The world is running out of data to train Artificial Intelligence known as AI models artificial intelligence researchers warned that the industry may face a shortage of training data, which is essential for developing powerful AI systems. The growth of AI models, especially large language models, could be slowed down, potentially impacting the AI revolution.
High-quality data is necessary for training accurate AI algorithms. Inadequate data can lead to inaccurate outputs, making the quality of training data crucial. Social media contents is easily accessible, but can be biased, prejudiced, or contain disinformation, which AI model can unintentionally replicate. AI developers prefer high-quality content from books, articles, papers, and curated web sources.
Research shows that AI is currently evolving faster than the amount of data published online, which can lead to scarcity of high-quality text data by 2026. This shortage could hinder AI development despite its potential economic impact. To address data scarcity risks, AI developers can improve algorithms to utilize existing data more efficiently, which will allow AI to generate its own data, and learn from it on its own.
Researchers propose content deals with creators, publishers, and copyright holders, to help address the power imbalance between them and AI companies. While challenges exists, these approaches offer potential solutions to ensure continued AI development.
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