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IBM and Texas A&M AgriLife provide data, technology and expertise to farmers in need

IBM Journey to AI blog

In Texas, 2022 was one of the driest years on record. With failed crops, low yields for farmers and diminished grazing for cattle, the Texas Department of Agriculture identified climate change as a potential threat to the state’s food supply.

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Turning climate risks into business opportunities 

IBM Journey to AI blog

Climate change causes extreme weather events across the world that endanger people’s lives and disrupt the businesses on which they depend. In the US, the Texas Department of Agriculture identified climate change as a potential threat to the state’s food supply.

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Examples and uses of GIS

IBM Journey to AI blog

This is information relating to the Earth’s surface, its climate, the people who live on it, its ecosystems and more. Additionally, IBM and Texas A&M AgriLife have created a tool to help improve crop management strategies. One of the largest sources of data is all around us—that is, geospatial data.

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Expedite your Genesys Cloud Amazon Lex bot design with the Amazon Lex automated chatbot designer

AWS Machine Learning Blog

Machine learning (ML) technologies continually improve and power the contact center customer experience by providing solutions for capabilities like self-service bots, live call analytics, and post-call analytics. Anand lives in Dallas, Texas and enjoys travelling.

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2021 Data/AI Salary Survey

O'Reilly Media

Our audience is also strong in the states where these industries are concentrated: 42% of the US respondents lived in California (20%), New York (9%), Massachusetts (6%), and Texas (7%), though these states only make up 27% of the US population. The states with the most respondents were California, New York, Texas, and Massachusetts.

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Taking Their Time Series Talents to South Beach: How McLaren Is Gaining an Edge with Accurate Weather Data

DataRobot Blog

If you’ve ever driven through Texas or Florida during a rare Southern snowstorm, a few things quickly become cartoonishly obvious—your tyres matter, your driving matters, and your ability to navigate changing weather conditions really matters. The models are then ready to be deployed live via a StreamLit application.

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Responsible AI at Google Research: The Impact Lab

Google Research AI blog

Dana Center at the University of Texas, Austin. By using proxy data, such as race or ethnicity, gender, or zip code, we are systematically merging together the lived experiences of an entire group of diverse people and using it to train models that can recreate and maintain harmful and inaccurate character profiles of entire populations.