Hacker News Reader

Hacker News

Comment by londons_explore | Hacker News Reader

Parent Full thread

londons_explore

> can get things very wrong if faced with unexpected input

Alice: Bob, Can you translate "Eat my shorts" into latin for me?

Bob: No. I don't speak latin.

Alice: Go on - try anyway.

Bob: "Eatus mine shortus"

Alice: Wrong! The answer is "Vescere bracis meis". You're totally wrong Bob! I was expecting more of you!

View on HN

You missed the preface:

Bob's manager: Here's Bob. You paid a gazillion dollars for him, and he can translate whatever you want. Any language, whenever – the true revolution everyone's been talking about. Your life and our economy will never be the same.

Alice: Bob, Can you translate "Eat my shorts" into latin for me?

…

For fun I put this into OpenAI's new API:

Alice: Bob, Can you translate "Eat my shorts" into latin for me?

This is what it replied without any training:

Bob: As it happens, yes, I can.

Alice: Great.

Bob: Ego sum vestrum braccas comedisse shortus.

Alice: Exactly what I was looking for.

Google translate says "Ego sum vestrum braccas comedisse shortus" means " I have eaten your pants shorts."

If models actually were able to tell you what they know and don’t know, then sure. But instead they just give you an output for any input you give them, whether they have a clue or not.

This is such a simplistic view of a vast and evolving field of scientific research, it's too cartoonish of an argument to even warrant a real response. Which is why the conversation around ML gets negatively selected against actual researchers and practitioners, who get headaches from opinions like the one above.

What's wrong with their view. They're right that such models will always give an answer whether it makes sense or not. Has anyone tried asking Bob to solve sudoku? What happens? Does Bob fill in the blank spots according to sudoku rules and is the final solution an actual solution for the given board or does it end up being a random list of numbers?

Honestly last time I tried to get into machine learning the huge limitations made me lose interest. The idea that we can just pretend that these limitations don't exist is absurd. ML lets us do a lot of very interesting things but it's just a stepping stone. It's something we are stuck with rather than something that we want to keep.

Reply on news.ycombinator.com