#232: Open vs Closed AI
In this email:
What is open source vs closed source AI?
The good and bad of open source
The good and bad of closed source
Open vs Closed
With much debate on the potential benefit and harm of looming generative AI models, the industry-wide debate continues: should AI be “open”?
Making AI models open refers to the practice of publicly sharing the models, training data sources, underlying code, etc.
Some key examples of open software (outside of AI) are Python (the programming language), Firefox, Ethereum, etc. (Ironically, Open AI is closed source)
Open source: the Good and Bad
Google has been a critical player in open source AI. They developed TensorFlow, an AI/ML software library particularly good for training and inference of deep neural networks.
Pros — Promotes innovation through collaboration, lower costs, and increased transparency
Cons — Lack of control, intellectual property concerns, and potential for slow development without dedicated resources
Closed source: the Good and Bad
OpenAI (the developer of Chat GPT) has consistently taken a closed-source AI approach and is on its path to becoming a for-profit company
Pros — Greater control, protection of intellectual property, and improved monetization opportunities
Cons — Limited collaboration, higher development costs, and slower innovation
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