The correct options are Copilot may generate suggestions that resemble patterns found in public repositories and occasionally the output can be similar to existing public code and The models are trained on publicly available code and they are not updated using a customer's private repositories.

Copilot is trained on large amounts of public code and natural language so it can produce suggestions that reflect common idioms and patterns. This means some suggestions can be similar to well known public snippets. Organizations can enable the matching public code filter to reduce the chance of suggestions that are too close to publicly available code and this supports safer adoption under internal compliance standards.

For business and enterprise customers GitHub states that private repositories, prompts, and completions are not used to train the underlying models. Prompts and related data are processed to operate and secure the service and retention is governed by documented privacy commitments and enterprise controls which supports GDPR compliance when combined with the GitHub Data Protection Agreement and standard contractual safeguards.

Copilot always encrypts your source code on the local device and also in transit to block any unauthorized viewing is incorrect because Copilot does not introduce special local encryption of your files and your code remains stored as you normally manage it. Network communications use industry standard encryption and GitHub encrypts data at rest in its systems, yet the absolute claim about always encrypting your local source code is not how Copilot functions.

Cloud DLP is incorrect because it is a Google Cloud service and it is not part of GitHub Copilot or its data processing approach.

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