Why is the shredding a result of the fair use stuff? I actually don't understand
204 karma · joined March 1, 2013
in my personal experience, the one time I tried to do something in rust, opus flailed for several feedback cycles and I finally had to relent and do substantial guiding/intervention. which was not great bc I have no idea how to write rust either.
- Some of us don't do full yolo mode all the time, then tool approvals or code reviews are required, nice to do a quick review and decide if you need to go back to your computer or not
- Letting claude spin or handle a long-running task outside of normal work hours and being able to check in intermittently to see if something crashed
Also, just in case people want to lit review further on this topic: they call their method "programmatic data curation" but I believe this approach is also called model distillation and/or student-teacher training.
Because I have a hard time believing they can actually extract time increments and higher-level tasks from log data without a ton of pre/post-processing. But then the problem is just as much work as it was 5 years ago when you might have been using plain old BERT.
- you have no car, how do you get to your doctor's appointment without asking parents for a ride?
- you are a minor, do you have any guarantee that your doctor won't tell your parents? You can't risk them finding out, they are very conservative
- you may not have ever made a doctor appointment for yourself before, maybe don't have access to insurance information etc
Planned Parenthood provides BCPs at a price you can afford with your teenager job (also guarantees privacy) but the closest one is hours away...
What do you do?
See also (great read): https://pubmed.ncbi.nlm.nih.gov/31006626/
wrt your Spanish example: grammatical gender adds information redundancy to make it easier to process spoken language (e.g. helps with reference resolution). This redundancy enables Spanish speakers to speak at a relatively fast rate without incurring perception errors. English has fewer words but a slower speech rate. It's an optimization problem.
The speech rate issue isn't as obvious if you're only looking at text, but I'd argue/speculate that lossless speech as a language evolutionary constraint has implications for learnability.
tl;dr there is no communication tax, languages are basically equivalent wrt to information rate, they just solved the optimization problem of compactness vs speech rate differently
But there are tons of languages (not just CJK languages) that use either compounding or combos of root + prefix/suffix/infix to express what would be multiple words in English. E.g. German 'Schadenfreude'. Its actually way more useful to tokenize this as separate parts because e.g. 'Freude' might be part of a lot of other "words" as well. So you can share that token across a lot of words, thereby keeping the vocab compact.
Meanwhile, there are off-shelf models that you can train very efficiently, on relevant data, privately, and you can run these on your own infrastructure.
Yes, GPT4 is probably great at all the benchmark tasks, but models have been great at all the open benchmark tasks for a long time. That's why they have to keep making harder tasks.
Depending on what you actually want to do with LMs, GPT4 might lose to a BERTish model in a cost-benefit analysis--especially given that (in my experience), the hard part of ML is still getting data/QA/infrastructure aligned with whatever it is you want to do with the ML. (At least at larger companies, maybe it's different at startups.)