The Girls of Steel, FIRST Robotics Competition Team 3504, founded in 2010 at Carnegie Mellon's Field Robotics Center, has a team mission to empower everyone, especially women and girls, to believe they are capable of success in STEM. The principles of our team include: teamwork, communication, respect, integrity, inclusion, and safety. We teach mechanical and technical skills, programming and analytical thinking, as well as leadership, teamwork, and business skills. We also value a commitment to quality, ethical behavior, and respect for others. Through outreach we aim to educate young people in STEM using hands-on design and development of a robot.
The digital bank founded by Prof. Amnon Shashua, among the founders of the self-driving auto-tech company Mobileye, officially began operations on Sunday, promising to shake up the Israeli banking sector and inject badly needed competition. First Digital Bank, Israel's first new banking institution in 43 years, aims to use artificial intelligence and other technology to create a personal ambiance without the actual human contact that comes with neighborhood branches. "Netflix killed off Blockbuster, Spotify disrupted the music industry and Tesla has left Ford and Mitsubishi in the dust. Banking is one of the few industries that hasn't undergone a revolution. Big, long-standing names control the market with too little competition and offer exactly the same products," said First Digital Bank's CEO, Gal Bar-Dea.
In an effort to address mounting concerns about algorithmic harms, Twitter has announced a new initiative that will subject some of the company's machine-learning systems to more scrutiny and pave the way for changes to any problematic AI models. Dubbed'Responsible ML', the initiative is designed not only to increase the transparency of the AI systems used by Twitter, but also to improve the fairness of the algorithms, and to provide users with "algorithmic choice" when it comes to the technologies that might affect them. Twitter has pledged to take responsibility for the platform's algorithmic decisions, and has appointed a Responsible ML working group to lead the initiative. This group, whose members are drawn from across the company, will be managed by Twitter's existing ML Ethics, Transparency and Accountability (META) team. With almost 200 million people using Twitter daily, the platform relies on machine-learning models for a many tasks, ranging from organizing content by relevance to identifying posts that violate terms of service.
Nasa's InSight Mars lander is currently trying to endure the abrasive Martian environment, as it sits on the Red Planet conserving power as its solar panels get covered in dust. InSight was designed to be powered by solar energy, gathered through dual two-meter panels. It was always expected that the panels would reduce their power output as time went on and dust landed on them, but would still have enough to last throughout the two-year mission. Unfortunately, not all has gone to plan. Despite InSight landing in Elysium Planitia, a windswept area of Mars that gets lots of sunlight, none of the passing dust devils (funnel-like chimneys of hot air) have been close enough to clean the panels.
Facebook is testing a new video speed dating app called Sparked which emphasises'kindness' and a'positive dating experience' between users. Developed by the social media giant's New Product Experimentation (NPE) team, the app requires users to have a Facebook profile, The Verge reported. The app requires users to type out what makes them a kind dater when signing up, and these responses will reportedly be "reviewed by a human at Sparked" before people can go on the video dates. The social media giant noted that Sparked would not contain any public profiles, or swiping, or DMs, and is likely to be free to use. Users also have to choose whether they want to date men, women, or nonbinary people, according to The Verge which reportedly accessed the app's website.
This work exploits a large source domain for pretraining and transfer the diversity information from source to target. Highlights: Anchor-based strategy for realism over regions in latent space A novel cross-domain distance consistency loss Existing models can be leveraged to model new distributions with less data Extensive results demonstrates qualitatively and quantitatively that this few-shot model automatically discovers correspondences between source and target domains and generates more diverse and realistic images than previous methods.
AI technology used to be limited to advanced research teams. It is now a key capability for many businesses to improve sales and product quality, provide deep personalisation and new interfaces, and to improve safety and reduce risk. AI is materially changing how we interact with and benefit from technology. Having ready access to and consistent operational control over AI infrastructure is a game changer that democratizes AI for enterprises and opens access to many new use cases.
Ireland's Data Protection Commission (DPC) is investigating the recent leak of a Facebook user dataset that dates back to 2019. At the start of April, it came out that someone on a hacking forum had made the dataset public, exposing the personal information of about 533 million Facebook users in 106 countries. Depending on the account, there are details about phone numbers, birth dates, email addresses, locations and more. The source of the leak is an oversight Facebook fixed in August 2019. "The DPC, having considered the information provided by Facebook Ireland regarding this matter to date, is of the opinion that one or more provisions of the GDPR and/or the Data Protection Act 2018 may have been, and/or are being, infringed in relation to Facebook Users' personal data," the agency said in a statement spotted by TechCrunch.
Companies form HR departments to handle hiring and compensation. Soon, HR leaders find themselves tackling, retention, performance management, culture and a myriad of other responsibilities. And now CEOs are asking them: What's your AI strategy? The short answer is: AI will transform HR creating a lean department that is less intrusive yet more impactful. Software has eaten the world and now AI is eating software.
It's highly unlikely that business owners are going to read this and begin to change their perspectives on how we define Data Science. Not because I doubt my influence or anything, but since I'm aware that the majority of my readers are at the beginning of their Data Science journey -- I really dislike the term "aspiring" -- but here is what I wish to tell you all… Stop trying to be good at everything in Data Science, and pick 1 (max 2) area's you want to specialize in and get really good at it! Let's face it... Breaking into Data Science is difficult for a number of reasons. However, I've come to a realization recently that much of the difficulty lies in the fact that the term "Data Scientist" encompasses so many different technical qualities that make it virtually impossible for one individual to meet all these criteria and stay up to date in each area -- and that's okay! I've been listening and speaking to Vin Vashishta, Chief Data Scientist and LinkedIn Top Voice 2019, and he believes that for roles to be defined better then more specialization amongst practitioners must occur.