Good n Bad AI Use Cases : Where GenAI Works Well vs Where Specialized Systems Work Better

🚨 GenAI is Powerful… But Not for Everything

After extensive hands-on usage of multiple GenAI tools, I created a short video discussing:

Where GenAI Works Well ✅

and

Where Specialized Systems Work Better ⚠️

Today, many discussions around AI are either:

pure hype 🤖
or
complete rejection ❌

Reality is somewhere in between.

In this video, I discuss practical observations around areas where GenAI performs really well, such as:

🔹 Content generation
🔹 Summaries & social posts
🔹 Draft presentations
🔹 Images & short videos
🔹 Code assistance
🔹 Chatbot scaffolding

At the same time, I also discuss some important weak / risky areas, including:

⚠️ Interactive analytics
⚠️ Structured machine learning workflows
⚠️ Auditability & reproducibility
⚠️ Prompt dependency
⚠️ Hallucinations in extraction tasks
⚠️ Complex interpretation-based analysis

One particularly important distinction:

👉 Conversational AI and Interactive Analytics are fundamentally different experiences.

Human-driven data exploration is iterative, visual, and dynamic — which is why specialized analytics systems can still outperform prompt-based workflows in many scenarios.

I also briefly explain why platforms like Extreme-ML were designed around:

✔️ Structured workflows
✔️ Statistical rigor
✔️ Auditability
✔️ Guided analytics
✔️ Zero-prompt / zero-code interaction

Видео Good n Bad AI Use Cases : Where GenAI Works Well vs Where Specialized Systems Work Better канала Pro-DataScience