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Least Squares: Where Convenience Meets Optimality

Contents0.1. Computational Convenience2. Mean and Median3. OLS is BLUE4. LS is MLE with normal errorsConclusion 0. Least Squares is used almost everywhere when it comes to numerical optimization and regression tasks in machine learning. It aims at minimizing the Mean Squared Error (MSE) of a given model. Both L1 (sum of absolute values) and L2 (sum of squares) …

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Benchmarking the next generation of never-ending learners

ContentsNotesReferences Notes References [1] John M Jumper, Richard Evans, Alexander Pritzel, Tim Green, Michael Figurnov, Olaf Ron-neberger, Kathryn Tunyasuvunakool, Russ Bates, Augustin Zídek, Anna Potapenko, Alex Bridgland, Clemens Meyer, Simon A A Kohl, Andy Ballard, Andrew Cowie, Bernardino Romera-Paredes, Stanislav Nikolov, Rishub Jain, Jonas Adler, Trevor Back, Stig Petersen, David A. Reiman, Ellen Clancy, Michal …

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Evolving Product Operating Models in the Age of AI

previous article on organizing for AI (link), we looked at how the interplay between three key dimensions — ownership of outcomes, outsourcing of staff, and the geographical proximity of team members — can yield a variety of organizational archetypes for implementing strategic AI initiatives, each implying a different twist to the product operating model. Now …

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Building interactive agents in video game worlds

Notes [1] Abramson, J., Ahuja, A., Barr, I., Brussee, A., Carnevale, F., Cassin, M., Chhaparia, R., Clark, S., Damoc, B., Dudzik, A. and Georgiev, P., 2020. Imitating interactive intelligence. arXiv preprint arXiv:2012.05672. [2] Abramson, J., Ahuja, A., Brussee, A., Carnevale, F., Cassin, M., Fischer, F., Georgiev, P., Goldin, A., Harley, T. and Hill, F., 2021. …

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RED

R.E.D.: Scaling Text Classification with Expert Delegation

With the new age of problem-solving augmented by Large Language Models (LLMs), only a handful of problems remain that have subpar solutions. Most classification problems (at a PoC level) can be solved by leveraging LLMs at 70–90% Precision/F1 with just good prompt engineering techniques, as well as adaptive in-context-learning (ICL) examples. What happens when you …

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DeepMind’s latest research at NeurIPS 2022

Advancing best-in-class large models, compute-optimal RL agents, and more transparent, ethical, and fair AI systems The thirty-sixth International Conference on Neural Information Processing Systems (NeurIPS 2022) is taking place from 28 November – 9 December 2022, as a hybrid event, based in New Orleans, USA. NeurIPS is the world’s largest conference in artificial intelligence (AI) …

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Mastering Stratego, the classic game of imperfect information

Research Published 1 December 2022 Authors Julien Perolat, Bart De Vylder, Daniel Hennes, Eugene Tarassov, Florian Strub and Karl Tuyls DeepNash learns to play Stratego from scratch by combining game theory and model-free deep RL Game-playing artificial intelligence (AI) systems have advanced to a new frontier. Stratego, the classic board game that’s more complex than …

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AI for the board game Diplomacy

Research Published 6 December 2022 Authors Yoram Bachrach, János Kramár Agents cooperate better by communicating and negotiating, and sanctioning broken promises helps keep them honest Successful communication and cooperation have been crucial for helping societies advance throughout history. The closed environments of board games can serve as a sandbox for modelling and investigating interaction and …

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