AI-powered content generation: what are the advantages and limitations?

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just a few months, the latest advances in AI content generation (ChatGPT, Bard, Midjourney, etc.) have taken a huge step forward.

Artificial intelligence is becoming a real challenge in SEO, but also in all aspects of digital marketing that involve writing.

Tools like ChatGPT allow you to create content that may not be at the level of top bloggers or copywriters, but is of above-average quality.

How can we use it list of us mobile number database and ethically, and above all, how can we stand out from the crowd in this haemorrhage of content that is currently taking place?

This is what we are going to discover in this article.

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How does AI-powered content writing work?
AI-powered content generation: what are the advantages and limitations? 5


Before discussing the use of content generation tools, it is necessary to review how these solutions work, which allow you to generate hundreds of texts in just a few minutes.

These tools, like ChatGPT, use a form of machine learning called deep learning.

AI-powered content generation: what are the advantages and limitations? 6


The starting point is data collection: models are trained on large sets of textual data (a mega library of content).

For example, in the case of GPT-3, the model was trained on millions (even billions) of texts from the Internet (books, articles, etc.).

Then there is a period of machine learning, the algorithm learns to predict the next word in a sentence based on the previous words, corrected by humans (this is called guided learning).

For example, if you give the model the sentence “The sky is…”, it might predict that the next word will be “blue.”

If the model says “The sky is green” a human will tell it that the answer is wrong, and therefore improve the quality of the answers.

The model thus learns as it goes along which are the “best” answers, and will deduce other questions directly or indirectly linked.

So the model adjusts its internal parameters to minimize the error between its predictions and the actual next words in the training data, guided by corrections by real people to improve the model's predictions.

Finally, we arrive at the final stage where the content generation tool is able to generate text with good results (still on the logic of predicting the next word).

For example, if you give it the beginning of a sentence, it can complete it by generating a logical and coherent sequence.

To achieve good results, models like GPT-3 use a mechanism called “attention,” which allows them to weight the importance of each word in context.