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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…
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…
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,…
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…
Data Lakehouse, meet fast queries and visualization: Databricks unveils Delta Engine, acquires Redash
Data warehouses alone don’t cut it. Data lakes alone don’t cut it either. So whether…
Scientific fact-checking using AI language models: COVID-19 research and beyond
Fact or fiction? That’s not always an easy question to answer. Incomplete knowledge, context and…
Graph analytics and knowledge graphs facilitate scientific research for COVID-19
State of the art in analytics and AI can help address some of the most…
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…
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…
Knowledge graph evolution: Platforms that speak your language
Knowledge graphs are among the most important technologies for the 2020s. Here is how they…