How do gen AI and traditional AI complement each other?

Gen AI and traditional AI serve different purposes. They can be used separately and together.

Traditional AI, such as classification and ML models, excels at specific tasks like pricing optimization and customer segmentation. These models are designed to be precise, stable and reliable for data-driven tasks.

Gen AI, on the other hand, can be used for efforts like content creation, chatbots and agents, as a virtual assistant and more.

Gen AI complements traditional AI by providing interpretive capabilities. For example:

• Generating informative reports or summaries based on traditional AI results
• A customer-facing chatbot that can route customer requests to traditional AI models tand then answer queries. For example, about package shipping times
• Generating synthetic data
• Analysis of the sentiment behind customer reviews, feedback, social media mentions, etc.
• Automate the labeling of textual data with high accuracy.

See how this works here.

Rather than replacing traditional AI, Gen AI enhances its output, making insights more accessible and adding flexibility to existing systems.

Integrating LLMs with Traditional ML: How, Why & Use Cases

Understand LLMs’ and ML models’ strengths, evaluate the benefits of integration and follow a number of example use cases, from advanced chatbots to synthetic data generation.