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 →On Graph query languages. The Year of the Graph Newsletter Vol. 3, June 2018
AWS Neptune goes GA, Microsoft Cosmos DB releases new features, the query language discussion heats up, TigerGraph announces free developer edition, building enterprise knowledge graphs in the real world with Zalando and Textkernel, and more. May has been another interesting month for the graph database world. How can data scientists use knowledge graphs? How, and […]
Read More →Open or closed? On graph database access, query languages, community building, and TigerGraph
Having an entry path, as well as a strong community, is important for any solution, and graph databases are no different. Following latest developments in graph query languages, TigerGraph is changing its strategy. How will this affect the domain? If you’ve been watching the graph database space, you probably know TigerGraph. It’s one of the […]
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 →NBA analytics and RDF graphs: Game, data, and metadata evolution, and Occam’s razor
Three-point shooting, Steph Curry, and coming up with stories. If you feel like doing your own analysis to investigate hypotheses or discover insights at any level, RDF graph's got your back. Case in point: The NBA.
Read More →AWS Neptune going GA: The good, the bad, and the ugly for graph database users and vendors
It's official: AWS has a production-ready graph database. What features are included today, and what will be included in the near future, what use cases are targeted, and what does AWS Neptune's release mean for users and graph database vendors?
Read More →GDPR in real life: Transparency, innovation, and adoption across borders and organizations
Part two: Auditing data on premise and in the cloud, spurring innovation in machine learning and interpretable AI, and influencing organizations, consumers, and legislation all over the world, GDPR is here to stay.
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 →GDPR in real life: Fear, uncertainty, and doubt
Part one: Why are most organizations still not ready for GDPR? And what are the implications and mechanisms of applying GDPR provisions for companies, individuals, and regulators?
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