Issue #35
January 26, 2020
- 1. The Economics of AI Today [thegradient.pub]
- 2. Emil's Story as a Self-Taught AI Researcher [floydhub.com]
- 3. RyanAir, Hamiltonian Cycles, and using Graph Theory to find cheap flights [jonlu.ca]
- 4. The battle for ethical AI at the world's biggest machine-learning conference [nature.com]
- 5. Discovering millions of datasets on the web [blog.google]
- 6. Machine Learning: The Big Picture [towardsdatascience.com]
- 7. Bayesian Neural Networks Need Not Concentrate [jacobbuckman.com]
- • How Amazon Web Services Uses Formal Methods (C. Newcombe, T. Rath, F. Zhang, B. Munteanu, M. Brooker, M. Deardeuff)
- • Collaboration leads to cooperation on sparse networks (S. D. Angus, J. Newton)
- • Blockchain Consensuses Algorithms: A Survey (M. S. Ferdous, M. Jabed M. Chowdhury, M. A. Hoque, A. Colman)
- • Measuring the diffusion of innovations with paragraph vector topic models (D. Lenz, P. Winker)
- • Scaling Laws for Neural Language Models (J. Kaplan, S. McCandlish, T. Henighan, T. B. Brown, B. Chess, R. Child, S. Gray, A. Radford, J. Wu, D. Amodei)
- • Neural Embeddings of Scholarly Periodicals Reveal Complex Disciplinary Organizations (H. Peng, Q. Ke, C. Budak, D. M. Romero, Y.-Y. Ahn)
Keynote: The Mathematics of Causal Inference: with Reflections on Machine Learning
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