Essentially every learning algorithm / inductive bias is applicable to this. E.g., think of learning a Bayes net where some of the variables are your actions. (How well it works is another question, and here causal theories are presumably very useful, but not exhaustive.)
AI
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NVIDIA NetApp DGX SuperPOD AI Infrastructure at SC22
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At SC22, NVIDIA and NetApp talk about the latest joint AI infrastructure offerings for flexible AI deployments including NVIDIA DGX SuperPOD powered by GPU-accelerated NVIDIA DGX Systems with AMD EPYC™ CPUs: https://
wp.me/p3RLHQ-nxX -
Evaluation Metrics for Language Modeling Explained
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Evaluation Metrics for Language Modeling https://
thegradient.pub/understanding-
evaluation-metrics-for-language-models/
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Shannon’s Mathematical Theory of Communication Foundations
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A Mathematical Theory of Communication By C. E. SHANNON
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Nuance and NVIDIA Partner on AI Diagnostic Tools for Radiologists
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@NuanceInc and NVIDIA announced today a partnership to bring #AI based diagnostic tools directly into the hands of clinical radiologists, enabling the delivery of improved patient care at lower costs. Read the press release: https://
nvda.ws/3TzMGkH -
Physics Laws as Master Algorithm: Intelligence Emergence
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The laws of physics are the master algorithm: run them long enough and intelligence emerges.
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Inductive Bias, Complete Data, and Causal Theories Recap
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To recap:
– We always need prior assumptions/inductive biases, unless we have complete data (no free lunch theorem).
– If we have complete data, we don't need anything else for any rung.
– Causal theories are a type of inductive bias.
I guess that's a No answer to your question. -
Complete Data Includes Mental States and Counterfactual Questions
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That's because the data is incomplete. Complete data includes the state of the actors' minds, and allows you to correctly answer counterfactual questions (which just correspond to different states of the world).
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Incomplete Models: Action’s Role in Learning and Decision-Making
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Those models are incomplete, because they don't include your actions. Convergence aside, and tautologically, if you know everything there's nothing left to learn. You can then make optimal decisions without causal assumptions.
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Technical Debt Loan Officer Role in Senior Career Ladder
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Oh I like that terminology – I think being a technical debt loan officer should be an acknowledged responsibility of the senior/staff career ladder