Evaluating AI Models, Unlocking Unstructured Data, and Achieving Reliability w/ Ben Kus
May 23, 2024
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Tech expert and Box CTO, Ben Kus, discusses AI's impact on productivity and decision-making in organizations, strategies for ensuring reliability, challenges of AI change management, evaluating AI quality, unlocking unstructured data, and the potential of AI agents for user experience.
Customizing prompts per AI model is crucial for accurate outputs.
Testing, iterating, and evaluating AI strategies are vital for successful AI product development.
Balancing safety, security, and innovation is key in managing AI implementations.
Deep dives
Challenges of Customizing Prompts per Model
In the podcast episode, the challenges of dealing with multiple AI models were discussed. Customizing prompts per model was highlighted as a crucial task, as even similar-looking models with similar outputs have different parameter needs and prompts. The speaker emphasized the importance of managing version history and control over prompts to ensure accurate outputs. An example illustrated how adding or removing a period in a prompt could significantly impact the model's response, indicating the need for precise customization.
Building AI Products at Scale
The episode delved into the intricacies of building AI products at scale, particularly in an enterprise setting. The guest speaker provided examples from Box on allowing customers to utilize various models in different scenarios. The discussion touched upon integrating AI capabilities across product stacks and the associated technical challenges. Additionally, the conversation explored AI operations, emphasizing the importance of testing, iterating, evaluating, and implementing AI strategies effectively.
Balancing Safety, Security, and Innovation in AI Implementation
The podcast covered the complex task of balancing safety, security, and innovation in AI implementations. The conversation highlighted the potential revolution in handling unstructured data, presenting new opportunities for products like Box. It emphasized the importance of maintaining a balance between safety and security protocols while keeping up with rapid AI advancements. Challenges in managing change and evaluating AI models were discussed, pointing towards the need for effective change management strategies amidst evolving AI capabilities and uncertainties.
The Evolution of AI in Interpreting Unstructured Data
AI is increasingly being used to process unstructured data efficiently. The podcast discussed the importance of having structured data upfront to facilitate AI-powered queries. One key concept mentioned is the 'multi doc QA' approach, where AI can extract specific information from a batch of unstructured data swiftly. The discussion highlighted the significance of combining structured and unstructured data techniques to derive business value effectively.
Enhancing AI Interactions through Agent-like Behavior
The conversation delved into the idea of enhancing AI interactions by implementing agent-like behavior. The potential of iterative processes in refining AI responses was emphasized. By allowing AI to iterate, seek clarification, and generate improved responses over multiple attempts, the quality and reliability of AI-generated insights can be significantly enhanced. The podcast explored the importance of evolving user experience to accommodate iterative AI interactions for more effective engagement and problem-solving.
Evaluating AI Models, Unlocking Unstructured Data, and Achieving Reliability w/ Ben Kus
Today on "Unsolicited Feedback," Fareed Mosavat dives deep into the evolving landscape of artificial intelligence with tech expert and Box CTO, Ben Kus. As AI continues to reshape industries, understanding its core mechanisms and potential applications has never been more critical. Ben sheds light on how AI can enhance productivity and decision-making within organizations while also sharing technical strategies he’s implemented to ensure reliability for Box’s enterprise customers.
