"The startups building AI in India aren't trying to out-compute San Francisco. They're doing something more interesting: proving that constraint itself can be a design philosophy."
"Large language models process text by breaking it into tokens, small chunks of characters that the model treats as discrete units. English gets efficient tokenization due to its dominance in training data."
Vivek Raghavan faced a choice between waiting for Silicon Valley to localize AI models for India or building his own. He opted for the latter, recognizing that many Indians struggle with English and have limited bandwidth. This decision reflects a broader trend where Indian startups are not competing with large tech firms but are instead leveraging constraints as a design philosophy. They demonstrate that models tailored for specific contexts can outperform those developed with abundant resources, highlighting a unique approach to AI development in resource-limited environments.
Read at Silicon Canals
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