Issue #29

December 15, 2019

---

1. 1. Artificial Intelligence Index Report 2019 [hai.stanford.edu]
2. 2. Quantum computing gains a first foothold in investment banking [medium.com/@IBMResearch]
3. 3. An AI Pioneer Wants His Algorithms to Understand the 'Why' [wired.com]
4. 4. When did societies become modern? 'Big history' dashes popular idea of Axial Age [nature.com]
5. 5. Project Petridish: Efficient forward neural architecture search [microsoft.com]
6. 6. The Huge, Unseen Operation Behind the Accuracy of Google Maps [wired.com]
7. 7. Building a search engine from scratch [0x65.dev]

---

• • Machine learning and the physical sciences (G. Carleo, I. Cirac, K. Cranmer, L. Daudet, M. Schuld, N. Tishby, L. Vogt-Maranto, L. Zdeborová)
• • Detecting and quantifying causal associations in large nonlinear time series datasets (J. Runge, P. Nowack, M. Kretschmer, S. Flaxman, D. Sejdinovic)
• • Markov chain approach to model intertemporal choices and coverages in air transport markets (D. O. Cajueiro, F. N. Mundim, J. I. F. Martins, P. A. M. Sakowski, R. F. S. Andrade)
• • Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (A. Olteanu, C. Castillo, F. Diaz, E. Kıcıman)
• • Recurrent Neural Networks (RNNs): A gentle Introduction and Overview (R. M. Schmidt)
• • Animal daily mobility patterns analysis using resting event networks (M. Lenormand, H. Pella, H. Capra)
• • The mathematical structure of innovation (T. M. A. Fink, A. Teimouri)
• • Logistic regression models for aggregated data (T. Whitaker, B. Beranger, S. A. Sisson)

---

16. Learning: Support Vector Machines

All our videos are also available in our YouTube playlist.

---