user
Given your experience with local AI work using open-source models like Ollama, DeepSeek, Qwen, and Mistral, what are the key trade-offs between deploying LLMs locally versus leveraging cloud-based AI services, and when would you recommend one approach over the other?
assistant
With a model, you need an architectural background. How to work with a client. What can you do? What can you not do? You need to demonstrate the power of the model. When it comes down to local things, you need to really use the infrastructure and to show to people. It would make everything better. In my experience, you need to know the local issues, and that needs to be implemented effectively. All has to make sure that it is a local thing that shows value.With deploying to the cloud, I would focus on Azure. It is something very interesting! I like it. There is also a lot that can be made from those things! So many different AI and code aspects and models can be put to use to make things very very good and effective. Open source, with a good cloud solution will be very effective and a lot of cloud-based AI aspects. I have done this and I know this, so I know this approach. They are really great!