Optimizing Machine Learning Inference at Scale

We optimize machine learning inference workloads for multiple applications in cloud or enterprise data centers and in edge applications.  Our products, expertise and IP ensure all available compute resources are optimized for cost, throughput, latency and energy.

Recommendation Systems

Recommendation models power the recommendation systems behind search, adverts & personalized content.  Performance of these models is often constrained by system memory.  We can eliminate this constraint, increasing compute density by up to 10x on existing infrastructure.

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Solutions for a Wide Range of ML Applications

To meet the huge increase in demand for AI, technologies must scale efficiently in order to meet strict latency and performance requirements while keeping the total cost of ownership and total power consumption low. Our low latency, high throughput solutions ensure efficient implementation of ML inference at scale.

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