Watch the talks: Videos from Nebius AI Cloud Unveiled meetup

Nebius shared insights into building AI-compatible cloud infrastructures, highlighting the hardware and software challenges faced, decision-making processes, and architectural strategies implemented. NVIDIA's Adam Grzywaczewski provided guidance on selecting optimal architectures for AI projects, while Grigorii Rochev introduced Soperator, a Kubernetes operator for Slurm that facilitates workload management by integrating Slurm with Kubernetes and offering features like autoscaling. Vasily Pantyukhin shared lessons learned from scaling AI models, aiming to help others avoid common pitfalls. Boris Yangel discussed enhancing agentic systems through test-time computation by combining guided search with agent inference. Meanwhile, Nebius AI Studio's development, focusing on its Inference Service for GenAI models, was elaborated on by Nikita Vdovushkin and Roman Gaev, who offered advice on selecting appropriate inference providers and models.

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