Newsletter Archive

Monday, March 23, 2026

Lossy self-improvement · Implementing Deep Q-Learning (DQN) from Scratch Using RLax JAX Haiku and Optax to Train a CartPole Reinforcement Learning Agent · How BM25 and RAG Retrieve Information Differently?                                                                                
AI Pulse AI Pulse Monday, March 23, 2026
Lossy self-improvement

Argues that AI self-improvement exists but faces fundamental constraints preventing rapid recursive improvement—information loss and diminishing returns limit how much each iteration can enhance capability.

Interconnects · 11 min read Community

Implementing Deep Q-Learning (DQN) from Scratch Using RLax JAX Haiku and Optax to Train a CartPole Reinforcement Learning Agent

Step-by-step guide to implementing Deep Q-Learning using RLax, JAX, Haiku, and Optax—combining Google DeepMind's RL library with core JAX components to train a CartPole agent from scratch.

MarkTechPost · 6 min read Tools

How BM25 and RAG Retrieve Information Differently?

BM25 vs. neural retrieval in RAG: how traditional keyword matching (BM25) and learned embeddings rank documents differently, with tradeoffs for search and AI-powered systems.

MarkTechPost · 10 min read Tools

Speculating Experts Accelerates Inference for Mixture-of-Experts

Researchers propose prefetching future experts in Mixture-of-Experts models by predicting which experts will be needed next, cutting CPU-GPU transfer overhead that kills inference speed when expert weights are memory-constrained.

arXiv ML · 3 min (abstract) Research

Nvidia pushes deeper into AI inference to counter custom chip rivals - digitimes

Nvidia is expanding its inference-focused offerings to defend market share against custom silicon from cloud providers and competitors. This strategic pivot reshapes hardware economics for AI deployment and forces practitioners to reassess cost-per-token calculations across platforms.

Digitimes · 3 min read Hardware

AI Startup Upstage in Talks to Buy 10,000 AMD Chips in Korea - Bloomberg.com

Korean AI startup Upstage is negotiating to purchase 10,000 AMD chips, marking a significant bet on AMD infrastructure as an alternative to Nvidia's dominant GPU ecosystem. The deal reflects growing momentum in breaking Nvidia's stranglehold on AI hardware procurement.

Bloomberg · 1 min read Industry

China's AI GPU self-sufficiency to hit 80% by 2030 highlights growing challenges for Nvidia - digitimes

China projects 80% AI GPU self-sufficiency by 2030, signaling accelerated domestic chip development and reduced reliance on Nvidia—a seismic market shift driven by U.S. export controls and strategic competition in frontier AI.

Digitimes · 3 min read Market

The AI Race Is Pressuring Utilities to Squeeze More From Europe’s Power Grids

European utilities are retrofitting power grids to accommodate the massive electricity demand from AI data centers, experimenting with novel load-balancing techniques to create capacity without major infrastructure overhauls. This is becoming a competitive advantage for regions trying to attract AI investment.

Wired AI · 1 min read Industry

Quick Hits
Meet the Gods of AI Warfare Wired AI Policy
Jensen Huang says Nvidia engineers should use AI tokens worth half their annual salary every year to be fully productive — compares not using AI to using paper and pencil for designing chips - Tom's Hardware Tomshardware Industry
Trump AI directive could spur congressional action on data centers - E&E News by POLITICO Eenews Policy
Ex-Goldman Banker’s AI Chip Company Secures SoftBank Funding Bloomberg Tech Market
Sen. Warren questions DOD about Anthropic blacklist that 'appears to be retaliation' CNBC Tech Policy
US Panel Warns China’s AI Models Gaining Ground Despite Chip Restrictions - Fine Day 102.3 Finedayradio Policy

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