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Modular's Chief Scientist Abdul Dakkak discusses at AI Engineer World's Fair 2026 why the company rebuilt its inference stack from scratch to run efficiently across a fragmented landscape of chips and accelerators.
The article argues that the output of AI coding agents is straining traditional CI systems, creating a bottleneck that cannot be fixed by hardware alone, and promotes Dagger as a smarter software stack solution.
The PyTorch Conference North America in 2026 will feature a talk by Chris Lattner on a unified software stack to address fragmentation in the AI ecosystem, with registration details provided.
Alibaba's T-Head open-sourced SAIL, the software stack for its Zhenwu AI chips, at WAIC in Shanghai. The move aims to lower the barrier for developers to migrate from Nvidia's CUDA ecosystem.
NVIDIA's full-stack inference software, codesigned with hardware, has reduced token costs by up to 5x on the Blackwell platform in just one month, enabling lower cost per token for AI factories. Companies like Baseten, Cognition, Deep Infra, and Together AI are using the stack to optimize inference performance.
Comparison of inference engine performance on different hardware: moving from baseline to vLLM with TP=2 on 2x RTX 3090s improves from ~14.5 tok/s to ~64 tok/s, and on RTX PRO 6000 moving to Sglang improves from ~32 tok/s to ~110 tok/s. Recommends vLLM/Sglang for CUDA/multi-GPU and llama.cpp for edge devices.
An analysis of the software stack behind autonomous robots, breaking down the components from perception to cloud support, and highlighting that most tools are open-source.
The article introduces an open-source AI agent stack comprising OpenClaw, Hermes, and Paperclip, describing it as a comprehensive setup that functions like an automated AI business.