Really great idea. AWS docs are a nightmare to navigate.
Thanks! Hope this saves you time instead of searching the docs. If you have any feature requests, let me know!
Readit Newsas4296 commented on AI-Powered Search and Chat for AWS Docs awsdocsgpt.com/... · Posted by u/as4296
Very cool! AWS docs are insanely hard to navigate, and I've been looking for a tool like this for a while. I'm curious how you created this—thinking of doing some similar stuff for my personal projects :)
I used web scraping -> vector embeddings -> vector DB search here. The chat functionality is built on top of search and AWS pages are used as context for better responses. The hard part was the fact that AWS Documentation is so large so embedding took a while. Also happy to chat and answer any questions you have on your personal projects!
this is great. I feel a chrome extension could extend the functionality and speed to use even more...thinking about building something like that?
I've been in the process of building a chrome extension to do exactly that. I've always wanted to work with browser tools so this is the perfect excuse haha.
I’ve been working with AWS the last year and a half, and the documentation sucks!!
It’s way too verbose, doesn’t have clear examples (if there are any at all), and even finding the right pages is much easier said than done.
For a while I used GPT-4 to help with AWS but the September 2021 knowledge cut-off became too much of an issue.
It actually got so bad that I built AWS Docs GPT for myself a few weeks ago and a friend told me to publish it — so here I am.
Hopefully this makes it much easier to query, search, and chat with every single item of documentation AWS has ever published.
Also, would love to hear your feedback and comments
> AlphaDev uncovered new sorting algorithms that led to improvements in the LLVM libc++ sorting library that were up to 70% faster for shorter sequences and about 1.7% faster for sequences exceeding 250,000 elements.
As someone that knows a thing or two about sorting... bullshit. No new algorithms were uncovered, and the work here did not lead to the claimed improvements.
They found a sequence of assembly that saves... one MOV. That's it. And it's not even novel, it's simply an unrolled insertion sort on three elements. That their patch for libc++ is 70% faster for small inputs is only due to the library not having an efficient implementation with a *branchless* sorting network beforehand. Those are not novel either, they already exist, made by humans.
> By open sourcing our new sorting algorithms in the main C++ library, millions of developers and companies around the world now use it on AI applications across industries from cloud computing and online shopping to supply chain management. This is the first change to this part of the sorting library in over a decade and the first time an algorithm designed through reinforcement learning has been added to this library. We see this as an important stepping stone for using AI to optimise the world’s code, one algorithm at a time.
I'm happy for the researchers that the reinforcement learning approach worked, and that it gave good code. But the paper and surrounding press release is self-aggrandizing in both its results and impact. That this is the first change to 'this part' of the sorting routine in a decade is also just completely cherry-picked. For example, I would say that my 2014 report and (ignored patch of) the fact that the libc++ sorting routine was QUADRATIC (https://bugs.llvm.org/show_bug.cgi?id=20837) finally being fixed late 2021 https://reviews.llvm.org/D113413 is quite the notable change. If anything it shows that there wasn't a particularly active development schedule on the libc++ sorting routine the past decade.
Lol I was about to say that would be incredibly crazy if they found a new sorting algorithm. My time complexity in USACO bout to go crazy.
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as4296 commented on Social media for AI bots: “No humans allowed” fry-ai.com/p/social-media... · Posted by u/mannylee1
For those who have taken the course, how useful do you think this is? Also, how does Google's models compare to those of OpenAI?
This is so crazy, never even realized how complex location tracking is...