1. Bayesian vs. Traditional Statistics by Michael Huemer at Fake Noûs. Huemer on the use of conditional probabilites in statistics, neglecting prior probabilities, and how this can lead to the Streetlamp fallacy.
  2. A Turbulent Year: The 2019 Data & AI Landscape by Matt Turck. A close look at the rapidly evolving data and AI landscape in 2019. 
  3. Part II: Major Trends in the 2019 Data & AI Landscape by Matt Turck. A data-packed long-read.
  4. A Visual Intro to NumPy and Data Representation by Jay Alammar. An explanation how NumPy can be applied to show different types of data for different use cases. 
  5. Network-Driven Differences in Mobility and Optimal Transitions Among Automatable Jobs by Jordan D. Dworkin at Royal Society Open Science. To soften the coming/beginning turbulence of automation, we not only need to look at the sectors that will be automated but also at the ability toshift between sectors. “Optimal recommendations should not only consider a new job’s automatability and growth potential, but also its similarity to the job a worker is leaving.”
  6. With Little Training, Machine-Learning Algorithms Can Uncover Hidden Scientific Knowledge by  Lawrence Berkeley National Laboratory for Techxplore. Paper: Unsupervised word embeddings capture latent knowledge from materials science literature by Tshitoyan et al. at Nature. By using NLP (specifically word embeddings) to analyze research papers, undetected or latent knowledge can be discovered. Anubhav Jain (coauthor): “I had thought maybe the algorithm could be descriptive of what people had done before but not come up with these different connections. I was pretty surprised when I saw not only the predictions but also the reasoning behind the predictions, things like the half-Heusler structure, which is a really hot crystal structure for thermoelectrics these days.”
  7. Getting It Less Wrong, The Brain’s Way: Science, Pragmatism, and Multiplism by Paul Grobstein. How our our approach to science mirrors the interpretation strategy of the brain. “The brain is not designed to have a single picture of “reality” as an outcome, but rather to explore an infinite variety of candidate pictures.”
  8. China is Forcing Tourists Crossing the Border to Install Apps that Scan their Phones by Nico Teitel at Vice. For anyone travelling to China, surveillance tech has just gotten a lot more real.
  9. Why Big Brother Doesn’t Bother Most Chinese by Adam Minter at Bloomberg. Though the article refers to studies, its conclusions seem a bit naive: After all, the system has been set up according to the rules of game theory, encouraging early adoption and stifling dissent.
  10. Temporal Processing by Sebastian Ruder. Introduction to temporal handling in NLP, i.e. connecting events in text to their corresponding time.