Agriculture, animal health and consumer goods companies face more challenges than ever – feeding the world with less available land in a safe and efficient manner while combating uncertainty over regulatory requirements, grappling with changing consumer demands and driving new innovations to market.
Agriculture entities produce, collect and store an unprecedented amount of increasingly diverse data that could be used to help solve these problems. However, traditional approaches to gleaning insights from data are no longer sufficient, given the volume, velocity and variety of data that modern agriculture businesses must manage. It is becoming increasingly critical for the agriculture industry to find new ways to transform data into useful information.
How AI From SAS Can Help
New AI techniques can automate complex tasks and unlock previously hidden insights across the spectrum of agriculture data. Here are just a few of the ways agriculture organizations are using AI:
- Research and development. Machine learning capabilities, including deep learning, can teach systems to detect outliers in data or match data against known patterns with unprecedented precision and recall, enabling you to innovate faster and more efficiently.
- Faster identification of research data. Applying AI capabilities, such as text analytics and natural language processing, to key terms or research you're working on can greatly reduce or eliminate manual online or paper record sorting.
- Greater efficiency and effectiveness. Using AI to automate repetitive tasks – no matter how complex – can revolutionize efficiency. For example, you could use drone images of crops in a field to calculate farm yield.
- Early detection of pests, disease and weeds. Drone technologies coupled with computer vision capabilities enable fast assessment of field conditions and prioritization of integrated pest management (IPM) strategies.
- Precision agriculture. Data analytics, sensor technologies and the internet of things (IoT), machine learning and cognitive computing can enable agribusinesses to better understand conditions in the field – e.g., soil moisture, light and humidity – in real time.
As the leader in advanced analytics, SAS understands that a carefully designed and well-implemented analytics strategy can help you more efficiently and effectively accomplish your goals. That's why we've embedded AI capabilities into our software – from the powerful SAS® Viya to targeted solutions for agriculture. With an emphasis on greater interpretability and transparency, our AI capabilities enable you to better understand why the algorithms’ outputs are what they are – while automatically identifying, better managing and protecting personal information.
SAS' leadership in advanced analytics, expertise in AI and experience with the agriculture industry can give you THE POWER TO KNOW®.<
- E-Book Making Sense of AI
- White Paper The Evolution of Analytics Opportunities and Challenges for Machine Learning in Business
- White Paper The Next Analytics Age: Machine Learning A Harvard Business Review Insight Center Collection
- White Paper Text Analytics for Executives What Can Text Analytics Do for Your Organization?