Inference Hardware That Keeps Up With the Models: Serving Frontier LLMs on Reconfigurable Silicon

​Frontier LLMs are getting bigger and changing shape faster than the chips built to run them. The result is inference that costs too much, runs too slow, or both.

​Saman Naderiparizi CTO of Elastix.ai will walk through why legacy inference accelerators hit a wall with today’s models, and how reconfigurable silicon changes the math. This is a 30-minute technical talk for people who build, deploy or pay for AI infrastructure.

​What you’ll take away:

• ​Where the bottlenecks are: why fixed-function accelerators struggle as model architectures evolve

• ​How reconfigurable silicon works: dynamic hardware flexibility that adapts execution to the model at runtime

• ​What this means in production: practical approaches to cutting latency and raising throughput at scale

​Who this is for: ML engineers, infrastructure leads, CTOs and technical founders running or evaluating LLM inference.

​Speaker: Saman Naderiparizi, Elastix.ai
Format: 30-minute talk with time for questions
Track: AI Systems & Infrastructure

​AI Systems & Infrastructure day is made possible with the support of Elastix.ai.

​Elastix.ai is a Seattle startup building inference infrastructure for frontier LLMs on reconfigurable silicon. Founded by former Apple and Meta machine learning engineers, Elastix runs large models on off-the-shelf FPGA servers that fit a standard air-cooled rack and plug in through a vLLM back end with an OpenAI-compatible API. The company reports up to 50x lower total cost of ownership and 80% less power than GPU deployments. Learn more at elastix.ai.

​Part of SURF x SWELL Seattle AI Week. Full calendar at luma.com/surfaiweek

FAQ:
​Q: Is there on-site parking?
Yes, secure garage parking is available $10 parking pass is available from the front desk at SURF Incubator on Floor 7.