“AI is the new electricity. But most teams aren’t building power plants — they’re still trying to wire up the first lightbulb.”
— Andrew Ng
Andrew Ng has always had a gift for cutting through the hype.
In this new video, we decode Andrew’s vision for AI from the perspective of builders, not bystanders.
This isn't about AGI speculation or billion-parameter models — it's about what you should actually be doing today to stay ahead in the AI era.
🎥 Watch the full breakdown:
📺 Andrew Ng: What Engineers Must Understand About AI Right Now
🔧 What You’ll Learn in This Video:
Small Data > Big Models
Andrew emphasizes a shift: from obsessing over model size to optimizing data quality and domain adaptation. We explain how this plays out for engineers on real-world AI teams.
Fine-tuning vs Foundation Models
Not every team needs to train from scratch. We explore Andrew’s take on transfer learning, foundation models, and when you should fine-tune vs plug in an API.
Data-Centric AI in Practice
If your labels are messy, your results will be too. Learn how Andrew’s "data-centric AI" philosophy translates into better pipelines, cleaner results, and fewer hallucinations.
👷 Who This Video Is For:
- Software engineers moving into ML
- AI/ML practitioners looking to stay pragmatic
- Tech leads designing real-world intelligent systems
- Product managers working with LLM integrations
🧠 Sound Off
Andrew says: “AI is about data, not just algorithms.”
Do you agree? What’s been more important in your projects — tuning the model or curating the data?
Let’s get a thread going 👇
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