⚡ Continuous Batching · Scour

⚡ Continuous BatchingSpecific

dynamic batching, vLLM, inference throughput, iteration-level scheduling

not much happened today | AINews

Covers 5 stories including Bernie Sanders unveils $7 trillion plan to give Americans control of AI industry

digitalocean.com·

Efficient LLM Compression with SparseGPT and Wanda on GPU Cloud

Covers NVIDIA Triton Inference Server — NVIDIA Triton Inference Server

Rack to Cloud·

GPU Scarcity Isn't the Problem Anymore. GPU Allocation Governance Is.

Discussed on DEV

Running local LLMs on the Arduino® UNO™ Q board: a practical guide

Running GLM-5.2 5x faster at 500tps with limitation

Discussed on Hacker News

Irrational Analysis·

Cerebras June 2026 Earnings

Discussed on Substack

·

The Transformer Pipeline: A Complete Mathematical and Visual Guide

The Crossplane Blog·

Building Modelplane on Crossplane

Discussed on Hacker News

·

The Context Budget That Will Decide Everyday AI

CompressKV: Semantic-Retrieval-Guided KV-Cache Compression for Resource-Efficient Long-Context LLM Inference

Serving Large Language Models with a Minimalist Python CLI

Covers 2 stories including uv

Discussed on Hacker News

Fergus's blog·

Adaptive speculative decoding: picking draft lengths at runtime

Covers 4 stories including Looking for a self-hosted alternative to Modal.com for running ML workloads

Discussed on Hacker News

blocksandfiles·

Dell and data physics

Generate per-session LoRA adapters in <1s for agentic inference efficiency

Discussed on Hacker News

carnotresearch.medium.com·

KV Cache in LLMs: From Zero to Production

certdepot.net·

Recent Technical

whyopensource.ai·

A running list of reasons to move to open source

Covers 3 stories including Statement on the US government directive to suspend access to Fable 5 and Mythos 5

Discussed on Hacker News

Gradient Ascent·

Groq on Endless Compute, Inside Claude's Mind, and GLM-5.2 Open Weights - The Tokenizer Edition #32

Covers 3 stories including alibaba/open-code-review: Battle-tested at Alibaba's scale. Hybrid architecture code review tool: deterministic pipelines + LLM Agent, precise line-level comments, built-in fine-tuned ruleset (NPE, thread-safety, XSS, SQL injection), OpenAI & Anthropic compatible.

ASAP: Agent-System Co-Design for Wall-Clock-Centered Auto HPO Research for ML Experiments

I gave my gaming PC and phone the same local LLM tasks, and only one of them is still in my daily rotation

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