Maximizing GPU Utilization: HTX's AI Infrastructure Strategy | WEKA

How does HTX maximize GPU utilization across its AI infrastructure? Chief Innovation Officer NG Pan Yong shares his strategy. https://www.weka.io/video/keeping-gpus-busy-is-the-real-ai-infrastructure-kpi WEKA's Betsy Chernoff sits down with NG Pan Yong, Chief Innovation Officer at HTX, to talk about getting the most from a significant GPU investment. For HTX, an idle GPU is a real concern, so the team looks for low latency, high throughput data solutions for everything from checkpointing during training to KV caching and hosting AI models for inference. Pan Yong also explains why storage is no longer a second-class citizen in the era of accelerated computing, and why the criterion that matters most in a technology partner is innovation: working with a data platform operating at the frontier of AI. *CHAPTERS* 0:00 Meet NG Pan Yong, Chief Innovation Officer at HTX 0:16 Maximizing the GPU investment 0:47 Keeping GPUs hydrated: the two KPIs 1:00 Storage is no longer a second-class citizen 1:52 Shortening the circuit between data and the brain 2:04 What HTX looks for in a storage partner Learn more: - Request a demo: https://www.weka.io/lp/cloud-demo/ - Subscribe for more AI infrastructure content: https://www.youtube.com/@WekaIO?sub_confirmation=1 About WEKA: WEKA NeuralMesh™ is the data platform built for AI, delivering the performance and efficiency needed to run agentic and LLM workloads at production scale. #GPUUtilization #WEKA #AIInfrastructure #DataStorage #GPUUtilization #WEKA #AIInfrastructure #DataStorage 👉 *Connect with WEKA:* Website: https://www.weka.io?utm_source=youtube&utm_medium=social&utm_campaign=brand LinkedIn: https://www.linkedin.com/company/weka-io?utm_source=youtube&utm_medium=social&utm_campaign= X: https://x.com/weka?utm_source=youtube&utm_medium=social&utm_campaign=inference