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==Philosophy and Broader Impact==
==Philosophy and Broader Impact==
The MVA approach mirrors broader trends in tech: ship fast, learn from users, and adapt. It rejects the notion that AI must be flawless out of the gate—a mindset fueling successes like [[Google]]’s evolving algorithms and [[OpenAI]]’s iterative models (from Article 3). By keeping humans involved and updates frequent, MVAs stay relevant in a field where stagnation means obsolescence (from Articles 2 and 4). It’s about momentum over perfection—a pragmatic way for developers, startups, and businesses to explore AI without drowning in complexity.
The MVA approach mirrors broader trends in tech: ship fast, learn from users, and adapt. It rejects the notion that AI must be flawless out of the gate, a mindset fueling successes like [[Google]]'s evolving algorithms and [[OpenAI]]'s iterative models. By keeping humans involved and updates frequent, MVAs stay relevant in a field where stagnation means obsolescence. It’s about momentum over perfection, a pragmatic way for developers, startups, and businesses to explore AI without drowning in complexity.