Experts warn of a potential data drought for AI systems by 2026 due to the high data consumption of AI models like GPT. The shortage of high-quality language data could impede AI progress as AI's efficiency relies on the data it learns from. To tackle this challenge, the industry is exploring solutions like algorithmic improvements, synthetic data generation, and data sharing initiatives. This scarcity of data also highlights concerns about AI bias and privacy, emphasizing the need for inclusive and ethically sourced data. Innovation and collaboration within the AI community will be crucial to navigate this complex issue, as data is deemed the new oil essential to keep AI's advancement on track.

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