10
benj
1y

Work on a product to categorize text… previous guy implemented an NLP solution that took 20 per body of text (500 words or so) in a $400/mo AWS instance, was about 80% accurate and needed “more data for training” 🤦‍♂️

I thought (and still think) that for some use cases AI is straight up snake oil. Decided instead to make an implementation with a word list and a bunch of if statements in Go… no performance considerations, loops within loops reading every single word… I just wanted to see if it worked and maybe later I could write it more optimized in Rust or something…

first time I ran it it took so little that I thought it had a bug… threw more of the test data we had for the NLP, 94% accuracy, 50 flipping milliseconds per body of text in a $5/mo AWS instance!!!

Now, that felt good!!
(The other guy… errr… left, that code is still the core of product of the company I built it for, I got bored and moved to another company :)

Comments
  • 3
    I stopped using my uni's feedback system on the third consecutive occasion that my innocent message was rejected by the tone analyzer. On the third occasion I was trying to alert them about this problem.
  • 1
    @lorentz sounds like Chat-GPT “how can you make this message pass a stupid tone analyzer”

    For real tho, that sounds infuriating!
  • 0
    @mansur85 I'm not sure that's the right word either, I'm referring to a program that sorts text into one of a few emotions such as "neutral", " angry", "happy".
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