Alba Rivas, a passionate Salesforce Developer Advocate, shares her insights on the power of Salesforce's Models API. Discover how this API enables developers to seamlessly integrate large language models via REST API or Apex, eliminating the need for custom code or prompt templates. Alba highlights the critical role of the Einstein Trust Layer in ensuring data security, compliance, and efficient integration with external models. Gain knowledge on AI implementation, including maintaining audit trails, monitoring data for toxicity, and using human feedback for refining AI systems.
We also explore the flexibility and capabilities of the Models API, offering a centralized interface for developers, along with resources like Postman collections, codeLive sessions, and an upcoming Trailhead module to support your journey in mastering generative AI with Salesforce.
Show Highlights:
- Discussion on the Einstein Trust Layer's role in ensuring security, data masking, and compliance for generative AI applications.
- Comparison between using prompt templates and the Models API.
- Importance of maintaining an audit trail.
- Focus on the value of human feedback in refining AI systems and the benefits of a centralized interface for developers.
- Insights into practical AI implementation and the flexibility offered by the Models API.
Links:
- Postman Collection - https://www.postman.com/salesforce-developers/workspace~34382471-0c97-40e5-a206-f947271665c4/collection/onih7sc/models-apis-beta
- Einstein Models API Documentation - https://developer.salesforce.com/docs/einstein/genai/guide/models-api.html
- codeLive: Exploring the New Models API (Beta) - https://www.youtube.com/watch?v=hf95_ghGeNI
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