Nobody believes that every AI project succeeds. Just ask MD Anderson. Anderson blew $60 million on a Watson project before pulling the plug. That project was a clown show. A report published by University of Texas auditors found that project leadership: Did not use proper contracting and procurement procedures Failed to follow IT Governance processes for project approval Did not
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Top AI/ML vendor news for 2019. New AutoML. Several established vendors added automation to their data science and machine learning product line. IBM launched AutoAI, a component of IBM Watson Studio. SAS added AutoML components to SAS Visual Data Mining. Google Cloud Platform launched Cloud AutoML Tables to beta. Alteryx announced the beta release of Assisted Analytics. Databricks announced an
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Cloudera was a great place to work. I had lots of fun there, and Clouderans are the best people. So I’m genuinely sorry to see the company run into trouble. Last week, Cloudera delivered its first post-merger earnings report. A bloodbath ensued: Cloudera Inc. was swimming in downgrades on Thursday morning as analysts digested the company’s weak outlook as well
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Four stories today: A new Big Data solution from Cloudera IBM Watson for workforce optimization Concerns about biased AI SAS embraces open source Let’s get right to it. Cloudera Announces Big Data Solution In a keynote speech at Strata Data, Cloudera Chief Strategy Officer Mike Olson introduced DataNV, a product that addresses the needs of CDOs who don’t have enough
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The Gartner Data and Analytics Summit 2019 in Orlando, that is. Good show. About 4,000 attendees, and most of the top ML and AI vendors. Folks who attend this show buy software. It’s a step up from some conferences, where you spend all day giving away stuff to people who can’t afford pants. Orlando is fun. This year, for the
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Break rules. That is the first principle of good writing. Conventional style and predictable prose will bore your audience. There is no greater sin. You think I don’t know the difference between good and well, and this blog will be a train wreck. Or you think the headline is a joke, and this blog will be fun to read. Either way,
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Every year, in February, SAS hosts a beauty show. It’s a ritual. Industry analysts fly to a posh resort. There, they see shiny new things most users will never see. They listen to executives talk about how the company finally has its shit together. This year is no exception. SAS held its analyst conference February 11-12 at Vanderbilt Beach, Florida.
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Gartner recently published its 2019 Magic Quadrant for Data Science and Machine Learning Platforms. You can secure a copy of the report from Gartner if you are a client, or read it for free here, courtesy of DataRobot. (Registration required.) Here’s how Gartner positioned the 17 vendors that made it into the MQ: Back in October, I wrote my predictions for
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It’s that time of year again. Time to drive stakes in the ground about the year ahead. Looking Back First, a brief look back to see if last year’s predictions aged well. You can read them here. Recap below. My predictions come with a lifetime guarantee: if you are not completely satisfied with them, I will return to you, in cash, the
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Well, 2018 is dead and gone. Time to take a look back at the year in AI/ML. A reminder that I work for DataRobot. This is my personal blog. Opinions are mine. On the Move It’s hard to believe that Amazon Web Services introduced Amazon SageMaker just a year ago, but here we are. AWS moved aggressively to enhance the
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