ElevenLabs

Nebius is a Nasdaq-listed technology company (NBIS) building full-stack AI infrastructure from its Amsterdam headquarters, with GPU clusters deployed across Europe and the United States. Led by CEO Arkady Volozh, the company operates AI-optimized sustainable data centers - including a facility 60 kilometers from Helsinki and a new Vineland, New Jersey site - and has raised significant capital ($700 million from investors including Accel, NVIDIA, and Orbis). The engineering organization, numbering in the hundreds, maintains deep expertise in world-class infrastructure and runs an in-house AI R&D team that dogfoods the platform to validate it against production ML practitioner requirements. The infrastructure stack spans hyperscaler-scale features with supercomputer-grade performance characteristics. ISEG, Nebius's supercomputer, ranks among the world's most powerful systems. The platform integrates NVIDIA GPUs with NVIDIA InfiniBand networking, exposing workload orchestration through both Kubernetes and Slurm. The operational layer includes standard observability (Prometheus, Grafana), data infrastructure (PostgreSQL, Apache Spark), and ML tooling (MLflow, vLLM, Triton, Ray), with infrastructure-as-code managed via Terraform. This architecture targets the latency, throughput, and reliability requirements of AI training and inference workloads at scale. The company has secured a multi-billion dollar agreement with Microsoft to deliver dedicated AI infrastructure from its Vineland data center. Nebius serves startups, research institutes, and enterprises across healthcare and life sciences, robotics, finance, and entertainment verticals. The technical approach emphasizes production-grade infrastructure that handles the operational complexity of large-scale AI deployments - managing GPU utilization, network bottlenecks, and the cost-performance trade-offs inherent in serving diverse AI workloads from model training through inference serving.

Thinking Machines Lab is a 2025-founded AI research and product company led by Mira Murati, former CTO of OpenAI. The organization addresses a concentration problem: training methods for frontier AI systems have remained largely confined to top labs, constraining public understanding and limiting users' ability to customize systems to specific needs. The team - comprising scientists and engineers who previously built ChatGPT, Character.ai, and contributed to PyTorch - focuses on making AI systems more widely understood, customizable, and generally capable through open science publications and code releases. The company's technical work centers on multimodal systems designed to adapt across the full spectrum of human expertise, with an explicit architectural preference for human–AI collaboration over full autonomy. Their stack includes Python, Rust, PyTorch, React/TypeScript, Kubernetes, and Spark. Development priorities span training and analysis of frontier models, multimodal system design, and foundational ML framework work - reflecting the team's prior experience building widely-deployed products and infrastructure. The operational model emphasizes open science: research findings and implementations are released publicly rather than held proprietary. This approach targets both the customizability bottleneck - where users cannot effectively tune systems to domain-specific requirements - and the knowledge distribution problem that limits informed discourse about frontier model development. Product outputs include multimodal systems and published research artifacts alongside the methodological contributions inherent in their open release practice.