AI Infrastructure Digest · Apr 5 Daily Digest
Inference Serving Deep Dives
- 🔥 vLLM and PagedAttention: Open-source library vLLM from UC Berkeley solves the KV Cache memory crisis for...

Created by Rachel Brooks
Daily highlights of applied AI infrastructure research for large-scale training and serving
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SSD revolutionizes LLM coding by distilling from raw self-outputs, bypassing teachers or RL – ideal for efficient production scaling.
Screening mechanism ditches softmax redistribution by thresholding keys directly, enabling absolute query-key relevance without global competition.
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vLLM revolutionizes LLM inference by tackling KV cache fragmentation, the silent killer wasting 60-80% of GPU memory via over-provisioning.
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Hands-on guide to deploying LLMs at scale like FAANG teams on Kubernetes:
Supermicro unpacks its powerful 8U AI/HPC platforms for NVIDIA Blackwell:
Sony's multi-tenant GPU cluster accelerates AI and visual computing for PlayStation consoles and game studios, training NVIDIA GPU models for...
Google's AI power crunch drives a bold shift:
Microsoft launches MAI foundational models to rival OpenAI on performance and price, offering cheaper proprietary options for transcription, voice,...
Key optimizations boosting GPU utilization for LLM serving:
--gpu-memory-utilization to split VRAM and run...Key angles on running enterprise-scale Kubernetes for GPU AI services:
New video guide for deploying Nvidia's NemoClaw agentic AI in the cloud:
Ultra-efficient 1-bit LLMs breakthrough: PrismML's Bonsai series, trained from scratch on BitNet architecture, revives Microsoft's BitNet for local...
Intuit's AI agents serve 3 million customers with 80.5% retention, automating bookkeeping tasks like reconciliation and payroll.