#LLM training

1868 related articles

Jul 17, 2026·2 min

Training a CPU-Native LLM on Zero Budget: The Architectural Gamble of Ternary Quantization × Sparse MoE

An indie dev attempts to train a CPU-native LLM on $0 budget using ternary quantization, sparsity, and fine-grained MoE — with pre-registered success criteria and full public reporting.

Jul 16, 2026·2 min

Google RLMF: Training LLMs to Honestly Express Uncertainty via Metacognitive Feedback

Google and Yale propose RLMF, using metacognitive feedback to train LLMs for honest uncertainty expression, achieving 63% calibration improvement in benchmarks.

Jul 16, 2026·3 min

DeepSeek Open-Sources DSpark: 50%–400% LLM Inference Speedup Without Retraining

DeepSeek open-sources DSpark, delivering 50%–400% LLM inference speedup with no retraining or quantization, via semi-autoregressive drafting and confidence-scheduled verification.

JAX Host Offloading: A Practical Guide…

Jul 14, 2026·2 min

JAX Host Offloading: A Practical Guide to Breaking Through LLM Training Memory Bottlenecks

Memory capacity is the core bottleneck in LLM training. This guide explores JAX-based host offloading — covering optimizer state offloading, activation strategies, PCIe bandwidth trade-offs, and how it complements activation recomputation.

Jul 13, 2026·3 min

Training a 100M-Parameter Model for Under $50: A Complete Record of Building SmoLLM from Scratch

An ML engineer trained SmoLLM, a 109M-parameter LLaMA-style model from scratch for under $50. Full breakdown of architecture, training pitfalls, instruction tuning, and real-world performance.

Jul 9, 2026·2 min

IEEE Launches LLM Training Course: Large Language Model Education Goes Mainstream

IEEE launches an official LLM training course, signaling large language models are entering standardized professional education. What this means for the AI talent gap and your career.

Jul 7, 2026·5 min

Nonuniform Tensor Parallelism: NVIDIA's New Fault-Tolerance Approach to Boost LLM Training Goodput

NVIDIA introduces Nonuniform Tensor Parallelism, letting GPUs bear different compute loads so training can continue without checkpoint rollback during hardware failures—boosting LLM training Goodput and fault tolerance at scale.

Agent Tuning: A Complete Guide to Training LLMs with Agent Capabilities

Tutorials

Jun 3, 2026·3 min

Agent Tuning: A Complete Guide to Training LLMs with Agent Capabilities

A deep dive into Agent Tuning principles and practices, covering why Agent training is needed, the evolution from Prompt to RAG to Agent, development workflows, and cost assessment for private deployment.

Complete Guide to LLM Training: Pre-training, SFT Fine-tuning, and Preference Alignment Explained

Deep Dives

Jun 3, 2026·3 min

Complete Guide to LLM Training: Pre-training, SFT Fine-tuning, and Preference Alignment Explained

Complete guide to the three core LLM training stages: pre-training, supervised fine-tuning (SFT), and preference alignment (DPO/PPO), covering LoRA, distillation, quantization, and pruning.

Jul 29, 2026·2 min

AI Bubble Fears Intensify: The Logic Behind Chip Stocks Selling Off Across U.S. and Asian Markets

Chip stocks fall simultaneously across U.S. and Asian markets as AI bubble fears intensify. Analysis of the drivers, sustainability of AI capex, and the balance between short-term volatility and long-term trends.

Jul 29, 2026·2 min

Grok 4.6 and 4.7 Roadmap Leaked: Analyzing xAI's Rapid Iteration Strategy

Reddit leaks suggest Grok 4.6 arrives around August 7 and Grok 4.7 in early September. This article analyzes xAI's rapid iteration strategy and token efficiency improvements.

Jul 29, 2026·4 min

Full-Stack Machine Learning Project Repository Structure Guide: From Chaos to Convention

A detailed guide to organizing full-stack ML project repositories, covering directory structure design, data-code separation, and configuration externalization to help ML developers move from experimental code to production-grade engineering.

Jul 29, 2026·4 min

A Guide to Full-Stack Machine Learning Project Repository Structure: From Chaos to Convention

A detailed guide to organizing full-stack ML project repositories, covering directory structure design, data-code separation, and externalized configuration to help ML developers move from experimental code to production-grade engineering standards.

Jul 29, 2026·2 min

AI Bubble Fears Intensify: The Logic Behind Chip Stocks Selling Off Across US and Asian Markets

Chip stocks decline simultaneously across US and Asian markets as AI bubble fears intensify. Analysis of the logic behind the selloff, sustainability questions around AI capex, and the relationship between short-term volatility and long-term trends.

Jul 29, 2026·3 min

Truth Has No Direction: How the Tarski Paradox Challenges LLM Truth Probe Techniques

How a Tarski-style attack challenges LLM truth probes from the foundations of logic. Is the linear representation hypothesis valid, or is the "truth direction" in AI activations just a statistical illusion?

Jul 29, 2026·2 min

Andrew Ng's New Company LearnVector: Achieving One-on-One Personalized Learning with AI

Andrew Ng launches LearnVector, leveraging generative AI to create one-on-one personalized learning experiences. Explore its core vision, potential capabilities, challenges, and how LLMs could solve education's scalability problem.

Jul 29, 2026·2 min

Claude Mythos Cryptographic Algorithm Cracking Incident: The Reality and Boundaries of AI Cryptanalysis

Anthropic's Claude Mythos Preview model reportedly discovered improved cryptographic attack methods. This article analyzes the realistic boundaries of AI cryptanalysis capabilities and implications.

Jul 29, 2026·2 min

Claude Mythos Codebreaking Incident Explained: The Reality and Limits of AI Cryptanalysis

Anthropic's Claude Mythos Preview model reportedly discovered improved cryptographic attack methods. This article analyzes the real capability boundaries of AI cryptanalysis and its implications.

Jul 29, 2026·2 min

OpenReviewer: An Open-Source LLM Built Specifically for Scientific Paper Review

OpenReviewer is an open-source LLM for generating critical scientific paper reviews. This article analyzes its technical approach, use cases, and limitations.

Jul 29, 2026·3 min

New Gemini Jailbreak Method: Deep Analysis of the Observer and Accomplice Technique

Deep analysis of a Gemini jailbreak technique—the Observer and Accomplice method—examining how it exploits contextual manipulation and reasoning chain inconsistencies to bypass AI safety alignment.