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AI Infrastructure

118 summarised stories about AI Infrastructure, each linking back to the original source. Browse all topics →

Monday, 4 May 2026

AI inference just plays by different rules

The Register 2 months ago

AI agents performing inference workloads generate unpredictable, concurrent data access patterns that overwhelm cloud storage systems designed for human-speed applications, requiring architectures that decouple performance from capacity. AWS EBS volumes experience burst credit exhaustion and latency spikes from 1 millisecond to 50+ milliseconds when AI inference traffic overwhelms the storage layer, as demonstrated by a fintech e-commerce platform whose AI shopping assistant caused a system-wide outage within 15 minutes of launch. Organizations must architect for extreme tail latency performance (p99/p999 under mixed load) and adopt software-defined storage solutions that can deliver consistent sub-millisecond latency even during concurrent OLTP and inference workloads, rather than attempting to scale through read replicas or additional IOPS provisioning.

Foundational research powering efficient inference at scale

Together AI 2 months ago

Together AI describes how inference costs dominate production AI systems at 80-90% of total lifetime cost, requiring optimization across latency, throughput, concurrency, and scheduling dimensions. The company has developed a full-stack approach including techniques like adaptive speculative decoding (Aurora delivering up to 1.25x speedup), custom hardware optimization on NVIDIA Blackwell systems, and intelligent batching that ship research to production within weeks. Better inference efficiency directly improves margins for AI-native companies by enabling more requests per GPU-hour and expanding economically viable use cases.