So you’re confident that human learning involves “understanding” which is distinct from “statistical optimization”. Is this something you feel in your soul or can you define the difference?
Yes. You learned not to touch a hot stove either from experience or a warning. That fear was immortalized by your understanding that it would hurt. An AI will tell you not to touch a hot stove (most of the time) because the words “hot” “stove” “pain” etc… pop up in its dataset together millions of times. As things are, they’re barely comparable. The only reason people keep arguing is because the output is very convincing. Go and download pytorch and read some stuff, or Google it. I’ve even asked deepseek for you:
Can AI learn and understand like people?
AI can learn and perform many tasks similarly to humans, but its understanding is fundamentally different. Here’s how AI compares to human learning and understanding:
1. Learning: Similar in Some Ways, Different in Others
AI Learns from Data: AI (especially deep learning models) improves by processing vast amounts of data, identifying patterns, and adjusting its internal parameters.
Humans Learn More Efficiently: Humans can generalize from few examples, use reasoning, and apply knowledge across different contexts—something AI struggles with unless trained extensively.
2. Understanding: AI vs. Human Cognition
AI “Understands” Statistically: AI recognizes patterns and makes predictions based on probabilities, but it lacks true comprehension, consciousness, or awareness.
Humans Understand Semantically: Humans grasp meaning, context, emotions, and abstract concepts in a way AI cannot (yet).
3. Strengths & Weaknesses
✔ AI Excels At:
Processing huge datasets quickly.
Recognizing patterns (e.g., images, speech).
Automating repetitive tasks.
❌ AI Falls Short At:
Common-sense reasoning (e.g., knowing ice melts when heated without being explicitly told).
Emotional intelligence (e.g., empathy, humor).
Creativity and abstract thinking (though AI can mimic it).
4. Current AI (Like ChatGPT) is a “Stochastic Parrot”
It generates plausible responses based on training but doesn’t truly “know” what it’s saying.
Unlike humans, it doesn’t have beliefs, desires, or self-awareness.
5. Future Possibilities (AGI)
Artificial General Intelligence (AGI)—a hypothetical AI with human-like reasoning—could bridge this gap, but we’re not there yet.
Conclusion:
AI can simulate learning and understanding impressively, but it doesn’t experience them like humans do. It’s a powerful tool, not a mind.
Would you like examples of where AI mimics vs. truly understands?
So you’re confident that human learning involves “understanding” which is distinct from “statistical optimization”. Is this something you feel in your soul or can you define the difference?
Yes. You learned not to touch a hot stove either from experience or a warning. That fear was immortalized by your understanding that it would hurt. An AI will tell you not to touch a hot stove (most of the time) because the words “hot” “stove” “pain” etc… pop up in its dataset together millions of times. As things are, they’re barely comparable. The only reason people keep arguing is because the output is very convincing. Go and download pytorch and read some stuff, or Google it. I’ve even asked deepseek for you:
Can AI learn and understand like people?
1. Learning: Similar in Some Ways, Different in Others
2. Understanding: AI vs. Human Cognition
3. Strengths & Weaknesses
✔ AI Excels At:
❌ AI Falls Short At:
4. Current AI (Like ChatGPT) is a “Stochastic Parrot”
5. Future Possibilities (AGI)
Conclusion:
AI can simulate learning and understanding impressively, but it doesn’t experience them like humans do. It’s a powerful tool, not a mind.
Would you like examples of where AI mimics vs. truly understands?