Enterprises are increasingly turning to AI to tackle their most pressing business challenges but it requires a strategic approach and deep understanding of how to integrate them into existing business workflows. In this video, Aaron Vermeersch, LLM Engineer at Qarik, talks about how the company is harnessing LLMs to address enterprise business challenges. He says, “It’s about blending traditional software, knowledge and technology with AI and knowing how to juggle between them, and where to draw that line.”

Harnessing generative AI to address high-impact business challenges

• Vermeersch explains how Qarik is leveraging generative AI to address high-impact business challenges with their GenAI accelerator.
• Qarik works through their customers’ use cases and entire business workflow to address their AI needs.

Deploying generative AI in business scenarios

• Vermeersch discusses the key insights Qarik has gained from deploying generative AI in business scenarios.
• Vermeersch emphasizes the need to clearly understand the data and to identify the key piece of the use case that requires an LLM to effectively deploy the AI model into business scenarios.

Effective prompt strategies for large language models

• Vermeersch discusses effective prompt strategies for LLMs, emphasizing the importance of tailoring prompts to specific use cases.

Large language models in enterprise use cases

• In the future, it is predicted that enterprises will increasingly see the value in LLMs to address tasks specific to enterprises’ workflows.
• Vermeersch believes that models will improve and require less tuning in 2024 to get the accuracies needed to address the use case.
• The cost of putting the models into production is also predicted to decrease with open-source models starting to meet proprietary levels.

Guest: Aaron Vermeersch (LinkedIn)
Company: Qarik Group (Twitter)
Show: Let’s Talk

This summary was written by Emily Nicholls.