TheKelsbee

I have a framework 16 that I picked up recently. Honestly, the screen is OK but it's not a very high-end display. One of the biggest advantages to this laptop is its hack-ability. With a little work I think would be feasible to swap that display for something you prefer more. The changeable bezels are nice though :)

Hi! AWS Developer Advocate here. Depending on the nonprofit/charity status it's possible they could qualify for free or reduced price hosting. There are a few different programs that you could qualify for.

There is also the Techsoup organization, which helps nonprofits and charities with technology needs: https://page.techsoup.org/amazon-web-services-for-nonprofits

I would highly recommend looking through there for not just AWS specific tools & services, but a wide variety of solutions that might help this charity.

Please feel free to reach out directly to me for additional assistance. Hope this helps!

I just plugged this prompt into Nova:

I want you to generate a document detailing the current landscape of AI model and agent providers. You should include external citations, a very brief synopsis of each tool, the pricing associated with the tool, and a link to check it out. Limit this to the top 20 tools in the AI space.

It generated a doc that I could download and build off of. Try something like that?

I'm not sure its easy to say one is better than the other. I've used ChatGPT pro, it's good. I've also use Gemini, and it's also good. Claude is surprisingly good as well. And I've recently been using Q-cli, which was extremely easy to get integrated into my Neovim/Tmux workflow.

Purely from a code quality perspective, they're all about the same, and they all generate code that rarely works for the first time. At least from my experience, and highly depending on language. For instance, Q-cli with Rust seems to generate better output for me than Gemini with Rust. And ChatGPT with JS gives me way better code than Claude with JS.

I honestly think that currently in the market, it's not really a choice of which is better, but which is the right tool for workflow and language.

Years ago, before the Internet, software was expected to be rather buggy. It took a long time to research and fix. Releasing software was expensive, you had to put it on physical media and ship it. QA was critical role, it was way less expensive to test the hell out it and fix it than it was to ship new code. The idea that computers could be trusted to perform tasks well was easily shattered when things went wrong, and the additional optics of losing customer trust went a long way into driving QA.

Fast forward to today, and it's way cheaper to ship code with bugs to prove out an idea works than it is to spend even a few minutes writing test cases and doing even a modicum of QA.

Ultimately, it's a not just a combination of all 3 things you've mentioned, which are all contributing factors; the real problem is any level of QA before proving an idea is seen as a waste of time and money. As someone who started in tech support & QA 30 years ago, it's really tough to see.

Honestly - q-cli has been my go-to. I can basically just give it a few rules, enable it to self compile & test, walk away for lunch and comeback to something that almost works...

I have this same thought, and have tried similar approaches.

OP: Have you trained or fine tuned a model that specifically reasons the worker model inputs against the user input? Or is this basically just taking a model and turning the temperature down to near 0?