Tagged machine learning
- Halfway through the upgrade, half of my corpus scored 0
- A plain classifier named the key by its sound 99 times in 100. Trained on the silence between presses, it still named it 39 times
- A model reading my essays gives back 2 of my 16 rules
- Under 1% of websites load a script that calls itself AI
- My live Whisper transcriber made 2.6 times more mistakes than Whisper on the whole file
- A secret scanner found 2 secrets in typed notes and none in the Whisper transcript of the same call
- In 2022 the share of new GitHub repositories about AI did not grow. The stars did
- The tenant came back as the lessor after a round trip through Russian
- Stable Diffusion asks for 10 GB of video memory and the weights take 4 of them
- One in 7 "Belarusian" pages in mC4 is in Russian
- GPT-3 reads Belarusian at 6.5 times the price of English
- I asked my notes 15 questions they cannot answer and got 13 answers
- OpenAI's biggest embedding model costs 75 times more than the smallest and loses ArguAna to a 22M one
- I added "none of the above" and the model refused as often as before, but a third of the questions switched
- I asked GPT-2 to show its work and it trusted its own wrong arithmetic
- I tested prompt tips on GPT-2 and the order of the examples beat all of them
- A chatbot told me the capital of Ghana is Moscow and said yes when I asked if it was sure
- I trained a reward model on 16,000 Reddit votes and it liked length more than the voters did
- 9 models, accuracy between 92.5 and 93.3, and 1 of them finds nothing