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Investment in Machine Learning Keeps Growing, DataRobot Finds

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After years of double-digit growth in machine learning investments, nearly 90% of companies grew their machine learning budgets again from 2020 to 2021, according to a survey from DataRobot, which also documented the top struggles that companies have with machine learning. For DataRobot's report, titled "5 Latest Trends in Enterprise Machine Learning," the AI cloud vendor surveyed about 400 companies about their AI and ML strategies. The survey showed that 86% of the companies surveyed planned to increase their spending on ML, compared ot 10% who planned no increase and just 4% who planned to spend less. While the number of companies planning to increase their 2021 spending on ML by 1% to 25% relative to 2020 declined compared to the previous two years, DataRobot spotted significant increase in companies planning to increase their spending by 26% or more. Where is all this money going?


Farmers Insurance Webinar - 09-19-17 - DataRobot

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During this webinar, Scot Barton, Head of Business Insurance R&D, will provide an overview of how Farmers Insurance created a sustainable, cost-effective, and customer-centric predictive analytics strategy through machine learning automation. Satadru Sengupta, General Manager of Insurance at DataRobot, will then review the full spectrum of use cases that DataRobot clients are currently solving with machine learning automation - and deliver a demo. The webinar will conclude with a conversation between Scot and Satadru on industry outlook and a short Q&A session. Sign up and we'll send you the recording from the live webinar.


Leaked AI regulation: What it means for the U.S.

ZDNet

Given the EU's leaked plans for AI regulation, which calls for a ban on specific types of AI systems, such as those that directly track individuals and create social credit scores, the topic of regulation in the U.S. has been on people's minds. AI is coming, so what can regulators do--and what should they absolutely not do--to protect citizens and consumers while also encouraging technological development? For insights I reached out to Haniyeh Mahmoudian, Ph.D., Global AI Ethicist at DataRobot, a Boston-based company that enables customers to create and validate machine learning models from their data. As an AI bias and ethics expert, Haniyeh is well-placed to speak about the new regulations and what they means for the U.S., as well as the risks inherent in unchecked AI and what actions should be taken by regulators going forward. GN: What are the biggest takeaways from the EU's leaked plans for AI regulation?


DataRobot looks to bridge Australia's Data Scientist gap - Which-50

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Joseph Brookes is a writer and content producer for Which-50.com He has covered the impact of digital transformation on Australian businesses with a particular focus on the media, financial services and governments sectors. Joseph is also responsible for Which-50's multimedia products including the production of video, podcasts and animated graphics.


Grand Slam Analytics: Who Will Win the World Series?

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Andrew Engel is General Manager for Sports and Gaming at DataRobot. He works with DataRobot customers across sports and casinos, including several Major League Baseball, National Basketball League and National Hockey League teams. He has been working as a data scientist and leading teams of data scientists for over ten years in a wide variety of domains from fraud prediction to marketing analytics. Andrew received his Ph.D. in Systems and Industrial Engineering with a focus on optimization and stochastic modeling. He has worked for Towson University, SAS Institute, the US Navy, Websense (now ForcePoint), Stics, and HP before joining DataRobot in February of 2016.