Events for you

This online event covers AI-driven quantum error correction techniques to enable fault-tolerant quantum computing. It focuses on replacing classical decoders with neural architectures that improve logical error rates and discusses engineering challenges for real-time implementation. Attendees interested in quantum computing advancements and AI applications in hardware control will benefit from the session.

This event examines the internal workings of large language model inference serving, focusing on the systems layer between API endpoints and GPU clusters. It is intended for machine learning practitioners interested in understanding bottlenecks, algorithms, and architecture involved in production LLM deployment. Attendees will gain insights into performance optimization for LLM inference in production environments.

This class teaches developers how to use Pi, a lightweight terminal-based coding agent, to create customizable and reusable AI-assisted workflows directly in their project directory. Students will learn installation, authentication, coding sessions, and advanced customization techniques. The event is aimed at developers and engineers interested in practical AI tooling for software projects.

This event explores the architecture, performance, and integration of Kimi K3, a large Mixture-of-Experts AI model by Moonshot AI. It targets developers and researchers interested in advanced AI models and autonomous multi-step code execution. Attendees will learn how to use and incorporate Kimi K3 into their workflows for high-level coding tasks.