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OpenAI Co-Founder Ilya Sutskever Rings Alarm Bells: AI's 'Fossil Fuel' Is Running Out As World Reaches 'Peak Data'

Benzinga ·  16:41

OpenAI co-founder Ilya Sutskever is sounding the alarm on a looming data crisis that could reshape the artificial intelligence industry's future.

What Happened: Speaking at the Conference on Neural Information Processing Systems (NeurIPS) in Vancouver on Friday, Sutskever warned that the critical resource powering AI development is running dry, reported the Observer.

"Data is the fossil fuel of AI," Sutskever said at the conference. "We've achieved peak data and there will be no more."

The warning comes amid growing evidence of data access restrictions. A study by the Data Provenance Initiative found that between 2023 and 2024, website owners blocked AI companies from accessing 25% of high-quality data sources and 5% of all data across major AI datasets.

This scarcity is already forcing industry leaders to adapt. OpenAI CEO Sam Altman has proposed using synthetic data – information generated by AI models themselves – as an alternative solution. The company is also exploring enhanced reasoning capabilities through its new o1 model.

Why It Matters: The data shortage concerns echo recent observations from venture capital firm Andreessen Horowitz. Marc Andreessen noted that AI capabilities have plateaued, with multiple companies hitting similar technological ceilings.

Sutskever, who left OpenAI earlier this year to launch Safe Superintelligence with $1 billion in backing from investors including Andreessen Horowitz and Sequoia Capital, believes AI will evolve beyond its data dependency.

"Future AI systems will understand things from limited data, they will not get confused," he said, though he declined to specify how or when this would occur.

The increasing difficulty in accessing diverse and high-quality datasets for AI training has prompted companies like OpenAI, Meta Platforms Inc (NASDAQ:META), NVIDIA Corp (NASDAQ:NVDA), and Microsoft Corp (NASDAQ:MSFT) to adopt data scraping practices, though not without controversy.

For example, Microsoft's LinkedIn was recently scrutinized for using user data to train its AI models before updating its terms of service.

Similarly, Meta has been using publicly available social media posts from Europe to train its Llama large language models, though privacy concerns have prompted legal challenges.

Nvidia, too, has been scraping videos from YouTube and Netflix, including those from popular tech YouTuber Marques Brownlee, to train its AI systems. While these companies argue their practices comply with copyright laws, the ethical implications of scraping data without explicit consent have raised alarm across the industry.

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