Agentic AI Demands Less Recomputation
As practioners of AI shifts to the use of autonomous agents and production scale inference, KV cache offloading has become a critical solution to reduce high cost of GPU recomputation and the time required for autonomous agents that can set goals, plan, and execute tasks with minimal human intervention. This emerging technology has the potential to revolutionize various industries by automating complex processes and optimizing workflows. Industries including customer service, financial services, supply chain management, software development and healthcare, just to name a few.
Demystifying KV Cache Webinar
This week, we broadcasted a webinar on KV Cache with VAST Data Director of AI Architecture Anat Heilper and Tensormesh CTO and Co-Founder Yihua Chen.
If you missed it, watch the on-demand version here.
New KB Repository for KV Cache is Live!
Additionally, our wonderful KV$ gurus, @Anat Heilper and @Gal Lapid have created a Knowledge Brief portal on KV$. Currently, there are 6 articles, with more to come.
See what our experts have written up with deployment guidance across different GPU platforms and inference optimization frameworks KVCache
Bookmark this because we’ll update it regularly!