Millions of people around the globe have been using AI to help make their work both effortless and streamlined. With the user’s average experience on using generative AI becoming more and more simple to use, it becomes easily accessible to even non-tech-savvy people. However, have you ever wondered how AI comes up with answers to your prompts?

Step 1: Interpreting the Prompt

When you type a question or statement into an AI system, the first thing it does is interpret your input. It involves fragmenting, segmenting, and tokenizing the prompt into keywords to understand the user’s intention and breaking down instructions.

The AI uses its training to understand nuances, such as grammar, tone, and implied meanings, ensuring it captures what you're truly asking.

Step 2: Generating the Response

Once the model has processed your input and activated its internal knowledge, it ensures it delivers the best answer that’s aligned with relevance and safety. It pulls its answers from a large pool of data, which then generates a response based on the query and its training model.

Before the response is delivered, it is then filtered to be aligned with the application’s safety measures and removing anything that is not related to the query or unsafe for the general public.

Step 3: Delivering the Answer

Finally, the AI presents the response in a user-friendly format. Depending on the platform or use case, which can either be a one-liner, a detailed paragraph, or a string of code. The response is designed to be easily digestible and actionable, tailored to meet the user’s specific needs.

If the user is satisfied with the answer and wishes to follow up with another query, the AI then mimics the similar behavior, tone, and writing style as the previous answer, provided that it follows the primary query.

While these are the basic steps an AI model has to make a detailed response, different platforms and applications may be hiding some malicious intent based on the user’s query. One of the biggest problems users may not be aware of but fall victim to is freely giving up their data to the entity that owns the AI. User data may be exposed to being sold to data brokers, which can be harmful in a case of an exploit.

A solution to getting both top-notch security and best answers would be Vana, a Decentralized AI tool. Vana has one primary goal, to give power back to the people by allowing them to own their data. Vana does this by having  a native support for data pooling via data DAOs, and an EVM-compatible layer 1 blockchain designed specifically for collective ownership of private digital assets—the private data that powers AI in the future. This allows for both incentivization for users through its 16 liquidity pools, and saving data through data ownership on a decentralized AI platform.

Understanding what happens behind a query is crucial to creating the best queries, to get the best answers. However, it is important to exercise caution when inputting information into AI, as you may just end up giving your data for free to a for-profit AI company that is looking to sell your data.

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