A troubleshooting platform for free: Netdata scores $14.2M funding to extend its open-source application monitoring platform
Netdata thinks what the world lacks is a troubleshooting platform to bring real-time metrics to observability. They are building and offering it to the world for free — for now.
Read More →Data.world secures $26 million funding, exemplifies the use of semantics and knowledge graphs for metadata management
Data.world wants to eliminate data silos to answer business questions. Their bet to do this is to provide data catalogs powered by knowledge graphs and semantics. The choice of technology seems to hit the mark, but intangibles matter, too.
Read More →Nvidia’s acquisition of Arm strengthens its ecosystem, brings economies of scale to the cloud, expansion to the edge
Nvidia is after a double bottom line in the AI chip market: Better performance and better economics. Arm's acquisition helps with the economies of scale in the data center and expands Nvidia's footprint to the edge
Read More →AI and automation vs. the COVID-19 pandemic: Trading liberty for safety
Reports on the use of AI to respond to COVID-19 may have been greatly exaggerated. But does the rush to pandemic-fighting solutions like thermal scanners, face recognition and immunity passports signal the normalization of surveillance technologies?
Read More →Graph, machine learning, hype, and beyond: ArangoDB open source multi-model database releases version 3.7
A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its offering.
Read More →Explainable AI: From the peak of inflated expectations to the pitfalls of interpreting machine learning models
We have reached peak hype for explainable AI. But what does this actually mean, and what will it take to get there?
Read More →Open source observability marches on: New Relic and Grafana Labs partnership brings benefits to developers
The perfect observability storm with open source leading the way, and a partnership that makes sense
Read More →Explainable AI: A guide for making black box machine learning models explainable
In the future, AI will explain itself, and interpretability could boost machine intelligence research. Getting started with the basics is a good way to get there, and Christoph Molnar's book is a good place to start.
Read More →Data governance and context for evidence-based medicine: Transparency and bias in COVID-19 times
In the early 90s, evidence-based medicine emerged to make medicine more data-driven. Three decades later, we have more data, but not enough context, or transparency.
Read More →Garbage in, garbage out: Data science, meet evidence-based medicine
Did you ever wonder how data is used in the medical industry? The picture that emerges by talking to the experts leaves a lot to be desired.
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