A collection of published work across various outlets and periods. I write about the intersection of Technology, Data, Software, Innovation, and Society.
Topics include AI, Knowledge Graphs, Analytics, Algorithms, the Commons, Environment and Sustainability, Blockchain and DLT, Decentralization, Future of Work, Science, Emerging Tech, and more.
|Make software great again: can open source be ethical and fair?|
Is there a way to go beyond open source, and have ethical, fair software in a cloud-first world? This is what some people in the open source community think.
|Amazon and commercial open source in the cloud: It’s complicated|
What do the data tell us about the relationship between cloud vendors -- specifically, Amazon and commercial open source vendors?
|Graph analytics and knowledge graphs facilitate scientific research for COVID-19 ZDNet|
State of the art in analytics and AI can help address some of the most pressing issues in scientific research. Here is how top scientists are using them to facilitate coronavirus research.
|Make Apache Cassandra great again: DataStax going cloud, Kubernetes, open source, and multi-model|
Actions and words, code and advocacy. DataStax is changing strategy, re-engaging with the Apache Cassandra open source community, and releasing some interesting technical advancements while at it, too.
|Business intelligence, meet graph. Neo4j introduces BI connector for data discovery tools|
Mixing graph and relational data is now even more accessible. What does this mean for analytics, and for graph databases specifically?
|Data science vs the COVID-19 pandemic: Flattening the curve — but how?|
Whether they are epidemiologists or not, a few people have attempted to use data and predictive models to model the COVID-19 pandemic. Let's look at the models, the data, and the assumptions and implications that come with them
|Graph analytics for the people: No code data migration, visual querying, and free COVID-19 analytics by TigerGraph|
Graph databases and analytics are getting ever more accessible and relevant
|Machine learning vs payment fraud: Transparency and humans in the loop to minimize customer insults|
What are customer insults, and what does machine learning have to do with it?
|Data science vs social media disinformation: the case of climate change and the Australian bushfires|
While a newly released World Weather Attribution study ties the Australian bushfires to anthropogenic climate change, disinformation on social media abounds
|Universal Code Search gets a boost: Sourcegraph secures $23 million Series B Round funding|
Sourcegraph wants to be the Google of code, even though code search is harder than web search