We are very excited to announce that Digamma.ai was selected to receive Microsoft AI for Earth Innovation Grant to apply Artificial Intelligence to help understand and protect the planet. AI for Earth awards grants to support projects that use AI to change the way people and organizations monitor, model, and manage Earth's natural systems. To date, they have awarded 435 grants to projects with impact in 71 countries. Our team will use the funds to continue and expand their work with U.S. Geological Survey to apply state-of-the-art Machine Learning algorithms towards the study of landslides and other natural hazards. The main objective of the partnership between Digamma.ai and USGS is not only to find the location of the landslides, but to gain a better understanding of the landscape responses to earthquakes and large storms.

Nvidia sales executive Kevin Connors says channel partners play an important role in the chipmaker's strategy for selling and supporting GPU-accelerated solutions for artificial intelligence -- a market that is still in its early stages and can provide the channel major growth opportunities as a result. "People are wanting higher performance computing at supercomputing levels, so that they can solve the world's problems, whether it's discovery of the next genome or better analysis and other such workloads," Connors, Nvidia's vice president of sales, global partners, said in an interview with CRN. The Santa Clara, Calif.-based company's GPUs have become increasingly important in high-performance computing and artificial intelligence workloads, thanks to the parallel computing capabilities offered by their large number of cores and the substantial software ecosystem Nvidia has built around its CUDA platform, also known as Compute Unified Device Architecture, which debuted in 2007. "As a company, we've always been focused on solving tough problems, problems that no one else could solve, and we invested in that. And so when we came out with CUDA -- which allowed application developers to port their high-performance computing apps, their scientific apps, engineering apps to our GPU platform -- that really began the process of developing a very rich ecosystem for high-performance computing," said Connors, who has been with Nvidia since 2006.

"FRONTLINE investigates the promise and perils of artificial intelligence, from fears about work and privacy to rivalry between the U.S. and China. The documentary traces a new industrial revolution that will reshape and disrupt our lives, our jobs and our world, and allow the emergence of the surveillance society." As a business technologist, I am beyond excited about the possibilities of artificial intelligence, machine learning and deep learning ("AI") and all of the application areas already impacted by the technology. The marriage of statistical analyses, adaptive pattern recognition, big data and computational efficiency to describe, explain, predict and actuate events, conditions and processes is thriving. It all came together at roughly the same time.

Albert Einstein's famous expression "spooky action at a distance" refers to quantum entanglement, a phenomenon seen on the most micro of scales. But machine learning seems to grow more mysterious and powerful every day, and scientists don't always understand how it works. The spookiest action yet is a new study of heart patients where a machine-learning algorithm decided who was most likely to die within a year based on echocardiogram (ECG) results, reported by New Scientist. The algorithm performed better than the traditional measures used by cardiologists. The study was done by researchers in Pennsylvania's Geisinger regional healthcare group, a low-cost and not-for-profit provider.

Madabhushi, along with 11 additional winners, will be recognized at the second annual cleveland.com/The HomeGrown Heroes celebrates the unsung heroes of our community who are working tirelessly on their start-ups, businesses, innovations and social organizations to fuel the economic development of our region. See Madabhushi's story in the video feature by John Pana at the top of this post. A Case Western Reserve University biomedical engineering researcher, Madabhushi is making award-winning gains in how artificial intelligence can contribute significantly not only to diagnosing cancer, but also giving physicians personalized guidance on the best treatment options for each patient. His work on how computers can more accurately predict which lung cancer patients would benefit from chemotherapy was named one of the Top 10 medical breakthroughs of 2018 by Prevention.

In some cases, AI-assisted cancer detection might be more than a convenience -- it could be the key to getting a diagnosis in the first place. Microsoft and SRL Diagnostics have developed an AI tool that helps detect cervical cancer, freeing doctors in India and other countries where the sheer volume of patients could prove overwhelming. The team trained an AI to spot signs of the cancer by feeding it "thousands" of annotated cervical smear images to help it spot abnormalities (including pre-cancerous examples) that warrant a closer look. Doctors would only have to look at those slides that justify real concern. A framework for using the AI is now ready for an "internal preview" at SRL.

Which of these levels of personal detail do you feel comfortable sharing with your smartphone? And should every app on that device have the same level of knowledge about your personal details? Welcome to the concept of siloed sharing. If you want to keep relying on your favorite device to store and automatically sort through your data, it's time to start considering whether you want to trust device-, app-, and cloud-level AI services to share access to all of your information, or whether there should be highly differential access levels with silo-class safeguards in place. Your phone already contains far more information about you than you realize. Depending on who makes the phone's operating system and chips, that information might be spread across storage silos -- separate folders and/or "secure enclaves" -- that aren't easily accessible to the network, the operating system, or other apps.

The stunning aerial dance of UFO's that wowed audiences in Steven Speilberg's Close Encounters of the Third Kind has become a reality thanks to the drone. The small aerial vehicles may be a potential threat in some circumstances but they can be beautiful in others. A spectacular aerial art form continues to evolve as operators use lighted drones and computer algorithms to create animations in the sky. Intel's 2018 light show in Sacramento used 1500 drones to put on this stunning display.

Artificial intelligence (AI) and machine learning (ML) technologies, although still relatively new concepts, are garnering a vast amount of interest in international development across sectors and geographies. The U.S. Agency for International Development (USAID)'s Center for Digital Development (CDD)'s Strategy & Research (S&R) team published a report in 2018, "Reflecting the Past, Shaping the Future: Making AI work for International Development", based on extensive research on this rapidly growing field. USAID would like to translate the report's recommendations into an actionable format so the lessons and good practices are accessible to USAID program staff and implementing partners that may have limited familiarity with, nor time, to devote to the topic. Today, the Digital Frontiers team has released a request for proposals (RFP) for qualified firms to work with Digital Frontiers and USAID's S&R team to create a modular, field-ready guidance product that translates findings from the report into concise, practical guidance for USAID staff and partners. Photo courtesy: Save the Children.

Scientists from the School of Energy and Power Engineering, Chongqing University, China, have discovered a highly efficient, time saving as well as a reliable machine learning (ML) method for the research and development of novel organic photovoltaic (OPV) materials. During the development of high performing OPV materials, if one can pre-establish the correlation between the structure of the designed material and its photovoltaic property, it becomes highly meaningful and time saving. The research is reported in the journal Science Advances. OPV cells are an easy and highly economical method for transforming the solar energy into electrical energy. Until now, the typical OPV materials-based research has focused on building a relationship between the newly developed OPV molecular material and its organic photovoltaic material properties.