The Delayed Arrival of Superintelligent AI: Insights for 2027

With the release of newest version of ChatGPT, it seems more and more evident that AI advancement is slowing down. But the reason behind that is more than just technical hurdles like hardware, algorithm, and training data. There might be a fundamental limit to how smart AI can get. And it might even be a limit to intelligence itself. In this video, we will explore the science behind this limit, and its implications for AGI, Superintelligence, and humanity.

*Note: Many people have given me constructive rebuttals in the comments. So I have compiled my answers to the common one in a pinned comment. You might especially be interested in answer #5, where I talk about how Mixture-of-Experts techniques can push existing Pareto Front further, while introducing more meta Pareto Fronts. It includes citations of research papers too. Enjoy! And yes, I used a flathead on a Phillips screw in the video. Couldn’t find my Phillips. Decided to troll y'all instead 😅

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** Video Chapters **
0:00 Intro
1:09 Pareto Front
2:32 Generalist vs Specialist
3:54 Being Big vs Being Small
6:26 The Problem of Taste
9:19 Mediocre AI

** Concepts Mentioned in this Video **
- Pareto Front: https://en.wikipedia.org/wiki/Pareto_front
- No Free Lunch Theorem: https://en.wikipedia.org/wiki/No_free_lunch_theorem
- Life History Theory: https://en.wikipedia.org/wiki/Life_history_theory
- Modularity: https://en.wikipedia.org/wiki/Modularity
- System 1 Thinking: https://en.wikipedia.org/wiki/Thinking,_Fast_and_Slow

** Disclaimer **
This talk is for educational purposes only. It’s not medical, mental health, financial, or legal advice. Please consult a licensed professional about your specific needs.