The global artificial intelligence in the sports market was valued at $1.4 billion in 2020 and is projected to reach $19.2 billion by 2030, growing at a CAGR of 30.3% from 2021 to 2030.

rimarily, we are leveraging AWS EC2 DL1 instances to train 2D and 3D models for 3DAT pipelines. We are consistently seeing cost savings compared to existing GPU-based instances across model types, enabling us to achieve much better Time-to-Market for existing models or training much larger and more complex models.

Amazon DL1 instances with Gaudi accelerators offer the best price-performance savings compared to other GPU offerings in the market.

Intel® OpenVINO™ is an inference solution that optimizes and accelerates the computation of AI workloads on Intel® hardware.

The FP32-optimized IR models outperformed using OpenVINO™ runtime in terms of throughput compared to other Deep Learning framework runtimes on the same Intel® hardware.

As a next step, the FP32 IR model was further optimized and converted to lower 8-bit precision with post-training quantization using the default quantization algorithm from the Post Training Optimization Tool (POT) from OpenVINO™ toolkit.

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