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Callosum (London) raised $10.25M for multi-vendor AI chip orchestration — unifying GPUs, TPUs, and custom silicon — founded by Cambridge neuroscientists. Feb 2026.
Callosum is a London-based AI infrastructure startup founded by Cambridge neuroscientists who applied their understanding of how the brain orchestrates computation across specialized regions to the problem of multi-vendor AI chip coordination. The company's name references the corpus callosum—the brain structure that connects and coordinates the two cerebral hemispheres—reflecting its technical mission: enabling different AI accelerators from different vendors to work together efficiently as a unified compute resource. Callosum addresses a real pain point for enterprises and cloud providers that now operate heterogeneous fleets of GPUs, TPUs, and custom silicon.\n\nCallosum's orchestration platform abstracts over hardware differences between AI chip vendors, allowing workloads to be scheduled and balanced across NVIDIA, AMD, Intel, and custom accelerators without manual optimization for each chip type. This is particularly valuable as enterprises seek to reduce vendor lock-in and optimize cost by mixing and matching hardware. The platform targets ML engineering teams and infrastructure operators at companies running large-scale AI training and inference workloads who need to maximize utilization across a diverse hardware estate.\n\nCallosum raised $10.25M in February 2026 in a seed or early-stage round, providing capital to build out its engineering team and deepen integrations with major chip platforms. While early in its journey, the company operates at a genuinely important intersection: as AI chip diversity grows and no single vendor dominates all workloads, the need for intelligent multi-vendor orchestration will only increase. Callosum's neuroscience-rooted technical vision and Cambridge pedigree give it a distinctive angle in the competitive AI infrastructure space.
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
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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