|Veritone reported that 54% of business executives who have implemented AI solutions or applications stated that productivity in the companies has increased / Photo by: alexandersikov via 123RF|
The business community is growing more comfortable with and optimistic about artificial intelligence. Veritone, a developer of an AI platform that comprehends and transforms multiple forms of data to create actionable intelligence, reported that 54% of business executives who have implemented AI solutions or applications stated that productivity in the companies has increased. This comes as no surprise since AI has the power to reduce workloads and enable workers to work better and focus on more strategic tasks.
It was reported that 61% of business executives with an innovation strategy stated that AI helps them in identifying otherwise missed opportunities in data. Workers can also focus more on contextualizing and applying data strategically by leveraging AI to quickly identify data opportunities. With the increasing adoption of AI, it is predicted that 75% of commercial enterprise applications will use AI by 2021. At the same time, 72% of leaders from the technology, media, and telecommunications industry think their product offerings will be impacted significantly by AI in the next five years.
While it is feared that AI can replace humans at their jobs, recent reports show that it can open more job opportunities for us. About 80% of tech and business leaders believe that AI creates jobs and improves worker efficiency. This is because efficiency gains that AI has made possible create more opportunities to be creative and spearhead new projects that require more jobs. However, reports still show that some leaders are still having a hard time integrating AI initiatives with existing processes and systems.
AI in Weather Forecasting
One of the many things that AI can greatly improve on is weather forecasting. Weather forecasting is a complex and often challenging skill involving observing and processing vast amounts of data. These data consist of the current state of the atmosphere, particularly the temperature, humidity, and wind. One must have an intensive understanding of atmospheric processes to determine how the atmosphere evolves in the future.
Trained observers or automatic weather stations are tasked to collect atmospheric pressure, temperature, wind speed, wind direction, humidity, and precipitation for weather forecasts. The information gained during the data assimilation process is used in conjunction with a numerical model's most recent forecast. While this sounds easy to do, weather forecasting is a daunting job. The chaotic nature of the atmosphere and incomplete understanding of the processes mean that forecasts become less accurate. This explains why sometimes weather forecasts for the day usually don’t happen.
However, the huge amounts of datasets of the Earth’s atmosphere make predicting future weather events very tricky. At the same time, a single error that develops in a forecast will rapidly grow and cause further errors on a larger scale. This is where AI comes in. The researchers from the US National Oceanic and Atmospheric Administration (NOAA) discovered that AI techniques can significantly improve the prediction skill for multiple types of high-impact weather such as severe thunderstorms, tornadoes, and hurricanes.
“AI methods extend easily to directly predicting impacts of high-impact weather, such as power generated by variable sources such as solar or wind, energy consumption in an area, or airport arrival capacity,” the authors said.
According to Interesting Engineering, a cutting edge, leading community designed for all lovers of engineering, technology, and science, AI can be employed to improve the accuracy and reliability of weather forecasting. The technology can also be used in identifying patterns and making a relevant hypothesis with the help of computer-generated mathematical programs and computational problem-solving methods.
|Weather forecasting is a complex and often challenging skill involving observing and processing vast amounts of data. These data consist of the current state of the atmosphere, particularly the temperature, humidity, and wind / Photo by: Umberto Leporini via 123RF|
New AI Tool to Improve Weather Forecasts
Today, many tech companies are developing AI systems to help authorities with weather forecasting. Recently, Google introduced a new AI tool that would enable speedy local weather predictions using satellite images, with no lag. Jason Hickey, Senior Software Engineer of Google Research, and his team presented their study of developing machine learning models for forecasting precipitation. This tool was designed to address the challenge of making accurate weather predictions by making highly localized physics-free predictions.
According to The Verge, an American technology news and media network that publishes news items, long-form feature stories, guidebooks, product reviews, and podcasts, Google’s approach offers more speed compared to traditional forecasting techniques. Currently, forecasters are using two existing methods: simulation forecasting, which creates detailed physics-based simulations of weather systems, and optical flow (OF) predictions, which look at the motion of phenomena like clouds.
However, these older methods are computationally intensive, which take hours to run on expensive supercomputers. “If it takes 6 hours to compute a forecast, that allows only 3-4 runs per day and resulting in forecasts based on 6+ hour old data, which limits our knowledge of what is happening right now,” Hickey said.
On the other hand, Google’s new AI tool enables “nearly instantaneous” weather forecasts, which can produce results in minutes since it makes predictions about simple radar data instead of trying to model complex weather systems. To train the model, the researchers used historical radar data collected between 2017 and 2019 from NOAA. The model was also trained through the convolution neural network (CNN) ‘U-Net’, which takes the input satellite imagery and then transforms them into output images.
According to the team, the new method is much better compared to the existing methods for weather forecasting. It can even create forecasts for up to 10 days in advance.
Hickey added that this new model is computationally cheaper, allowing high-resolution weather forecasting, almost instantaneously. It is also trained to help in extreme weather forecasting and, in turn, can also be used as a tool for crisis management during climate change disasters. According to New Atlas, one of the world's largest independent science and technology publications, knowing weather predictions is a crucial factor in assessing how climate change continues to impact our planet. It is also important for crisis management and the reduction of losses to life and property.
"As weather patterns are altered by climate change, and as the frequency of extreme weather events increases, it becomes more important to provide actionable predictions at high spatial and temporal resolutions,” the researchers said.
AI can greatly help in improving weather forecasting that experts have been working on for years. This will help us in preparing not only for simple storms but also potential weather disasters in the future.