I see generative AI as a revolution more than just a new technology. It has taken AI out of the shadows of theory and into practical applications across almost every aspect of how we work, live, create and learn.
This issue, as well as the heated debates about the openness of AI, leads to the million-dollar question that could change the trajectory of how AI is developed and consumed: Should large language models that form the foundation of generative AI be offered as open-source or proprietary software? In addition to AI, open source is available for operating systems, web servers and applications. It can be traced back to the early days of computing, when sharing source code and collaborative development were common practices among researchers and programmers. Yet, it wasn’t until much later, whenin 1991 and invited contributions from developers worldwide, that open source officially took hold.
For enterprises using free, open-source models, however, they can gain the freedom to use the models as they desire, but often don’t have the AI talent or resources to effectively tailor them, establish governance or train employees for their effective use. Integrating open-source generative AI into the enterprise can be a major undertaking that could compromise data privacy and security and increase corporate risk when there is no strategic plan or support through partnerships.
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