Why do they need to run benchmarks to confirm performance? Can't they run an example prompt and verify they get the exact same output token probabilities for all prompts? The fact that they are not doing this makes me suspicious that they are in fact not doing the exact same thing as vLLM.
It is also a bit weird that they are not incorporating speculative decoding, that seems like a critical performance optimization, especially for decode heavy workloads.
IMO the core of the issue is the awful Github Actions Cache design. Look at the recommendations to avoid an attack by this extremely pernicious malware proof of concept: https://github.com/AdnaneKhan/Cacheract?tab=readme-ov-file#g.... How easy is it to mess this up when designing an action?
The LLM is a cute way to carry out this vulnerability, but in fact it's very easy to get code execution and poison a cache without LLMs, for example when executing code in the context of a unit test.
Wow that is wild, that is exactly along the lines of my fantasy language. It'd be so easy to go into the deep end building tooling and improving a language like this.
I've given up on soft delete -- the nail in the coffin for me was my customers' legal requirements that data is fully deleted, not archived. It never worked that well anyways. I never had a successful restore from a large set of soft-deleted rows.
Home affordability is getting better anyways, which is great, because we are finally having a surge in new & denser home building in popular regions and there mortgage rates are more reasonable than they were in the COVID-era.
Maybe the best part of this legislation will be that people will realize it's not institutional investors that are driving up home prices. No, that's far too optimistic.
It's not debouncing, it's delaying. Ideally you can still update a specific dependency to a more up to date version if it turns out an old version has a vulnerability.
There are some good reasons it is lower now, like defense lawyers and Miranda rights. Obviously it'd be good if we had both good civil rights AND high murder clearance, but they seem in obvious tension with each other.
If you haven't, give Cursor's Composer model a shot. It might not be quite as good as the top models, but in my experience it's almost as good, and the lightning fast feedback is more than worth the tradeoff. You can give it a task, wait ten seconds, and evaluate the results. It's quite common for it to not be good enough, but no worse than Sonnet, and if it doesn't work you just wasted 30 seconds instead of 10 minutes.