d2iq
FEBRUARY 19, 2021
Going from a prototype to production is perilous when it comes to machine learning: most initiatives fail , and for the few models that are ever deployed, it takes many months to do so. As little as 5% of the code of production machine learning systems is the model itself. Adapted from Sculley et al.
ProdOps
FEBRUARY 16, 2021
In the most recent acquisition for the company, DoiT International (DoiT), a global multi-cloud software and managed service provider with deep expertise in Kubernetes, Machine Learning, and Big Data, today announced that it has acquired ProdOps , a top provider of scalable software operations and infrastructure automation services.
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CTOvision
JULY 9, 2014
The term “Big Data” has become synonymous with this evolution. But still, many of our customers continue to ask, “What is Big Data?”, “What are its use cases?”, What is Big Data? The data is too big, moves too fast, or does not fit the structures of your database architectures.
Mobilunity
MAY 20, 2023
Success Stories of Women in Tech Successful businesses lead by example by valuing women CTO, developers, and team leaders. Dr. Fei-Fei Li: A pioneer in artificial intelligence, Dr. Li is the co-director of Stanford University’s Human-Centered AI Institute and the Stanford Vision and Learning Lab.
The Parallax
APRIL 17, 2019
How Facebook fights fake news with machine learning and human insights. CrowdStrike CEO on political infosec lessons learned (Q&A). You need a combination of human analysts and algorithm analysis, “—Staffan Truvé, co-founder and CTO, Recorded Future. READ MORE ON FAKE NEWS AND CYBERSECURITY.
CTOvision
AUGUST 11, 2015
Cognitio's Roger Hockenberry provided context in this report: “Both Wall Street and the intelligence world want the same thing: to find unknown unknowns in the data,” said Roger Hockenberry, the former chief technology officer of the Central Intelligence Agency’s clandestine services and now a partner at the consulting firm Cognitio Corp.
CTOvision
JUNE 15, 2015
IBM will also put more than 3,500 IBM researchers and developers to work on Spark-related projects at more than a dozen labs worldwide; donate its breakthrough IBM SystemML machine learning technology to the Spark open source ecosystem; and educate more than one million data scientists and data engineers on Spark.
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