Open Source: What's Next
summary
Panelists argue that open source already underpins >90% of shipped software and that there are >100 million projects, yet AI breaks assumptions: the OSI open-source AI definition v1 is useful but incomplete because it omits the crucial issue of training data provenance. Legal detail: US copyright treats 100% machine-generated code as uncopyrightable unless human edits add originality. Practical fixes discussed include using LLMs/Copilot carefully, running SCA tools like Black Duck and cargo audits, creating a software bill of materials and EU CRA–driven tooling.
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chapters (7)
- 0:00Introduction and panel setup
- 1:51Open source evolution and business impact
- 6:09Open source AI definition and challenges
- 16:32Corporate adoption of AI in products
- 27:49Open source governance in companies
- 39:52Education and open source offices
- 44:31Closing thoughts and future outlook
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