As software engineers, we have been conditioned to accept a deeply flawed premise: that entering the Artificial Intelligence research space requires multi-billion-dollar infrastructure, massive enterprise GPU clusters, and infinite venture capital. The mainstream tech narrative has turned language model pre-training into a game of brute-force computational scale. But scale alone is not engineering. Recently, an independent research line under the architecture CetinLM proved that localized ...