Don't you want to use the average instead of "0.5"?
From the explanation:
> The code is a function that takes in an input tensor and returns the mean squared error of the input.
It's hard to believe that the system can detect that it's the "mean squared error". Is this an explanation a real example from the implementation, or it's just a handmade example?
Note: Wait more time to repost. Users usually get angry and start to flag our post is you repost too often.
I saw the previous post gaining no traction, and personally had fun testing the service with C / Audio code before, so I wanted it to stay afloat a bit longer, at least.
> It's hard to believe that the system can detect that it's the "mean squared error".
I won't be surprised ML model detected it, statistics-wise, associating "Tensorflow" and "mean" with "mean squared error".
Happened when I fed it CLIP-related code.
> Don't you want to use the average instead of "0.5"?
It was tested on the real-life code, looks like a Colab I have previously recommended.
> It's hard to believe that the system can detect that it's the "mean squared error". Is this an explanation a real example from the implementation, or it's just a handmade example?
> Don't you want to use the average instead of "0.5"?
It's from the real implementation. The code was some code a user sent in, which I ran the tool on.
> I tried and got the same outcome.
I fixed the waitlist– there was a problem, where if you typed your email then filled out the rest of the form without editing the email field, the waitlist signup would fail.
I tried variations of the same code, changing the name of the `inner` function to `temp` and `banana`. In each of them I got a different explanation, for example:
> - The code is a function that takes in an input tensor and returns the squared difference between it and 0.5.
that I think it's more correct than "mean squared error". You should change that example.
I also got:
> - The code is called l2, which stands for "linear regression."
The examples are impressive however I would suggest being slightly more conservative in claiming what it can explain. I definitely think it is over reaching to claim that it works on any language.
From the first example:
> return -tf.reduce_mean((T("input") - 0.5)2)*
Don't you want to use the average instead of "0.5"?
From the explanation:
> The code is a function that takes in an input tensor and returns the mean squared error of the input.
It's hard to believe that the system can detect that it's the "mean squared error". Is this an explanation a real example from the implementation, or it's just a handmade example?
Note: Wait more time to repost. Users usually get angry and start to flag our post is you repost too often.
Also, as mimixco said in https://news.ycombinator.com/item?id=28131271
> The live example on the home page doesn't seem to work. I assumed JS was supported and typed this:
> const addOne = function(someNumber) { return someNumber + 1 }
> The "explain" box shows nothing.
> This site makes bold claims which, so far, I don't see backed up by anything. Even the "join waitlist" dialog is broken!
> Next...
I tried and got the same outcome.