APC 技術ブログ


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Simplify GenAI App Development with Secure, Custom AI Agents


In the session titled "Introduction to AI Agent Workflows and Tools," strategies for streamlining the development of generative AI applications were showcased. The speakers, Atriti from Mosaic AI and Bilal, a Product Manager from AI Influence, began with a discussion on the fundamental concepts of AI agents, enumerated their benefits, and delved into their configuration.

Bilal highlighted the challenges faced during the deployment of these agents and introduced several new features from Databricks to simplify the deployment process. This section of the presentation aimed to bridge the gap between theoretical knowledge of AI agents and practical implementations in GenAI app development.

Attendees gained a comprehensive understanding of how AI agents can significantly optimize the GenAI app development process. Furthermore, they learned about the technical components constituting AI agents, explored cutting-edge tools to aid their deployment, and ensured a smoother development experience.

Practical Demonstrations and Comparisons

This session introduced the concept of AI agents utilizing specific tools for efficient access to necessary information. Through this automated process, AI agents can retrieve data from tools and generate responses that appear naturally composed.

During the demonstration, a scenario was presented where the facilitator requested the AI agent to provide the schedule for the upcoming seven days. The agent not only managed this unexpected request effectively but also accurately summarized the weekly schedule. Moreover, the capability of the agent to intelligently handle more complex queries was demonstrated.

This part of the session highlighted the AI agent's ability to seamlessly integrate with existing tools and rapidly extract and convey accurate information. It showed the agents' flexibility and proficiency in handling both anticipated requests and complex user queries.

These demonstrations confirmed the advanced capabilities of AI agents and deepened the understanding of their practical applications in real scenarios. Observing these agents operate in real-time provided valuable insights into the potential and efficacy of AI technologies for future enhancements.

Agent Metrics, Quality, and Governance

In the presentation titled "Simplifying GenAI App Development with Secure, Custom AI Agents," the evaluation of metrics, quality, and governance of AI agents was revealed to be of central importance in streamlining effective development of GenAI applications. Here, we introduce the key insights collected and discussed.

Agent Metrics

The primary performance metrics for AI agents include monitoring the efficiency of actions chosen by the agent and assessing the accuracy of the tool selection process to ensure optimal outcomes. By understanding the trajectory of the agent's navigation paths and analyzing the intermediate values relayed to tools, developers can enhance the decision-making processes within AI agents.

Agent Quality

Maintaining the quality of AI agents is complex due to their interactions with various components and data sources. Careful checking of the intermediate processes handled by agents is essential. Incorrect tool selection or inaccurate data interpretation by the agent could significantly degrade the quality of the outputs. Hence, continuous monitoring and intervention mechanisms are crucial.

Agent Governance

The governance of AI agents includes setting clear rules on which parts of the system the agent can manage autonomously and addressing potential delays and security risks that arise. It is crucial to ensure transparency in how agents integrate and interact with enterprise data sources and long-lived models (LLMs).

Implementation Challenges

Physical deployment of AI agents on CPUs, which effectively coordinate with corporate data sources and LLMs, presents various technical barriers. Addressing these challenges requires a comprehensive strategy focused on regular evaluation and optimization of the agent's operational performance, aiming for seamless integration to support efficient and secure application development.

Addressing these focal points helps recognize the complexity and importance of metrics, quality, and governance in developing GenAI applications using AI agents. The session emphasized the importance of careful selection of paths and tools that lead to successful projects within this innovative technological landscape.

About the special site during DAIS

This year, we have prepared a special site to report on the session contents and the situation from the DAIS site! We plan to update the blog every day during DAIS, so please take a look.