Ted Weatherford is Vice President of Business Development at Xsight Labs, leveraging over three decades of experience in semiconductor product management, strategic marketing and business development roles. Ted builds commercial dream teams and is known for securing early key customer design-wins and establishing strong differentiated company and product branding. Ted was instrumental in early ARM adoption of mobile handsets into higher performance markets including Base Station digital units, Hyperscale cloud-server and control plane applications in 2010-2015. Ted has spent most of his career eventualizing merchant Ethernet’s early adoption into new markets including the Metro, WAN, DSL/PON Access/Wireless, early Cloud and now currently focused on AI Edge Inference and Gigawatt-scale Token Factory connectivity markets (1996-present). Known for his sincerity, high energy style, optimistic EQ and his enduring middle-class grit, Ted has driven high-rate market growth at both the largest and smallest semiconductor companies (AVGO, INTEL, MTK, CRDO, EZCH, Nephos and Innovium). Ted has enjoyed trusted advisory roles and completed many consulting services for many fabless semiconductor companies over his thirty years in Silicon Valley, California. Ted can be found spending most of his time with his family when he’s not designing thermal-ionic valve amplifiers, Executive Producing art projects (funding music and film) or reading a book while enjoying a slow cigar.
AI doesn’t just need more storage—it needs the right medium. Flash brings the essentials: density, speed, and performance per watt, with lower heat penalties than spinning media at comparable throughput. The question is whether today’s architectures let flash behave like the AI-optimized resource it actually is.
The Open Flash Platform (OFP) initiative is unlocking those inherent flash advantages at rack scale—reducing unnecessary data-path hops, minimizing CPU and DRAM overhead, and improving determinism for latency-sensitive AI pipelines. In this panel, ecosystem leaders will separate what’s real from what’s hype: where OFP delivers immediate wins (throughput-per-watt, density, and predictable performance) and which workloads and deployment patterns will adopt first—from AI training and inference to high-throughput analytics and content pipelines.
Panel Topics:* Eliminating overhead: fewer hops, less CPU/DRAM tax, more predictable latency* AI pressure test: feeding GPUs with consistent throughput and QoS isolation* Deployment models: hyperscale, enterprise, and hybrid designs that simplify operations* What must standardize next: observability