Open AI versus Closed AI

Open Cons

• Infrastructure Burden: Self-hosting requires dedicated hardware, technical overhead, and an engineering team to manage deployment.
• Performance Gap: Top closed-source systems often lead industry benchmarks by a few months, though open alternatives are closing the gap quickly. 
• Security Risks: Shared weights or community code can sometimes expose vulnerabilities or be weaponized by malicious actors if poorly supervised. Google AI. Okay who is going to supervise China on their open versions?

Closed Cons

• High Ongoing Costs: Licensing and API query fees scale up rapidly with heavy enterprise use.
• Vendor Lock-In: Users depend entirely on the provider’s roadmap, pricing changes, and privacy policies.
• Zero Visibility: Lack of transparency makes it hard to audit training data, trace exact biases, or customize core behavior. Google AI. Making Closed AI more difficult to weaponize by malicious actor!

And that is all I’m going to say about that!