In this week’s roundup, learn how artificial intelligence (AI) is being used to keep track of volcanic activity, improve the plant breeding process, and build better batteries. Understand what Machine Learning Ops (MLOps) is and why it’s important as your organization scales its machine learning efforts. Lastly, look ahead to the next generation of artificial intelligence. 

Scale Your Machine Learning with MLOps

By Jessica Davis, contributing writer for

You’ve implemented artificial intelligence and machine learning pilot programs within your organization. Key learnings have bubbled to the surface as a result. You need to apply these learnings and use them to get more efficient for future projects in other areas of your organization. But how? You need to start looking at MLOps.


Deep Learning Artificial Intelligence Keeps An Eye On Volcano Movements

By Matt Swayne, contributing writer for

RADAR satellites collect remote sensing data that can detect ground movements at volcanoes in near real-time. But, clouds and other atmospheric disturbances can cause significant measurement errors. Researchers have uncovered a way to use AI to clear up the noise, greatly improving the accuracy of near real-time observation of volcanic movements and the detection of volcanic activity and unrest.


Inner Workings: Crop Researchers Harness Artificial Intelligence To Breed Crops For The Changing Climate

By Carolyn Beans, contributing writer for

With a rapidly growing world population amidst climate change, plant breeders have a challenge in front of them to ensure crop productivity keeps up. Researchers are turning to AI to speed up the process of plant breeding in order to quickly assess which plants grow in a particular climate. What used to take years to achieve can now be done much more rapidly, even taking climate change into account. 


The Next Generation Of Artificial Intelligence

By Rob Toews, contributing writer for

The field of AI is progressing and evolving at an amazingly fast speed—and it will only change more rapidly moving forward. What’s cutting-edge today will be outdated in five years. What can you expect for the future of AI? What should you be on the lookout for? Learn about three emerging areas that are poised to redefine the field.


AI Is Throwing Battery Development Into Overdrive

by Daniel Oberhaus, contributing writer for

For the last few years, researchers are using AI to determine how to build a better, fast charging battery. For example, one team managed to optimize a fast-charging protocol for a lithium-ion battery in less than a month. Without the use of AI, this would have taken roughly two years to achieve. Learn about more ways AI is being used for battery development and the positive implications that this will have on the environment.


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