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Introduction to Approximate Solution Methods for Reinforcement Learning
series about Reinforcement Learning (RL), following Sutton and Barto’s famous book “Reinforcement Learning” . In the previous posts we finished dissecting Part I of said…
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A Coding Tutorial on OpenMythos on Recurrent-Depth Transformers with Depth Extrapolation, Adaptive Computation, and Mixture-of-Experts Routing
In this tutorial, we explore the implementation of OpenMythos, a theoretical reconstruction…
Google DeepMind Introduces Decoupled DiLoCo: An Asynchronous Training Architecture Achieving 88% Goodput Under High Hardware Failure Rates
Training frontier AI models is, at its core, a coordination problem. Thousands…
Mend Releases AI Security Governance Framework: Covering Asset Inventory, Risk Tiering, AI Supply Chain Security, and Maturity Model
There’s a pattern playing out inside almost every engineering organization right now.…
OpenAI Releases GPT-5.5, a Fully Retrained Agentic Model That Scores 82.7% on Terminal-Bench 2.0 and 84.9% on GDPval
OpenAI has released GPT-5.5, its most capable model to date and the…
Mend.io Releases AI Security Governance Framework Covering Asset Inventory, Risk Tiering, AI Supply Chain Security, and Maturity Model
There’s a pattern playing out inside almost every engineering organization right now.…
Efficient Privacy Loss Accounting for Subsampling and Random Allocation
We consider the privacy amplification properties of a sampling scheme in which…
Your Synthetic Data Passed Every Test and Still Broke Your Model
looked solid. The KL divergence was well within acceptable ranges. On the…
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