"The AI industrial complex has operated on the idea that feeding models more data means smarter models. However, the next frontier of AI requires rich and multifaceted data that cannot simply be downloaded."
"If we aren't able to stem the excess of junk data, the entire promise of physical AI and world models may never achieve its full potential. Junk data does not advance AI models at all."
"The hunger for data has spawned a wave of multi-billion dollar AI data startups, but this has produced a bounty of junk data that is easier to produce and does not contribute to meaningful advancements."
"Training models to understand the multi-dimensional world requires significantly more data that is hard to obtain, leading machine learning engineers to simulate data through hours of virtual reenactments."
The advancement of physical AI and world models hinges on the quality of data used for training. While the AI industry has thrived on the abundance of internet data, the next phase requires rich, multifaceted data to navigate complex real-world tasks. A crisis looms as the demand for data has led to an influx of junk data, which does not contribute to model improvement. Producing high-quality data is labor-intensive, necessitating extensive simulations to capture the complexities of the physical world.
Read at Fortune
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