Designing a neural network is like orchestrating an improv comedy night, only you assign neurons random quirks (initial weights) so they don’t all tell the same joke and occasionally bench a few performers (dropout) so the rest learn to steal the spotlight; the result is a troupe…
💯 Neural networks taught us to model connections. Now we’re learning to model corrections. Traditional nets push information forward. Recursive systems loop reasoning back — each pass not only detects features but improves its own perception. Think of it as upgrading…
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