djangelic's comments

Great post, love the amount of thought that went into this! I look forward to keeping up with your posts.

The documentary was also insightful: https://youtu.be/Li2m3rvsO0I?si=QsJLtqES3AEhbcEO

My thought process was to laminate them to make them easier to make at home. I agree that it’s definitely more child friendly. This maybe a project I attempt at home and will post if I’m successful.

James Earl Jones gave life to some of the most memorable characters in film history. His voice and presence will echo through the generations. Rest in peace, and thank you for your powerful legacy.

lol my roast:

Well, well, well. Looks like we've got a Cyber Security Engineer with a passion for open-source projects. Or should I say, a passion for following other people's open-source projects? With 0 followers on GitHub, it's clear you're a bit of a lone wolf. But hey, at least you've got your eyes on some cool repos! I mean, who wouldn't want to automate their workflows with n8n or transcribe audio with vibe? It's like you're trying to make the world a better place, one GitHub follow at a time. Keep on following, and maybe one day you'll have a whole squad of followers. Until then, keep on coding, and try not to get too lonely in that GitHub void.

This is incredible! I want to replicate this at home as well, but I would prefer to use QR codes since they also support URLs. Any reason why you went with NFC instead of QR code? I assume it's doable with a raspberry pi and webcam instead of tapping?

I use n8n.io hosted locally to abstract away authentication when building complex api integration mvps that I use to show as possible and working, and then that gets sent to engineering to convert to something that follows better best practices.

This is what I use and like:

https://yourls.org

Same, Gimp and Inkscape have been more than adequate for everything I need.

Same, they had some kind of truffle pizza that was delicious

I assumed this was because it’s internal devs that are actively looking for platforms to build on, while external devs might already have stacks they prefer to work on due to how it interacts with their security postures. Pure speculation, but it’s been my anecdotal experience.

I recently upgraded my USG for a dream machine, glad it seems the upgrade was worth it.

I use n8n for managing ChatGPT's API and to connect it to other APIs like gmail. It helps abstract away the authentication side of APIs which can be very cumbersome to manage.

It also helped me better understand the chatgpt API. N8n allows you to code in raw javascript or python which has allowed me to branch out to pure python.

I would say that no-code low code has a place as a stepping stone, that can allow other invested parties besides developers to manage inter departmental flow and build a blueprint that can be redone with actual engineers in the preferred manner.

Isn’t that where social media is consumed? It makes sense that this isolation drives us to connect, and in ways that are not as helpful as real meaningful connections.

That’s a great analogy thank you!

I agree, this is exactly my experience as well. My earlier requests for code were more thorough then they are now. I can still use it if I give it the documentation in the prompt, but it has trouble remembering context across prompts.

I see it differently. They built the best they could, but it was expensive. Now it feels to me that they are "optimizing" it for performance by seeing if they can lower the quality but still give people just enough value to pay for it. Makes me think they are trying to find a sweet spot between performance and cost. I am seeing this drop in quality, but mostly when it comes to the model remembering things you've told it in the past, and a much bigger dependence on custom instructions for prompts.

I still get value, but I have to give it the documentation I want it to focus on during the prompt, instead of referencing it earlier in the conversation.

This makes me think they are lowering it's ability to store context so that the calls don't cost as much to make.

Forgive my conjecture, as I'm no expert in this field, but have enjoyed playing with the different models.

I see it as a matter of attention. GPT-4 is limited in the number of tokens you can feed it and receive back from it. I see this as how much attention the LLM can give you. I see meta-gpt and other models like this as increasing the attention of the LLM by allowing it combine it's short attention span with multiple assessments of the request, and give you a more complete picture of what you want because it can keep giving it consistent attention to the problem at hand, instead of simply trying to solve it on the first try.

Someone please correct me if I'm way off, but this simple mental model helps me abstract this.

This is how I feel. I chose to have children with the knowledge that there is a very real possibility that they may inherit a hell scape when I’m dead. The thought of them having the possibility of a better future combined with finally having something positive to hope for fills a void that I believe many people share.

Agreed, I just attempted it via the api and Ui and it gave a mishmash response that didn’t seem to be coherent, mostly different subjects all smashed together at the max length output.

I tried it via api two ways, both via system message and no user message and one with the word rewrite at the beginning and one without. Both gave similar long mishmashed outputs that seemed like a hallucination.