"In business, this becomes an on-premises AI that can be accessed remotely by authorized endpoints (you, your iPhone, your employees' devices). The beauty of this arrangement is that whatever data you share or requests you might make are handled only by the devices and software you control. How it might work You might be running an open-source Llama large language model (LLM) to analyze your business documents and databases - combined with data (privately) found on the web - to give your field operatives access to up-to-the minute analysis relevant to them."
"In this model, you might have a couple of high-memory Macs (even an M1 Max Mac Studio, which you can get second-hand for around $1,000) securely hosted at your offices, with access managed by your choice of secure remote access solutions and your own endpoint security profiling/MDM tools. You might use Apple's ML framework, MLX, installing models you choose, or turn to other solutions, including Ollama."
On-premises AI can be deployed within a business and accessed remotely by authorized endpoints, keeping data and requests confined to devices and software under organizational control. An open-source Llama LLM can analyze internal business documents and databases, combined with privately gathered web data, to provide field operatives with up-to-the-minute, context-relevant analysis. Hosting can run on a few high-memory Macs—such as an M1 Max Mac Studio obtained second-hand—securely hosted at offices. Remote access and endpoint security can be managed with chosen secure remote access solutions and MDM profiling. Models can be installed using Apple's ML framework MLX or alternatives like Ollama.
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