Three Albuquerque-based companies and New Mexico State University will compete alongside nine out-of-state entities for $50,000 in cash prizes in this year's Hyperspace Challenge. Organizers of the challenge, now in its third year, selected a total of 11 companies and two universities to participate in the 2020 accelerator program, which will focus on developing new, innovative technology to help the U.S. Space Force provide satellites and spacecraft with remote, autonomous ability to manage problems. The Air Force Research Laboratory at Kirtland Air Force Base launched the annual challenge in 2018 in partnership with the ABQid business accelerator run by CNM Ingenuity. The program pairs participating companies with government contractors to resolve critical issues, potentially leading to contracts to build new technology for the U.S. Department of Defense and other federal entities. The last two accelerators in 2018 and 2019 focused, respectively, on data analytics to manage reams of information received from space operations, and new technologies for small satellites.
In recent times, ensemble techniques have become popular among data scientists and enthusiasts. Until now Random Forest and Gradient Boosting algorithms were winning the data science competitions and hackathons, over the period of the last few years XGBoost has been performing better than other algorithms on problems involving structured data. Apart from its performance, XGBoost is also recognized for its speed, accuracy and scale. XGBoost is developed on the framework of Gradient Boosting. Just like other boosting algorithms XGBoost uses decision trees for its ensemble model.
Table recognition is a well-studied problem in document analysis, and many academic and commercial approaches have been developed to recognize tables in several document formats, including plain text, scanned page images, and born-digital, object-based formats such as PDF. There are several works that can convert tables in text-based PDF format into structured representations. However, there is limited work on image-based table content recognition. The proposed challenge aims at assessing the ability of state-of-the-art methods to recognize scientific tables in LaTeX format. Our shared task has two subtasks.
From instantaneous translation to conversational interfaces, artificial-intelligence (AI) technologies are making ever more evident impacts on our lives. This is particularly true in the financial-services sector, where challengers are already launching disruptive AI-powered innovations. To remain competitive, incumbent banks must become "AI first" in vision and execution, and as discussed in our previous article, 1 1. Suparna Biswas, Brant Carson, Violet Chung, Shwaitang Singh, and Renny Thomas, "AI-bank of the future: Can banks meet the AI challenge?," If fully integrated, these capabilities can strengthen engagement significantly, supporting customers' financial activities across diverse online and physical contexts with intelligent, highly personalized solutions delivered through an interface that is intuitive, seamless, and fast.
For global banking, artificial intelligence (AI) could potentially deliver up to US$1 trillion of additional value each year, boosting revenues through increased personalization of services, lowering costs through efficiencies, and uncovering new and previously unrealized opportunities through the use of data, says McKinsey & Company. In a post titled AI-bank of the future: Can banks meet the AI challenge?, McKinsey says that banks have continuously adapted to the latest technology innovations throughout the years, and as the industry heads towards the AI-powered digital age, incumbents must adopt AI at scale and become so-called "AI-first banks." Several trends are accelerating banks' transition towards becoming AI-first, it says, with the first one being customers' rapid adoption of digital banking. COVID-19 has further boosted the adoption of digital banking with use of online and mobile banking channels surging an estimated 20 to 50% in the first few months of the pandemic. The emergence of digital ecosystems and so-called "super apps" is also changing the way consumers discover, evaluate and purchase banking products and services, it says.
As Artificial Intelligence offered its best at the beginning of the pandemic, starting from predicting the outbreak up to monitoring the number of cases, it continues to facilitate all our life aspects for us and our children to be able to work, study, and play safely. Virtual assistants and chatbots have been deployed to support healthcare organisations. The US Center for Disease Control and Prevention and Microsoft have developed a coronavirus self-checker service to help users self-assess COVID-19 and suggest a course of action. AI has been used for checking temperature using; tracking cases and their contacts with facial recognition and smartphones; and tracking the GPS location and itinerary of infected people through mobile phones. You no longer need to physically perform your tasks as AI gives you the ability to control your home or company remotely.
Businesses across the globe are fascinated with the idea of AI and automation because this advanced technology promises operational efficiency, enhanced processes, and substantial cost savings. However, AI and its allied technologies have also created uncertainties, confusion, and doubts about the human capability for adopting, deploying, and executing these magical systems in actual business situations -- simply because the business leaders and operators are still all humans. Today, it is widely acknowledged that automation and AI technologies will gradually transform the global workplace, with intelligent machines performing human tasks in some cases and aiding the human in other cases. The presence of robotic machines in the workplace will ultimately increase efficiency and reduce costs. As a result, many human occupations will disappear, while others will adapt to technology-enabled roles.
Smarter Patterns is an interaction pattern library that provides solutions for common AI challenges. Born out of extensive research into how artificial intelligence is being used and understood today, it is an evolving resource that considers the form and function of the patterns as well as the ethical challenges AI poses. Without a clear concept of what it actually is, AI can be confusing and scary to users. How can we help them understand what the AI is being used for, how it's being leveraged in their applications, and why it should matter to them? Users don't necessarily want to use AI all the time.
Imagine a sprint-like event, where anybody, right from the industry's who's who to a novice college graduate working in collaboration with their respective teams to create a functioning solution for the problem at hand. Hackathons are truly such electric events that form the breeding ground for such brilliant tech solutions. It also sometimes prove to be a great way to hire professionals who have the perfect mix of data science knowledge and programming skills for companies working in the areas of machine learning, artificial intelligence, and data science. The popularity of hackathons has only grown over the years. As per a survey, 32% of respondents said that hackathons are an excellent medium for learning and upskilling.
Riiid, a leader in AI education solutions, just launched a challenge via Kaggle to use the largest educational dataset to build innovative algorithms that track knowledge states of 780K students. The goal is to accurately predict how students will perform on future interactions. If successful, it's possible that any student with an Internet connection can enjoy the benefits of a personalized learning experience, regardless of where they live. With your participation, we can build a better and more equitable model for education in a post-COVID-19 world. The 100K prize competition will run from October 5 to January 2021 and the winning models will have a chance to present at AAAI 2021.