed and treated by doctors. It all adds up to a fast growing market.
HitchBot, a friendly-looking talking robot with a bucket for a body and pool-noodle limbs, first arrived on American soil back in 2015. This "hitchhiking" robot was an experiment by a pair of Canadian researchers who wanted to investigate people's trust in, and attitude towards, technology. The researchers wanted to see "whether a robot could hitchhike across the country, relying only on the goodwill and help of strangers." With rudimentary computer vision and a limited vocabulary but no independent means of locomotion, HitchBot was fully dependent on the participation of willing passers-by to get from place to place. Fresh off its successful journey across Canada, where it also picked up a fervent social media following, HitchBot was dropped off in Massachusetts and struck out towards California. But HitchBot never made it to the Golden State.
Set the first and last books in Cory Doctorow's epic, three-book Little Brother cypherpunk saga side-by-side, and they read a bit like a creative writing master class on telling two starkly opposite stories from the same prompt. The Department of Homeland responds by turning San Francisco into a fascist, total-surveillance police state. The protagonist, a digitally gifted, troublemaking teen, must decide how to respond. In the first Little Brother installment, which Doctorow published in 2008, the answer seemed righteously inevitable: The hero uses his hacker skills to fight back. Specifically, he and his plucky hacker friends figure out how to jailbreak their Xboxes and channel the video game consoles' encrypted comms over the Tor network to create Xnet, a cheap, anonymous, surveillance-proof system for organizing protest and foiling the panopticon cops by injecting false data into their totalitarian schemes. In Doctorow's third work in the series, publishing this week and titled Attack Surface, the protagonist takes an altogether different path.
After a rocky, unpredictable season, the San Francisco Shock defeated the Seoul Dynasty, 4-2, to secure their place as Overwatch League's first back-to-back world champions. Seoul came from behind on Saturday, cutting through skepticism and pushing the series to six maps, with a series of clutch plays by Junyoung "Profit" Park, who won the 2018 Overwatch Grand Finals with the London Spitfire.
RoboCup-97, The First Robot World Cup Soccer Games and Conferences, was held at the Fifteenth International Joint Conference on Artificial Intelligence. There were two leagues: (1) real robot and (2) simulation. Ten teams participated in the real-robot league and 29 teams in the simulation league. Over 150 researchers attended the technical workshop. The world champions are CMUNITED (Carnegie Mellon University) for the small-size league, DREAMTEAM (University of Southern California) and TRACKIES (Osaka University, Japan) for the middle-size league, and AT-HUMBOLDT (Humboldt University) for the simulation league.
The Workshop Program of the Association for the Advancement of Artificial Intelligence's Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16) was held at the beginning of the conference, February 12-13, 2016. Workshop participants met and discussed issues with a selected focus -- providing an informal setting for active exchange among researchers, developers and users on topics of current interest. To foster interaction and exchange of ideas, the workshops were kept small, with 25-65 participants. Attendance was sometimes limited to active participants only, but most workshops also allowed general registration by other interested individuals. The AAAI-16 Workshops were an excellent forum for exploring emerging approaches and task areas, for bridging the gaps between AI and other fields or between subfields of AI, for elucidating the results of exploratory research, or for critiquing existing approaches.
When Alex Handy first founded the Museum of Arts and Digital Entertainment (or the MADE) in Oakland, Calif. in 2011, he imagined the institution as a bucket placed underneath an industry that was constantly leaking and dripping out vital artifacts of its own history. Over the museum's near-decade of existence, it has weathered rising rents, flooding, and even robberies to deliver a playable library of more than 10,000 games to its visitors. However, more than six months after the ongoing coronavirus crisis forced its closure, it's not at all clear if the MADE -- or its fellow video game museums across the globe -- will be able to survive the economic fallout wrought by the virus. And given the interactive nature of video games, it's clear that these museums will have an even tougher time mitigating the risk of transmission once they open back up.
The iTunes big data engineering team is looking for talented server-side engineers to build and enhance social features such as those underpinning Apple Music. This is your opportunity to contribute to key Apple services built using massively scaled systems, on a team located in San Francisco and working closely with Cupertino and London. Key Qualifications Minimum of 5 years professional software engineering experience. Proficiency in building Node.js applications. Experience with building RESTful APIs. Experience with a NoSQL solution, document store, or key-value store (e.g. Cassandra, Redis, MongoDB, Couchbase). Comfortable with Linux command line tools and basic shell scripting. Description Our team is responsible for architecting and delivering services such as those central to Apple Music Connect that allow users and artists to interact with each other. To build these features, we create server-side applications that employ a combination of microservices, message-passing, caching layers, and distributed databases. We serve our data over cleanly designed RESTful HTTP endpoints used by multiple client platforms making a massive number of requests per second at millisecond response times. This is a great opportunity to join a small but growing team of motivated engineers, with wide responsibility and high-profile feature ownership. Whether you’re interested in architecture, data modeling, plumbing data pipelines, or designing endpoints, there are numerous possibilities for building new features from scratch and enhancing the existing infrastructure. Education Education: BS or MS in Computer Science, or equivalent experience Additional Requirements Experience with building highly scalable services using a microservices architecture. Experience with message-based architectures using Kafka or other another message broker. Experience with Agile software development methodologies including Scrum and TDD (test-driven development). Ability to collaborate with cross-functional teams. Familiarity or experience with Java or another object-oriented programming language. Experience with Git.
Hardware, systems and algorithms research communities have historically had different incentive structures and fluctuating motivation to engage with each other explicitly. This historical treatment is odd given that hardware and software have frequently determined which research ideas succeed (and fail). This essay introduces the term hardware lottery to describe when a research idea wins because it is suited to the available software and hardware and not because the idea is superior to alternative research directions. Examples from early computer science history illustrate how hardware lotteries can delay research progress by casting successful ideas as failures. These lessons are particularly salient given the advent of domain specialized hardware which make it increasingly costly to stray off of the beaten path of research ideas. This essay posits that the gains from progress in computing are likely to become even more uneven, with certain research directions moving into the fast-lane while progress on others is further obstructed.
In this tutorial, you will create an automatic Sudoku puzzle solver using OpenCV, Deep Learning, and Optical Character Recognition (OCR). My wife is a huge Sudoku nerd. Every time we travel, whether it be a 45-minute flight from Philadelphia to Albany or a 6-hour transcontinental flight to California, she always has a Sudoku puzzle with her. The funny thing is, she prefers the printed Sudoku puzzle books. She hates the digital/smartphone app versions and refuses to play them. I'm not a big puzzle person myself, but one time, we were sitting on a flight, and I asked: How do you know if you solved the puzzle correctly?