Thinking Machines Lab vs Skild AI
Side-by-side comparison of AI visibility scores, market position, and capabilities
NVIDIA strategic investment and 1GW Vera Rubin compute deal in Mar 2026; reportedly seeking $5B at $50B. Mira Murati's lab for customizable frontier models.
About
Thinking Machines Lab was founded by Mira Murati, who served as Chief Technology Officer of OpenAI before departing in 2024. Murati's tenure at OpenAI oversaw the development and launch of GPT-4, DALL-E, and ChatGPT, giving her unmatched firsthand experience with the technical and organizational challenges of frontier AI development. She founded Thinking Machines Lab with the mission of building AI systems that are both highly capable and deeply aligned with human values and intent.\n\nThinking Machines Lab operates as an AI research organization focused on developing next-generation foundation models and the scientific frameworks needed to make powerful AI systems more reliable, interpretable, and beneficial. The company has assembled a team of researchers from leading AI institutions and is building the compute infrastructure necessary for frontier model training. It secured a multi-year compute agreement with NVIDIA, ensuring access to the GPU capacity required to compete at the frontier of AI research.\n\nThe company raised $2 billion at a $12 billion valuation, with participation from Andreessen Horowitz, NVIDIA, and AMD — a capital raise that ranks among the largest first rounds in technology history. The involvement of both major AI chip vendors as strategic investors signals deep alignment between Thinking Machines Lab's compute roadmap and the hardware ecosystem. With Murati's profile, the caliber of its investor base, and its frontier research mandate, Thinking Machines Lab is positioned as one of the most closely watched AI labs in the post-ChatGPT era.
Universal robot brain startup raised $1.4B Series C at $14B valuation in Jan 2026 led by SoftBank with Nvidia and Bezos; $30M 2025 revenue; deployed at Foxconn
About
Skild AI is building a universal robot brain — a foundation model for physical intelligence that can power a broad range of robot types without requiring task-specific training for each deployment. Founded to solve the fragmentation problem in robotics AI, where every robot type and task requires separate model development, Skild's approach trains a single generalist model on diverse robotic data and fine-tunes it rapidly for specific deployments. The company was founded by robotics AI researchers who identified the model reuse gap as the primary barrier to scalable robot deployment.\n\nSkild's generalist robot model has been deployed across more than 30 distinct robot types — spanning manipulation arms, mobile platforms, and humanoid form factors — demonstrating the cross-hardware generalization that most robot AI systems lack. The platform targets robotics manufacturers, logistics operators, and industrial automation companies that need AI-capable robots but lack the internal ML infrastructure to develop foundation models themselves. By offering a model-as-a-service layer, Skild enables robot OEMs and systems integrators to add AI capabilities without building the underlying research infrastructure.\n\nSkild AI raised a $1.4 billion Series C in January 2026 at a $14 billion valuation, led by SoftBank with co-investment from NVIDIA and Jeff Bezos. The round was one of the largest in robotics AI history and reflects institutional conviction in the physical AI market's scale. With $30 million in 2025 revenue and accelerating enterprise deployments, Skild is building the financial foundation to match its valuation. The SoftBank-NVIDIA investor combination positions Skild at the center of the global robotics deployment wave.
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