Artifictional Intelligence: is the Singularity or the Surrender the real threat to humanity?
Artificial intelligence is one of those things: overhyped and yet mystical, the realm of experts and yet something everyone is inclined to have an opinion on. Harry Collins is no AI expert, and yet he seems to get it in a way we could only wish more experts did. Collins is a sociologist. In his book “Artifictional […]
Read More →AI chips for big data and machine learning: Hard choices in the cloud and on-premise
How can GPUs and FPGAs help with data-intensive tasks such as operations, analytics, and machine learning, and what are the options?
Read More →Zen and the art of data structures: From self-tuning to self-designing data systems
Designing data systems is something few people understand, and it's very hard and costly. But that, too, could be automated, says new research from Harvard, and we're about to start seeing it in real life.
Read More →The best programming language for data science and machine learning
Hint: There is no easy answer, and no consensus either.
Read More →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?
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