Boston Dynamics' Spot robot is expanding to its resume every day, and the quadruped can add nuclear power plant exploration and radiation monitoring to the list. Engineers from the University of Bristol recently tested Spot around the Exclusion Zone territory of the Chernobyl Nuclear Power Plant. The Exclusion Zone covers approximately a 1,000-square-mile area in Ukraine surrounding the Chernobyl Nuclear Power Plant, where radioactive contamination is highest and public access and inhabitation are restricted. According to the State Agency for Exclusion Zone Management, this is the first time Spot has been tested there. Spot helped create a 3D map of the distribution of nuclear radiation around the Chernobyl Nuclear Plant.
Our team is officially announcing the launch of a new 3.0 version of Catchar with a marketplace module. We found that some creators use Sketchfab, Gumroad and Etsy to sell and monetize their AR/MR assets. However, creators from CIS, Georgia, Ukraine, Asia and some other countries are limited in payouts from these services. We released a marketplace and asset store where Augmented Reality creators and Machine Learning engineers can list for sale their templates, source code, 3D models and tutorials. Our system provides direct profit payouts through SWIFT and SEPA.
"Machine learning is to businesses today what petrol engines were to horses back then." For this week's ML practitioner's series, Analytics India Magazine got in touch with Eugene Khvedchenya from Ukraine. Eugene is a Kaggle master and is currently ranked 104 on the global leaderboard. He has more than 10 years of experience in developing computer vision applications, and in this interview, he shared few valuable insights from his decade long journey. Eugene started programming from a young age ever since he saw his father assembling Orion 128 PC, a popular DIY PC in the early 90s.
Arkieva, Inc., a leading designer, and provider of the Arkieva suite of Advanced Planning and Scheduling (APS) software tools for manufacturing companies today announced the launch of their new machine learning forecasting and ROI tool, Swifcast. Swifcast is the only app that allows users to load historical supply chain data and get both an actionable demand forecast and an ROI to prove the business case for transforming an organization's approach to predicting future demand. Swifcast intends to help supply chain practitioners and the corner office better understand the intersection of technology and financial results, alleviating concerns over making changes to business process without a firm feel for the outcome. "We have had hundreds of conversations with customers and prospects over how to prove ROI and how generic some underlying assumptions are," says Ernie Untereiner, Arkieva's Director of Sales and Marketing, "We set out to build a tool that would use the client's historical data to provide a personalized ROI and forecast. Our goal is to empower planners to have the data points that they need to create business case justification for management to invest in the organization's planning future."
"Whenever you compete, you have to accept simple rules – someone wins, someone loses, and usually the winner takes it all." For this week's ML practitioner's series, Analytics India Magazine got in touch with Oleg Yaroshevskiy from Ukraine. In this interview, he shares his experiences from his journey to the top 20 in one of the toughest data science competitions in the world. Oleg majored in maths and statistics from Cybernetics Faculty of Taras Shevchenko National University of Kyiv, which was co-founded by Victor Glushkov, one of the cybernetics pioneers who played a key role in the advancement of theoretical computer science, including artificial intelligence. Oleg had a formal introduction to machine learning (ML) during his graduation days where he had studied neural networks along with the popular Andrew NG's course on Coursera back in 2013.
Rapidly expanding market of chatbot solutions drives many businesses to discovery of value, benefits and competitive advantages of chatbots. In this situation companies that are planning to add a chatbot to their IT infrastructure are often not familiar with the principles and components of chatbots and so decision makers are in situation that they have to define business strategies without sufficient knowledge about chatbot ecosystem. In this article we will try to clarify these aspects and describe value and impact of each component based on our experience of building chatbots. First of all, we would like to mention that many people (even skilled and experienced in business process management) have too simplistic vision about chatbots. There are dozens of "do-it-yourself" kits on the market, but building your own solution (dedicated to needs of particular business model) without proper understanding of the whole "chatbot universe" could end with disappointment of business and customer frustration (and what is even worse – loss of trust to your chatbot).
Kremlin analysts could have used Twitter as a source of military intelligence to inform their actions in the 2014 Russia–Ukraine conflict, a study has found. University of California experts showed that location-tagged tweets by Ukraine residents could have been used to map out sentiments towards Russia in real-time. The map they made of pro-Kremlin regions turned out to bear a striking resemblance to the actual areas to which Russia dispatched its special forces. Specifically, this included Crimea and regions in the far east of Ukraine -- where the incoming forces would have been most likely to be seen as liberators. In contrast, the data could also reveal those areas where dispatching forces would have lead to greater resistance and corresponding casualties and costs.
During the 13 years he spent in banking, Tomasz Borowski's career spanned operations, risk management, and product management, where he also witnessed the brutality and unprofessional methods that conventional debt collection agencies adopted to retrieve outstanding balances. He observed the same thing when he moved to Ukraine in 2005 to continue his banking career. He did his own research on alternative methods and came to know about two digital debt collection companies--US-based TrueAccord and Polish debt collection agency Kruk SA--both worth over a billion US dollars today. "I decided to move to Southeast Asia and began exploring the market here. It was obvious to me that the situation here was similar to Ukraine. I decided to utilize my experience in finance and create a professional credit management services company to help change this market," Borowski told KrASIA.
Continuing its acquisition spree, Snapchat's parent company Snap has now bought AI Factory, a Ukrainian computer vision and AI-based startup that earlier collaborated with them to build Snapchat's new Cameos animated selfie-based video feature. According to reports, it would cost Snap $166 million to acquire AI Factory. It had earlier spent $150 million on another Ukraine based startup Looksery in 2015 to power its augmented reality lenses-- and shook up the lens filters game for all social video and photo apps. Lenses became a mega success for Snap where it was reported that 70% of its daily active users play with them, which not just brings in new users, but also increases user retention and revenues by way of sponsorships and the purchase of the devices by users. Founded in 2018, AI Factory has been developing innovative computer vision and augmented reality products with a focus on image and video technologies, analysis and processing.
Artificial intelligence (AI) is now receiving unprecedented global attention as it finds widespread practical application in multiple spheres of activity. But what are the human rights, social justice and development implications of AI when used in areas such as health, education and social services, or in building "smart cities"? How does algorithmic decision making impact on marginalised people and the poor? This edition of Global Information Society Watch (GISWatch) provides a perspective from the global South on the application of AI to our everyday lives. It includes 40 country reports from countries as diverse as Benin, Argentina, India, Russia and Ukraine, as well as three regional reports.