Grantees get access to Microsoft Azure cloud computing resources and a variety of data science and machine learning tools, including powerful assets in the the Microsoft Cognitive Toolkit and the GeoAI Data Science Virtual Machine (DSVM). Grantees will receive 12 months of free resources worth $5,000, $10,000, or $15,000, depending on project needs. The Microsoft Azure Research blog explains what, why, and how cloud computing can accelerate your research. You can also stay up to date on advancements through the Microsoft Azure blog. Grantees affiliated with academic institutions, non-profit organizations, and start-up institutions also have the potential to access Esri ArcGIS Pro a next-generation, 64‐bit GIS desktop providing 2D and 3D mapping capabilities in an intuitive user interface.
New technologies are generating far more information than ever before to help scientists assess and predict the health and behavior of species and ecosystems, as well as the threats they face. These include cryptic cameras, acoustic sensors, satellite imagery and citizen science apps. Now, researchers and conservation practitioners analyzing large data sets are exploring artificial intelligence, or AI--the ability of a machine or a computer program to think and learn--to help them process, analyze and interpret data to monitor ecosystems and predict results. Computer systems already exist that can host huge amounts of data, use AI with increasingly "smart" algorithms to classify data from the various types of sensors used by scientists, apply modeling results to create reproducible code, and create user interfaces to allow people to monitor natural systems and make predictions with high accuracy. By training computer algorithms with a subset of available data, machines can now learn what they should do for a given challenge--such as classify photos by the species found in them, identify areas of a satellite image containing water or intact forest, or translate speech from one language to another --based on human feedback and data collected from previous experience.
In the last two decades, the impact of artificial intelligence (AI) has grown from a very small community of data scientists to something that is woven into many people's daily lives. Machine learning, computer vision, and other AI disciplines--supported by the cloud--are helping people achieve more, from mundane tasks, like avoiding a traffic jam, to revolutionary breakthroughs, like curing cancer. Over the past year, Microsoft has been on a journey to apply these transformative technologies to the world's biggest environmental challenges. On July 12, 2017, Microsoft launched AI for Earth as a $2 million program in London, with a goal of providing AI and cloud tools to researchers working on the frontlines of environmental challenges in the areas of agriculture, water, biodiversity, and climate change. Since that time, AI for Earth has grown into a $50 million over five-year program, with 112 grantees in 27 countries and seven featured projects.
Since Microsoft launched its new AI for Earth program in July, we've seen a tremendous response from the global conservation and environmental research community. The program was built on the premise that Microsoft's AI infrastructure and applications can transform how the world monitors and responds to the ever-increasing scale and speed of changes we see in our natural world. Realizing this ambition, though, requires removing some key barriers to adoption that individuals and organizations working on these problems currently face. Today, I'm pleased to announce two important milestones in addressing this issue of access. We've funded $235,000 in Azure compute resources across the four focus areas of our AI for Earth program--agriculture, water, biodiversity and climate change.
Increasingly, it's being applied to conservation; a coalition of researchers earlier this year developed a machine learning algorithm that can identify and describe wildlife. And in a blog post this week, Microsoft highlighted a Santa Cruz-based startup -- Conservation Metrics -- that's leveraging AI to keep tabs on African savanna elephants. Conservation Metrics, a recipient of Microsoft's AI for Earth grant program, is using algorithms to analyze a corpus from Cornell University Lab of Ornithology's Elephant Listening Project, which collects data from acoustic sensors embedded throughout Nouabalé-Ndoki National Park and adjacent logging areas in the Republic of Congo. Its system isolates elephant calls -- the low-frequency rumbling sounds they use to communicate with one another -- from the recordings and derives insights, like population size and herd movement. It's precise enough to identify individual animals that can't be seen from the air, according to Conservation Metrics CEO Matthew McKown.