Moving fast without breaking data: Governance for managing risk in machine learning and beyond
How do you resolve the tension between the need to build and deploy accurate machine learning models fast, and the need to understand how those models work, what data they touch upon, and what are the implications? Immuta says data governance is the answer.
Read More →Wolfram Research goes for Software 2.0, releases neural net repository
Wolfram, having been into AI before it was cool, now gets a piece of the deep learning hype, in its sui generis way. Where does it stand compared to the competition, and how easy is it to use and integrate Wolfram with the rest of the world?
Read More →AI-powered DevOps is how CA wants to reinvent software development and itself
How does non-deterministic software sound? Making data-driven software to help make data-driven software may seem like catch 22, but that's what CA wants to do. Here's why and how.
Read More →Business analytics: The essentials of data-driven decision-making
Data shows that data-driven organizations perform better. But what does it take to get there?
Read More →Human in the loop: Machine learning and AI for the people
HITL is a mix and match approach that may help make ML both more efficient and approachable.
Read More →The road to automation, the joy of work, and the ‘Jen problem’
How do we get to the point where technology is the infrastructure firms run on, and what happens when we do?
Read More →Modernizing Hadoop: Reaching the plateau of productivity
What's new in Hadoop, and how is vendor dynamics and strategy evolving?
Read More →GPU databases are coming of age
GPUs are powering a new generation of databases. What is so special about them and can they come into their own?
Read More →Big data, crystal balls, and looking glasses: Reviewing 2017, predicting 2018
It's this time of year again, when crystal balls meet data. Here's what's kept the data world busy in 2017, and will most likely continue to do so in 2018.
Read More →Machine Learning: The cloud is the new battlefield
There's a reason why every major cloud provider is backing its own machine learning framework. What's that and how do you get to choose?
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