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Cloud-based AI service

As explained in Build Applications with Local AI Models on a Mac

A service that provides AI capabilities through remotely operated servers.

A cloud-based AI service runs the AI model on a provider’s server. You enter a prompt in an application; the prompt crosses the internet to the service, and the response travels back. With local AI, the prompt, model, and response stay on your computer. That boundary matters when you decide what data to send. section 1.1.1

Figure 1.1 Cloud AI (right) sends your prompt across the internet to a hosted inference service, and your data may be stored on the company’s servers. Local AI (left) keeps the prompt, the model, and the response inside your machine: no network hop, no external server, and no data leaving your control.

Follow the prompt and response in each direction to see where data leaves your machine. section 1.1.1

Cloud AI is useful when a task calls for the strongest available models, the latest updates, or possibly real-time information—and the content is not sensitive. It needs an internet connection. Your data reaches company servers and may be stored there, while service prices, terms, and features can change. Local AI offers offline use and more control, but its models are generally smaller and are frozen at their training cutoff date. section 1.1.1 section 1.1.2 section 1.1

Table 1.1 A comparison of cloud AI services and local AI (Ollama) across key dimensions

Feature

Cloud AI (ChatGPT, Gemini, Claude)

Local AI (Ollama)

Model size

Very large (hundreds of billions of parameters)

Smaller (1B to 70B+ parameters)

Response quality

State-of-the-art for complex tasks

Excellent for many tasks; improving rapidly

Accuracy/recency

Continuously updated; may have real-time data

Frozen at the training cutoff; no real-time data

Privacy

Your data is sent to company servers

Your data never leaves your machine

Cost

Free tiers are available; paid plans for heavy use

Completely free (you pay only for electricity)

Internet required

Yes, always

No; works fully offline

Speed (first response)

Depends on server load and network

Depends on your hardware

Availability

Can go down during outages

Always available if your computer is on

Customization

Limited to what the service offers

Full control over model selection and parameters

Data retention

Company may store your conversations

You control everything

Hardware needed

Any device with a browser

Capable local machine (8 GB+ RAM recommended)

Compare quality, recency, privacy, cost, connectivity, and availability before choosing where to run a task. section 1.1.1

Choose the location to fit the task

Use cloud AI for a difficult, nonsensitive task that needs maximum capability. For a private voice application, keeping the AI local means the audio need not leave your computer. On a ship or at a remote research station without internet access, a laptop with Ollama and an already-downloaded model can still work. You can use both approaches for different tasks. section 1.1.2 section 1.1 section 14.4.8

How Build Applications with Local AI Models on a Mac covers it

How deep it goes
Explains prompt travel and practical tradeoffs, without detailing how to deploy a cloud service.
Examples
Contrasts ChatGPT, Gemini, and Claude with Ollama, and considers private voice audio and internet-free remote locations.
What you can do after
Evaluate/understand it by deciding whether a task warrants hosted capability or local privacy and offline access.
How it connects
Connects hosted inference to local AI, data privacy, offline use, model recency, and Ollama.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Build Applications with Local AI Models on a Mac. The section links point to the parts of the book it draws on.