LOADING
This talk explores building a complete self-hosted LLM stack in Rust: Paddler, a distributed load balancer for serving LLMs at scale, and Poet, a static site generator that consumes those LLMs for AI-powered content features.
This talk explores building a complete self-hosted LLM stack in Rust: Paddler, a distributed load balancer for serving LLMs at scale, and Poet, a static site generator that consumes those LLMs for AI-powered content features.
We'll dive into the hard problems: async request routing across dynamic agent fleets, integrating with llama.cpp's C++ codebase, managing KV cache in custom slots, and implementing zero-to-N autoscaling with request buffering. You'll see how Rust's ownership model prevented entire classes of bugs in distributed state management, and walk away with concrete patterns for building and consuming LLM infrastructure in production.
In this talk, we’ll re-create the core ideas of Karpathy’s micrograd, but entirely in Rust.
This talk puts popular Rust rewrites to the test. We'll examine how these tools stack up against their battle-tested predecessors, looking at real-world performance, compilation times, binary sizes, feature completeness, and ecosystem maturity.
This talk explains how Rust debugging actually works: how compiler-generated debuginfo (DWARF/PDB) maps binaries back to source, and how LLDB/GDB interpret that data in practice.
The talk explores how Rust’s type system and memory safety can be leveraged to enforce mandatory guardrails at the infrastructure level, where traditional frameworks often fall short.
