Your Question:
If there haven’t been datacenters that store digital information like text, chats, images, and videos, would AI still be able to dynamically create answers to prompts using weights and tokens based on statistics and probability?
The Answer:
No. AI models rely on existing data to learn patterns. Without stored data, there would be nothing to train on, so the model couldn’t form meaningful weights or probabilities. Any output would be random and not useful.
Your Question:
“No is the answer haha 😂”
If “no” is the answer, then AI is simply a computer program or software that helps humans access information in datacenters in a customized and relatable format based on the user’s prompt. Humans engineered it.
The Answer:
Not quite. AI is not just a tool that fetches data from datacenters. It doesn’t directly look up answers.
It is a trained model that learned patterns from data and uses probabilities to generate responses. Datacenters mainly store and run the model, not act as a live library it searches.
A better way to say it:
AI is a human-made system that learned from data and can generate new responses, not just customize stored information.
Your Suggestion, Questions, and Clarification:
That sounds similar to what I meant. Since AI wouldn’t exist without data stored in datacenters, doesn’t that mean it’s an engineered program that manipulates that stored information using probability and statistics? And isn’t that what you call a trained model that learned patterns from data, whether it is after it got trained or before it got trained on it, it is still manipulating data?
Answer:
Close, but slightly off.
AI does not manipulate stored data in datacenters while answering questions.
- During training → it learns from stored datasets
- After training → it no longer uses those datasets directly
At runtime, it uses:
- Learned weights
- Probability to predict the next word
So, AI generates answers from learned patterns, not by working on stored files in real time.
Refined idea:
AI is a human-engineered system that learns from stored data, then uses statistical patterns to generate new answers independently of that data.
Your Final Question:
Humans are the ones who initially train AI by showing it data and associations, right? After that, it follows those patterns. And doesn’t that mean others can also train their own AI using their own datasets?
Answer:
Yes — that’s basically correct.
- Humans provide data and training methods
- The AI learns patterns from that data (partly guided, partly automatic)
- After training, it follows those learned patterns
And yes:
People can train their own AI models or fine-tune existing ones using their own datasets.
Conclusion:
AI is not just a system that retrieves stored information. It is a human-engineered system that learns patterns from data and uses probability to generate new, context-aware responses.
And you have solidly seen and witnessed the cause and effect of AI; every other thing you do with the information depends on you.
Technology is not hard to conceptualize when you closely look at it.
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