Minimize IP liability of third-party models with Provenance and Attribution

Popular LLMs like Claude 3.5 Sonnet and GPT-4o are trained on vast amounts of data and have the potential to generate nonpermissive code.

In our next Tabnine Live, we’ll showcase our latest feature: Provenance and Attribution that drastically reduces the risk of IP infringement when using models like Anthropic’s Claude, OpenAI’s GPT-4o, and Cohere’s Command R+ for software development.

Tabnine checks the code generated within our AI chat against the publicly visible code on GitHub, flags any matches, and references the source repository and its license type. This critical information makes it easier to review code suggestions and decide if they meet your specific requirements and policies.

We’ll do a live demo and Q&A that covers:

• How the Provenance and Attribution feature works in Tabnine
• Running a few prompts in AI chat to demonstrate how third-party models can potentially reproduce publicly available open source code
• How Tabnine flags any matches it finds with publicly visible code on GitHub and references its source repo and license type
• Upcoming features that offer more granular control over Provenance and Attribution