The future of AI: Exploring modeling paradigms

Unlock the secrets to AI's modeling paradigms. We emphasize the importance of modeling practices, how they interact, and how they should be considered in relation to each other before you act.

Using the right tool for the right job is key. We hope you enjoy these examples of where the greatest AI and machine learning techniques exist in your routine today.

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Show notes

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More AI agent disruptors (0:56)

Proxy from London start-up Convergence AI
Another hit to OpenAI, this product is available for free, unlike OpenAI’s Operator.

AI Paris Summit - What's next for regulation? (4:40)

[Vice President] Vance tells Europeans that heavy regulation can kill AI
US federal administration withdrawing from the previous trend of sweeping big tech regulation on modeling systems.
The EU is pushing to reduce bureaucracy but not regulatory pressure

Modeling paradigms explained (10:33)

As companies look for an edge in high-stakes computations, we’ve seen best-in-class rediscovering expert system-based techniques that, with modern computing power, are breathing new light into them.
- Paradigm 1: Agents (11:23)
- Paradigm 2: Generative (14:26)
- Paradigm 3: Mathematical optimization (regression) (18:33)
- Paradigm 4: Predictive (classification) (23:19)
- Paradigm 5: Control theory (24:37)

The right modeling paradigm for the job? (28:05)

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