AI Architecture

What people often think AI is

Beyond the Hype: The Nuanced Reality of AI 🤖What people often think AI is:• Data: A static entity that AI can automatically turn into insights.

• AI: A magic wand that can do anything.• Value: The automatic result of applying AI to data.What AI actually involves:• Data: A dynamic process of selecting, sourcing, and synthesizing diverse data.• AI: A complex process involving data engineering, feature engineering, scaling, modeling, and deployment. • Value: An ongoing process of extracting insights, monitoring performance, and iteratively improving models.Key Constraints:• Legal: AI systems must be developed and used within legal and regulatory constraints.• Ethical/Transparency: AI must be used fairly, transparently, and ethically.• Historical Bias: Models can inherit bias if trained on biased data. • Security: AI systems must be secured from threats and breaches

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