Unraveling the Database Dilemma
in Powering Enterprise-Level
Generative AI
Networking Dinner & Cocktails
at The Great Room, Centennial Tower, Singapore

Here’s what we discussed:

In the era of OpenAI’s ChatGPT, Google’s Bard & Gemini, and Anthropic’s Claude, the boundaries of artificial intelligence are being continually pushed. Enterprises are bracing for the new opportunities and challenges this presents… Perhaps most significantly, they are grappling with integrating large language models (LLMs) with their proprietary data, necessitating a robust technical underpinning.

Participants joined us for an insightful discussion where we unraveled the complexities of database selection, collaborative innovation, and ethical AI, paving the way for a future where technology and integrity seamlessly coexist.

We learned:

• The realm of ‘private AI’ and its pivotal role in crafting advanced AI applications tailored to the distinct needs of enterprises.
• The fusion of LLMs with proprietary data unveils the pathway for enterprises to harness their extensive data reservoirs for training and fine-tuning LLMs.
• Domain-specific contexts but also yields more precise insights.
• Decision framework for choosing the ideal database for generative AI.
• The transformative power of collaboration and knowledge exchange among organizations unlocks avenues to elevate the performance and comprehension of LLMs.
• Ethical considerations and data privacy standards for cutting-edge AI applications.