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Learn about open source AI alternatives to proprietary solutions through this 46-minute conference talk that explores IBM's Granite and Granite-Code foundational models. Discover why transparency and legal protection matter in AI adoption, and understand the risks of using closed-source AI systems with unclear legal frameworks. Explore how Granite models provide externally verifiable, legally backed AI solutions with full documentation and IBM legal support. Get hands-on experience setting up a local "co-pilot" experience using purely open source AI tools, and learn to enhance the Granite foundational model with new knowledge through InstructLab. Understand the technical architecture behind transparent AI systems, examine the training methodologies documented in published papers, and gain practical skills for contributing to genuinely open AI development. Compare the legal and technical advantages of open source AI versus proprietary alternatives, and discover how to build AI solutions that prioritize transparency, legal clarity, and community collaboration in the rapidly evolving AI landscape.
