When we talk about AI, people often mix up two important concepts - AI models and AI applications. But they're actually quite different!
Think of it like a car: the engine is powerful, but you need the whole vehicle to actually drive somewhere.
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Can you guess which part AI models are like?
An AI model is the "brain" or "engine" - it's the mathematical core that's been trained on data to recognize patterns or generate outputs.
Models like GPT-4 or Claude are just algorithms with billions of learned parameters. They're pure intelligence without a way to interact with users.
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What would an engine be without a car body?
An AI application (or system) is the complete package - it takes that model and wraps it with everything needed to make it useful.
This includes the user interface, data processing, servers, and all the code that lets you actually chat with the AI.
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Starting to see why ChatGPT is more than just GPT-4?
ChatGPT is the application - it provides the chat interface, saves your conversations, handles millions of users, and manages all the technical stuff.
Inside, it uses GPT models as its "engine" to generate responses. But without ChatGPT's application layer, GPT-4 would just be code sitting on a server!
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What other parts might an AI application need?
AI applications typically include data collection systems, business logic (rules for how to use the model), infrastructure (servers and databases), and visualization tools.
Think of Google Maps - the routing algorithm is the "model," but the app includes maps, UI, traffic data, and much more!
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Can you think of another app that uses AI models inside?
