Optimizing Data Architecture for Generative AI
The key to unlocking the full potential of your data architecture for generative AI models lies in making efficient use of high-quality, diverse training data. Overcoming challenges in data acquisition, storage, and processing is vital. As models and data grow, costs and complexity rise, impacting startups’ focus on innovation, personalization, automation, efficiency, and entertainment.
Join experts from Nvidia, Run:ai and WEKA and learn how you can:
- Maximize GPU utilization in on-premises, cloud, and hybrid environments
- Simplify orchestration and acceleration for Al Workloads
- Manage your data and storage intelligently and effectively
- Optimize your infrastructure for generative AI and reduce costs
The key to unlocking the full potential of your data architecture for generative AI models lies in making efficient use of high-quality, diverse training data. Overcoming challenges in data acquisition, storage, and processing is vital. As models and data grow, costs and complexity rise, impacting startups’ focus on innovation, personalization, automation, efficiency, and entertainment.
Join experts from Nvidia, Run:ai and WEKA and learn how you can:
- Maximize GPU utilization in on-premises, cloud, and hybrid environments
- Simplify orchestration and acceleration for Al Workloads
- Manage your data and storage intelligently and effectively
- Optimize your infrastructure for generative AI and reduce costs
Speakers
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David Boyd
European Alliances Manager, Storage Partners
NVIDIA -
Gijsbert Janssen van Doorn
Director Product Marketing
Run:AI -
Derek Burke
Regional Sales Manager
WEKA -
Steve Knight
Director, EMEA Marketing
WEKA