The Hidden Toll of Generative AI: Cutting Costs Without Cutting Corners
The five best practices for organizations to optimize generative AI costs as they scale from pilots to production. These include being objective about tradeoffs between model accuracy, performance, and costs; creating an AI model garden to promote choice and transparency; balancing upfront and operational costs in model customization; understanding the complexities and costs of self-hosting; and embracing guided prompt design to enhance efficiency and reduce costs.
Arun Chandrasekaran writes for SiliconANGLE
Organizations transitioning from gen AI pilots to production experience a rude awakening when it comes to costs. Creating a production-ready gen AI system can be orders of magnitude more expensive than running a pilot.
By implementing these strategies, organizations can maximize their return on AI investments while maintaining control over expenses. Regular reviews and a culture of accountability are also emphasized for ongoing cost optimization.