CoreWeave powers the world's AI innovations with a cloud platform designed specifically for compute-intensive workloads. Purpose-built from the ground up, the CoreWeave Cloud Platform delivers leading-edge compute at cutting-edge scale and speed optimized for AI, enabling leading AI labs and enterprises to accelerate breakthroughs and shape the future. Trusted by some of the world's leading AI labs and AI enterprises, CoreWeave continues to be the cloud platform provider of choice for those pushing the boundaries of artificial intelligence.
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AI is a fundamentally different technology from anything we've seen before and with it comes a
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new set of requirements training state-of-the-art models and running inference at scale requires
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trillions of simultaneous calculations across billions of parameters this necessitates enormous
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amounts of compute resources and what's more empirical evidence from scaling laws suggests
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that the relationship is exponential meaning orders of magnitude more compute are needed to
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unlock incremental gains in model performance evidently infrastructure isn't just important
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it is a critical enabler of higher performance AI but existing CPU based infrastructure simply
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will not cut it this architecture was built for day-to-day web hosting and database management
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and running SAAS applications workloads that rely on simple fixed logic calculations and lightweight
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processing AI workloads are different they require massively paralleled Matrix based calculations
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that are computationally intensive and need to be able to scale dynamically to match the demands
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of training and inference workloads generalized clouds and their cpub based architectures simply
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cannot meet ai's increasing demands and lack the necessary optimizations across the entire stack to
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unlock the performance required for AI the world needs to rethink the data center traditional air
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cooled facilities often cannot accommodate the extreme power and cooling requirements of modern
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GPU clusters they experience significant retrofitting challenges leading to power
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constraints and inefficient resource utilization you need a new set of managed software Services
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these Legacy Cloud Stacks include layers of software abstraction hypervisors virtual machines
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and unnecessary managed services not built for AI that create latency and consume precious
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processing overhead and because of these built-in layers of abstraction generalized clouds also lack
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the visibility and automation required to rapidly detect and remediate infrastructure issues this is
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a massive limitation given the need to effectively monitor infrastructure Health as components are
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pushed to their limits you need a new set of developer tools and a unified environment for
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running various orchestration Frameworks such as slurm and kubernetes and parallel
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so that AI teams can maximize the efficiency of their infrastructure usage and importantly
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you need tools to automate the provisioning of infrastructure the status quo today is that once
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a customer contracts for accelerated compute capacity the process of manual GPU acceptance
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provisioning and burn and testing can take weeks or months resulting in slower iteration cycles and
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delayed time to market the reality is that up to 65% of effective compute capacity embedded in gpus
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is lost to system inefficiencies creating what we refer to as the mfu model flops utilization
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Gap with AI Enterprises needing every last bit of performance out of their compute closing
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the mfu Gap represents one of the most critical challenges they face and that's exactly what
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we've built CoreWeave to solve with CoreWeave AI teams get up and running faster they get immediate
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access to bleeding edge infrastructure with the software and manage services needed to orchestrate
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Monitor and optimize AI workloads in short they get the performance that they are spending
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billions to achieve AI needs a new Cloud to help close the mfu gap and core weave is that cloud
