Legal Knowledge Management and the Rise of Artificial Intelligence
Robotic Refactoring the Workplace
Why Your Next Insurance Claims Processor Could be a Robot
The Forgotten Element in Your Big Data Strategy
"AI -The Future of Automotive Industry"
Nitin Sethi, Global IT Director - Business Transformation & Engagement, Visteon Corporation
WiFi Networks: Shifting from Providing a Service to Improving the...
Daniel J. Strojny, Interim Associate Director of Network and IT Operations, University of St. Thomas
Breaking the Stereotypes in the Development of AI
Yves Jacquier, Executive Director, Production Studio Services, Ubisoft
Operationalize Machine Learning
Zongjie Diao, Director of Product Strategy and Management, Data Center Compute Group, CISCO
Thank you for Subscribing to CIO Applications Weekly Brief
Know your Weather with AI Now
The massive amounts of data sets the stage for technologies like artificial intelligence (AI) and machine learning (ML) to contribute significantly toward accurate weather forecasts.
FREMONT, CA: “Want to know the weather? Look out of the window.” While the statement may be on a lighter note, it hasn’t failed to demonstrate the attitude of the people toward the weather forecasting teams. However, most of the people are unaware of how complex and often challenging are the skills involved in forecasting, which requires processing and observing vast amounts of data.
Identifying patterns in the assimilated data is a strenuous task. For maximum accuracy, the process needs to be carried out in real-time where a little discrepancy can severely impact the predictions carried out for an extended period such as a month or two. Meteorologists employ several methods and tools for prediction such as weather balloons and satellites like the Joint Polar Satellite System (JPSS) and Deep Space Climate Observatory (DSCOVR). In combination, such equipment generates massive amounts of data that sets the stage for technologies like artificial intelligence (AI) and machine learning (ML) to contribute significantly toward accurate forecasts.
AI Facilitating Forecasts
Predicting future gets an uphill task despite the availability of enormous data sets. Conventional computer models make judgments over large-scale phenomena like pressure differences effect on wind patterns and heating up of the earth’s surface due to solar radiations.
AI can help to improve the efficiency of the weather forecasting by leveraging vast data sets and computational problem-solving methods. Understanding the inherent complexity in weather prediction, scientists are using AI for accurate and refined results. With the help of deep learning capabilities, AI can learn from past weather records and result in relatively better forecasts. For instance, the Numerical Weather Prediction (NWP) model analyzes data sets from sensors and satellites to supply short term weather forecasts and extended period of climatic predictions too. Companies are currently investing heavily in AI-based weather prediction models.
With further advancements in AI technologies will help the companies to develop weather models with data sets from across the world which can not only improve weather forecasts but also help the research teams to unravel the complexities involved in weather forecasting.