Rust developers, like all developers, are nervous about their worth in an AI world. This talk gives us reasons to be optimistic and opens a vista where we are enhanced by AI rather than replaced. As AI becomes increasingly integrated into software development, we face questions about how our programming languages and tools should evolve: questions that don’t yet have clear answers.

Rather than prescribing solutions, this talk explores the open questions and possible directions that developers and tooling authors should be thinking about.

As the pace of change is extremely fast, I believe we’ll see many new libraries in the next six months, so I’m keeping this description short (there will definitely be new material).

The general idea is to help developers get acquainted with the changes in this rapidly evolving field from a practical point of view. As navigating the growing Rust AI landscape can be challenging. The AI landscape is evolving rapidly, with new libraries emerging all the time. In this talk, we'll explore the current state of AI development in Rust, highlighting key crates, frameworks, and tools. Covering the essentials from ML and NLP to integrating LLMs and agent-based automation.

In short: what we should do to make AI development great again in Rust.

I really want to make this talk something statistical and analytical, with plenty of infographics so people can take photos of the slides and have a kind of visual cheat sheet showing the current state of the AI landscape. The idea is to help visitors quickly understand where Rust AI libraries stand today, so they don’t have to spend time googling later (and maybe even inspire someone to spot open gaps and create new open-source solutions)