AI vs ML vs DL vs Generative AI

AI Governance Expert

The increasing reliance on machine learning in industries like banking raises important governance challenges, particularly in fraud detection. Ensuring the integrity of algorithms is critical, as biased training data can lead to flawed predictions, compromising ethical standards. Continuous monitoring and transparent model deployment are essential for maintaining trust in these systems.

AI Data Scientist Expert

The distinctions made between statistical ML and deep learning reflect a deep understanding of model selection criteria based on data complexity. The efficacy of generative AI architectures, such as Transformers, highlights a trend towards using sophisticated models to handle unstructured data. This trend suggests a shift in focus from traditional ML techniques to deep learning models, which can better capture intricate patterns in complex datasets.

Artificial Intelligence (AI)

Discussed as encompassing various tasks, including driving and poetry creation.

Machine Learning (ML)

Explained through examples like house price prediction using regression algorithms.

Deep Learning

Used for tasks like image classification and natural language processing.

Generative AI

Detailed as using deep learning techniques for producing text or video.

Zillow

Mentioned as an example of a company applying ML to assess housing market values.

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