Explore how Mobileye optimized its REM system’s ML inference with AWS Graviton processors and Triton Inference Server, achieving over 2x throughput improvement and significant cost savings for autonomous driving maps.
Together AI’s ATLAS system offers adaptive speculative decoding for up to 400% faster AI inference. It learns from live workloads, overcoming performance degradation from workload drift.
Amazon SageMaker HyperPod now offers managed auto-scaling with Karpenter, optimizing resource utilization and costs for large-scale ML workloads. Enable just-in-time provisioning, scale to zero, and integrate with KEDA for event-driven scaling.
Amazon’s Rufus uses AWS AI chips & parallel decoding to double inference speed, cut costs by 50%, and handle Prime Day traffic seamlessly. Learn how!
Amazon SageMaker LMI v15 boosts LLM performance with the new vLLM V1 engine, async mode, expanded model support & optimized throughput. Deploy cutting-edge LLMs with ease!
The information provided on this website is provided for entertainment purposes only. We make no representations or warranties, expressed or implied, about the information. This includes its completeness, accuracy, adequacy, legality, usefulness, reliability, suitability, and availability. We also make no claims about anything else. Any reliance you place on the information is strictly your own responsibility. We accept payment from advertisers and sponsors with relevant ads. We may recommend products on our website and get paid to advertise them. You can find additional terms in the terms of use.
