Session Outline
The vast majority of today’s generative AI projects will fail. Not because of inherent flaws in large language models (LLMs), but because of misconceptions about how to use them. And the lack of capabilities needed to successfully design, develop, and operationalize genAI-driven applications. In this session with former industry analyst, Dr. Kjell Carlsson, at the Data Innovation Summit 2024, we debunk the most harmful myths that set generative AI projects up for failure. We look at key elements for a strategy that leverages the interest and excitement around generative AI.
Key Takeaways
- Pure GenAI applications don’t exist; rather, they thrive when integrated with Predictive AI, enhancing real-world use cases by combining generative capabilities with predictive insights.
- In comparing LLMOps to MLOps, it becomes evident that a unified approach is essential. Integrating both LLMOps and MLOps ensures seamless management and deployment of language models alongside other machine learning systems, streamlining processes and maximizing efficiency in AI development pipelines.
- Navigating GenAI through disillusionment requires strategic approaches. Emphasizing incremental implementation, fostering realistic expectations, and prioritizing user-centric design can mitigate disillusionment by demonstrating tangible benefits and fostering trust in GenAI’s capabilities.
Tune into on-site interview at the summit, where we had the pleasure of speaking and hearing more from Dr. Kjell!