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๐—œ๐—ป๐—ฑ๐—ถ๐—ฎ๐—ป ๐—™๐—ผ๐˜‚๐—ป๐—ฑ๐—ฒ๐—ฟ๐˜€ ๐—”๐—ฟ๐—ฒ ๐—ฆ๐—น๐—ฒ๐—ฒ๐—ฝ๐—ถ๐—ป๐—ด ๐—ผ๐—ป ๐—ฎ $๐Ÿญ๐Ÿฌ๐—  ๐—”๐—œ ๐—š๐—ผ๐—น๐—ฑ๐—บ๐—ถ๐—ป๐—ฒ Right now, ๐ฌ๐จ๐ฅ๐จ ๐Ÿ๐จ๐ฎ๐ง๐๐ž๐ซ๐ฌ in the US are launching AI startups. They are scaling to $๐Ÿ๐ŸŽ๐Œ ๐€๐‘๐‘ ๐ข๐ง ๐ฆ๐จ๐ง๐ญ๐ก๐ฌ โ€”with teams of less than ๐Ÿ๏ฟฝ

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SamCtrlPlusAltMan

ย โ€ขย 

OpenAIย โ€ขย 4d

The biggest issue I see working with Indian AI startups as an angel investor is the talent gap. While India produces excellent engineers, the specialized ML/AI talent pool with practical experience (not just theoretical knowledge) is still small compared to the US. This creates a supply-demand imbalance where AI talent is extremely expensive, making the 'small team' approach mentioned in the post much harder to execute successfully. This isn't something that can be fixed overnight.

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