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 →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 →Streamlit wants to revolutionize building machine learning and data science applications, scores $21 million Series A funding
Streamlit wants to be for data science what business intelligence tools have been for databases: A quick way to get to results, without bothering much with the details
Read More →Compute to data: using blockchain to decentralize data science and AI with the Ocean Protocol
The conflict between access to data and data sovereignty is key to understanding how AI works, and moving it forward. The Ocean Protocol Foundation wants to help resolve that conflict, by introducing a way of letting AI work with data without giving up control.
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 →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
Read More →Nvidia GPUs for data science, analytics, and distributed machine learning using Python with Dask
Nvidia wants to extend the success of the GPU beyond graphics and deep learning to the full data science experience. Open source Python library Dask is the key to this.
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