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.
Read More →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 you call it data lakehouse or by any other name, you need the best of two worlds, says Databricks. A new query engine and a visualization layer are the next pieces in Databricks' puzzle.
Read More →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 bias typically come into play. In the nascent domain of scientific fact checking, things are complicated.
Read More →AI chips in 2020: Nvidia and the challengers
Now that the dust from Nvidia's unveiling of its new Ampere AI chip has settled, let's take a look at the AI chip market behind the scenes and away from the spotlight
Read More →GoodData and Visa: A common data-driven future?
From user, to partner and investor. That's not a very common scenario for software vendors, especially if the user-cum-partner-investor is someone like Visa. GoodData is evolving more than its relationship with select users.
Read More →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 pressing issues in scientific research. Here is how top scientists are using them to facilitate coronavirus research.
Read More →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
Read More →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?
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