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Iterate.ai's new inference engine, Lifeboat, addresses the critical bottleneck of GPU memory saturation caused by high-concurrency AI agent workloads. By implementing fair scheduling and optimized key-value caching, the software enables a single Blackwell GPU to sustain up to six times more concurrent sessions compared to standard engines without sacrificing model precision or security. This advancement is particularly relevant for enterprises requiring confidential computing to run complex agent workflows on-premises while maximizing hardware efficiency.
Exclusive: Iterate.ai’s Lifeboat runs up to six times more AI agent sessions per GPU
Enterprise artificial intelligence software company Iterate Studio Inc. today launched Lifeboat, an inference engine for large language models that has confidential computing built in. Iterate.ai says the software fits two to six times as many concurrent AI agent sessions on each graphics processing unit. Lifeboat is seeking to take on a memory problem that agents […] The post Exclusive: Iterate.ai’s Lifeboat runs up to six times more AI agent sessions per GPU appeared first on SiliconANGLE.
Exclusive: Iterate.ai’s Lifeboat runs up to six times more AI agent sessions per GPU Enterprise artificial intelligence software company Iterate Studio Inc. today launched Lifeboat, an inference engine for large language models that has confidential computing built in. Iterate.ai says the software fits two to six times as many concurrent AI agent sessions on each graphics processing unit. Lifeboat is seeking to take on a memory problem that agents create at scale. A chatbot…
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