Here's how the data we feed AI determines the results
Why do I feel so weird that my creative output has been vacuumed into AI datasets, when so much of my life is already up for grabs?
What data is used to train AI models?
AI models, especially large language models (LLMs), are trained on massive datasets that include a wide variety of sources. For instance, the Google C4 dataset comprises 15 million websites, which include content from journalism, entertainment, software development, and more. This diverse range of data helps explain why certain industries may feel threatened by advancements in AI.
How is personal data handled in AI training?
The training of AI models involves processing vast amounts of data, including potentially personal information. However, this data is not stored in a conventional database; instead, it is abstracted and transformed within neural networks. As a result, while the models learn from the data, they do not reproduce it in its original form, which raises questions about copyright and the ethical use of personal content.
What are the concerns surrounding AI training datasets?
There are significant concerns about copyright issues and the potential for misinformation stemming from the datasets used to train AI models. As companies like OpenAI become less transparent about their data sources, public scrutiny increases. This has led to discussions about regulation and the need for clearer guidelines on how personal and proprietary data is utilized in AI training.
Here's how the data we feed AI determines the results
published by Alpha Technologies Inc.
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