We are looking for engineers, researchers and open-source contributors with technical work worth sharing.

Topics include:

• AI and ML systems  

• Model training, inference and serving  

• AI agents and agent infrastructure  

• GPUs, accelerators and compute infrastructure  

• Semiconductor and chip architecture  

• Compilers, runtimes, memory and interconnect  

• Distributed systems and data infrastructure  

• Data centers, energy and efficiency  

• AI safety, evaluation and benchmarking  

• Open-source AI technologies  

• AI for chip and systems design  

• Related research and engineering topics

We particularly value sessions based on real work: original research, benchmarks, experiments, production systems, architecture and implementation lessons, open-source projects, and failures that taught you something useful.

A strong proposal should clearly explain what attendees will learn and, where relevant, include measurements, evidence, code, demonstrations or practical experience.

We welcome technical talks for intermediate to expert audiences from academia, industry, startups and the open-source community.

Sales pitches and primarily promotional product presentations will NOT be accepted.

Submissions are reviewed on a rolling basis, so we encourage you to submit early.