Open-source AI is revolutionizing the perception of artificial intelligence, as exemplified by DeepSeek and Red Hat's innovative strategies. Red Hat merges its commitment to open-source with the complexities of modern AI, focusing on practical enterprise solutions rather than theoretical AGI aspirations. At the Linux Foundation Members Summit, concerns were raised about the ambiguities in 'open-source AI,' highlighting inadequate transparency in AI training data and model weights. Licenses labeled 'open-source' are sometimes restrictive, raising ethical questions about accessibility and legitimacy in the AI industry.
Just look at DeepSeek, the Chinese open-source program that blew the financial doors off the AI industry.
Red Hat balances practical enterprise needs with what AI can deliver today, rather than chasing artificial general intelligence (AGI) dreams.
What is the analog to [source code] for AI? That is not clear. Some people believe training data has to be open, but that's highly impractical for LLMs.
These fake open-source programs include Meta's LLama, and Fontana criticizes this trend, noting that many licenses discriminate against fields of endeavor.
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