The democratization of tomorrow’s technology
summary
Intel pitches Gaudi DL1 and Gaudi2 as purpose-built training accelerators claiming up to 40–77% better price/performance versus GPUs and nearly 2x throughput versus A100, with integrated 100GbE for scale-out. Concrete deployments include Mobileye (production AV model training), Leidos (frontal chest X‑ray work showing ~60% cost savings), the San Diego Supercomputing Center’s Voyager cluster for researchers, and manufacturing cases that move from 5,000 to five million weld checks a day and cut defects ~90%. Robotics workflows add edge GPUs, cloud orchestration and human-in-the-loop exception handling; Amazon reports ~500k robots deployed.
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chapters (11)
- 0:00Start
- 0:26Democratization of technologies - From cloud to edge
- 11:28SDSC's Voyager
- 13:16Democratizing Al with ease of use, tools, support
- 14:44Gaudi training efficiency + developer productivity
- 18:03Reducing resource cost through ease of use
- 19:20Easing the transition from existing GPU models
- 20:27Al accessible across industries and applications
- 22:03Educating underserved students
- 24:37Trends accelerating automation & robotics
- 29:46Technology drivers
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30mAccelerate deep learning & Habana Gaudi–based Amazon EC2 DL1 instances
31mRealize price-performance advantage for AI
31mRealize price-performance advantage for AI
50mAI acceleration at the edge
09mDemocratizing Access to GPUs for Faster MLAI Innovation with Generative AI
40mFueling the AI Revolution with Gaming
40mAI Factory - Enabling Scalable Innovation & Intelligent Systems
16mUsing AI and Computer Technologies to Enhance IT Infrastructure