Issue #256
September 18, 2024
- 1. How does cosine similarity work? [tomhazledine.com]
- 2. B-trees and database indexes [planetscale.com]
- 3. Learning to Reason with LLMs [openai.com]
- 4. Geometric Search Trees [g-trees.github.io]
- 5. Novel Architecture Makes Neural Networks More Understandable [quantamagazine.org]
- 6. How I Mastered Data Structures and Algorithms [medium.com/algomaster-io]
- 7. How the LLM Got Lost in the Network and Discovered Graph Reasoning [towardsdatascience.com]
- • Grounding AI in reality with a little help from Data Commons (J. Chen, P. Ramaswami)
- • Collaborative forecasting of influenza-like illness in Italy: the Influcast experience (S. Fiandrino, A. Bizzotto, G. Guzzetta, S. Merler, F. Baldo, E. Valdano, A. M. Urdiales, A. Bella, F. Celino, L. Zino, A. Rizzo, Y. Li, N. Perra, C. Gioannini, P. Milano, D. Paolotti, M. Quaggiotto, L. Rossi, I. Vismara, A. Vespignani, N. Gozzi)
- • Self-similarity of temporal interaction networks arises from hyperbolic geometry with time-varying curvature (S. Dutta, D. Das, T. Chakraborty)
- • A review of the structure of street networks (M. Barthelemy, G. Boeing)
- • A Review of Graph Neural Networks in Epidemic Modeling (Z. Liu, G. Wan, B. A. Prakash, M. S. Y. Lau, W. Jin)
- • LLMs Will Always Hallucinate, and We Need to Live With This (S. Banerjee, A. Agarwal, S. Singla)
- • Bayesian clustering with uncertain data (K. Nicholls, P. D. W. Kirk, C. Wallace)
Terence Tao at IMO 2024: AI and Mathematics
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