PYMNTS.com February 6, 2025
Researchers from MIT, Harvard and Yale discovered a paradox in the field of artificial intelligence (AI) training that could represent a breakthrough in accelerating intelligence in robots.
They discovered that AI systems that learn in quiet, controlled environments at times outperformed those trained in noisy, unpredictable conditions when deployed in the real world, according to their paper, “The Indoor-Training Effect: unexpected gains from distribution shifts in the transition function.”
It’s like saying that a tennis player who trained in a quiet tennis court will do better in an actual tennis game despite windy conditions and a crowd roaring in the background than another player who trained in real-world conditions.
But this was exactly what the researchers found.
“Surprisingly, we found...
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