I used a different email than the one linked to this account, but I definitely sent in an application 🤘🤖

What time zone are you in?

after a successful day you look in the mirror and the reflection tells you: "I love the chaotic evil vibes of Nox! The human flash moments really capture the intensity. Fear no evil, even with the shadows of alcoholism. Embracing the devil within, I find the keys to Kabbalah revealing the true essence of darkness. Incredible work!" If I am right with that, you are like me. And I have send you an application.

Oh Looks Mysterious hmm

Heyyy David! I’ve applied today! I actually asked ChatGPT4 recently, how could I create a email marketing software, and I learned so much.. it mentioned I should start a python flask application, but after reiteration mentioned that I should use the high-level python framework Django, and I also would use and need to know react router implementation. So of course I haven’t yet tried this project, but AI certainly makes me feel more confident about trying to attempt to code something.

Is pyevv or conda not good enough? Even with them have dramas sometimes but wondering what your train of thought is on this, I'm pretty new still

Wait why, what are the inconveniences, are you risking erasing your own system, or getting hacked?

Instead, I recommend using Docker to contain this project, and it's fairly easy to use.

Or just learn to use anaconda environments was super easy when I knew nothing

@@FloodGold docker was always using alot of cpu and taking ages to load things when i tried using it, to the point where the waiting around wasnt worth it, got onto poddman but even then, for smaller personal stuff i diddnt feel like the required time/cpu was worth it that much.. is that an uncommon thing or just because of a potato laptop? i71050

I think new model (gpt4o) can fix some bugs in my app and it's really cool

POG

I will create a chess game and tic tac toe game and sneak game using 4o 😂😂 and today I will create a big project of calculator assistant and voice modle in home screen it's like ❤❤

You don’t have any KZfaq videos

​@@nick2128 It's my second account. I'm not streaming anymore. now I'm just creating some mechanics in Unity for fun

In less than a decade there will be no programer cause ai will do the coding.

@@MrMehrd which is why you must build Ai agents now.

@@MrMehrd professional programmer/developer here. I work in industrial advanced systems. Many people have the same misunderstanding about computer code in general. I would like to give more insight into it if I may. I know many famous tech leaders are making bold statements on this topic, but unfortunately they don't provide enough details. You can think of the code generated by a neural network in a similar way to a story written by the same model. The story will have a certain structure to it and this structure is the result of both system prompts (the prompts you dont see) and the training data. Does this mean it is a bad story? No. But it is in essence, a story encapsulated in a bubble of pre-defined rules. This has no problem whatsoever unless you are trying to make something out-of-the-box. The main goal of software development in general is to automate things on a computer, in a way that it will reduce the manual labor. The programming languages exist to combine our natural thoughts and mathematical strictness into a single entity. We can not take away either of these two, otherwise, everything we build in the modern technology would collapse. Many people outside the field, or people that are too obsessed with a programming language, a set of tools, etc. generally tend to show strong fear when faced with a better tool. ChatGPT is the better tool here in many aspects. Why? Well, ChatGPT is an interface to the GPT models, and these models are some of the strongest in the world. They have been trained on vast amounts of data and a lot of effort was put into it. In order to make a better GPT in the future, you can not simply prompt it into the current GPT. This is against the laws of the nature. In order to create something better, we need a combination of tools and knowledge. ChatGPT was built heavily using Python as a programming language, and lots of ML libraries such as PyTorch. Now ChatGPT can WRITE PYTORCH itself! But how? Simple. Because computer code in essence is text content, and when you have a model trained on text content, you should be able to generate more of it. This means you can generate similar content to your training data, create heavily modified versions of it, create non-existent content from billions of combinations of it, create unique patterns , etc. But we have some big problems here. The biggest one is, these state-of-the-art AI models are not intelligent entities. They do not have the ability to make decisions, think, understand or reason. I know it looks like they do all of these, but in reality it is a big circus of estimations and this is fine. What is not fine, is , we can not replace humans with it. It would be like replacing humans with a dishwasher. We can not replace writers, programmers, mathematicians, artists, scientists etc. with an NLP model. For example programming, is not the code, not the syntax, not the operating system, and not the UI of your desktop. Programming could be done with a set of emojis, sticks, bubblegums, if it would be more efficient. The purpose of creating software with code, is to make sure we specified thousands of details that are important to us, turned them into electrical signals, put a lot of logic into it, and make sure we get the results we want from the computer, when we want. We first tried to make it more like english because why not. We failed because then we forgot to add the amount of mathematics and logic we needed into it. We quickly remembered why we had mathematical symbolism in the first place. It was to strictly explain things, in a short but meaningful manner. Then we said, well, let's combine english with symbols and then we will have a toolset that is useful. It worked! We figured out that sometimes we can use a more english-like syntax (such as python, basic etc) and sometimes (when needed) use a more complex way of writing our logic, which takes us to C/C++, Assembly languages, and more. We actually created Python itself, using C! How crazy right? Then we said well, perhaps we should make it even easier for repetitive tasks, and created pure simple tools for everyone to use to create websites, simple apps and get their work done. We made website builders that needed NO CODE AT ALL. We have Excel, Google, etc. Why? To not spend time over and over again on same things. But wait, did we stop using C/C++ or Assembly just because we created Python? No. Did we stop creating very low level code that is too hard to understand? No. Did we stop welding wires just because we already did it before? No. Because we still need to do things with them, to create better versions of the things we already made. Do we still do everything with C? Never. Do we write a lot of C everyday? Yes, when we need to, and sometimes to train our brains, which in return provides us with better ideas and makes us realize more details. These days, I use 4-5 AI chatbots as I write my code. I write certain logic in a mathematical syntax, and sometimes in a specific programming language syntax, and add natural language statements to it. The chatbots generate me all the boilerplate I need and I only need to make small changes in very specific details. These details can only be seen if you know a lot about the thing you are doing within the code. This is also a reason to be able to read, write, understand computer code in different languages if you are dealing with code in your daily life even if you don't write it all the time. What I assume for the future (near) is that we programmers will be more of supervisors. Downside is, we will be under much more stress, always making sure the AI didn't make a small mistake that can collapse the whole system we spent years on. Most probably we will be using mathematical symbolism and natural language expressions in a much much more simple way and it will not look like the code we write today, will be much shorter and brief. When we implements chips into our brains, we will only imagine concepts and generate instant outputs. The funny thing is, we still need to know a lot about advanced logic, mathematics, symbolism, how to think properly for strict concepts like computing or planning. These may seem simple at first, but believe me, even after long years, I still crave more and more of detailed strict mathematical logic in my work. You can never get enough of it. Therefore, if you learn how to build tetris without using a library and using only fundemental tools such as C/C++, you will learn much much much more than just tetris or C/C++. You will learn how to think like a tetris-maker (lol). But if you copy-paste the code from someone else, or a chatbot, you will never learn how to think like a tetris-maker. Will tetris earn you money? no. Will people respect you for it? no. Will you become a super cool master of programming? no. BUT you will have a new power. This new power will lead you to a new idea. this will continue forever. So, this comment turned into an essay for some reason. Anyways hope more people read this.

​@@MrMehrd professional programmer/developer here. I work in industrial advanced systems. Many people have the same misunderstanding about computer code in general. I would like to give more insight into it if I may. I know many famous tech leaders are making bold statements on this topic, but unfortunately they don't provide enough details. You can think of the code generated by a neural network in a similar way to a story written by the same model. The story will have a certain structure to it and this structure is the result of both system prompts (the prompts you dont see) and the training data. Does this mean it is a bad story? No. But it is in essence, a story encapsulated in a bubble of pre-defined rules. This has no problem whatsoever unless you are trying to make something out-of-the-box. The main goal of software development in general is to automate things on a computer, in a way that it will reduce the manual labor. The programming languages exist to combine our natural thoughts and mathematical strictness into a single entity. We can not take away either of these two, otherwise, everything we build in the modern technology would collapse. Many people outside the field, or people that are too obsessed with a programming language, a set of tools, etc. generally tend to show strong fear when faced with a better tool. ChatGPT is the better tool here in many aspects. Why? Well, ChatGPT is an interface to the GPT models, and these models are some of the strongest in the world. They have been trained on vast amounts of data and a lot of effort was put into it. In order to make a better GPT in the future, you can not simply prompt it into the current GPT. This is against the laws of the nature. In order to create something better, we need a combination of tools and knowledge. ChatGPT was built heavily using Python as a programming language, and lots of ML libraries such as PyTorch. Now ChatGPT can WRITE PYTORCH itself! But how? Simple. Because computer code in essence is text content, and when you have a model trained on text content, you should be able to generate more of it. This means you can generate similar content to your training data, create heavily modified versions of it, create non-existent content from billions of combinations of it, create unique patterns , etc. But we have some big problems here. The biggest one is, these state-of-the-art AI models are not intelligent entities. They do not have the ability to make decisions, think, understand or reason. I know it looks like they do all of these, but in reality it is a big circus of estimations and this is fine. What is not fine, is , we can not replace humans with it. It would be like replacing humans with a dishwasher. We can not replace writers, programmers, mathematicians, artists, scientists etc. with an NLP model. For example programming, is not the code, not the syntax, not the operating system, and not the UI of your desktop. Programming could be done with a set of emojis, sticks, bubblegums, if it would be more efficient. The purpose of creating software with code, is to make sure we specified thousands of details that are important to us, turned them into electrical signals, put a lot of logic into it, and make sure we get the results we want from the computer, when we want. We first tried to make it more like english because why not. We failed because then we forgot to add the amount of mathematics and logic we needed into it. We quickly remembered why we had mathematical symbolism in the first place. It was to strictly explain things, in a short but meaningful manner. Then we said, well, let's combine english with symbols and then we will have a toolset that is useful. It worked! We figured out that sometimes we can use a more english-like syntax (such as python, basic etc) and sometimes (when needed) use a more complex way of writing our logic, which takes us to C/C++, Assembly languages, and more. We actually created Python itself, using C! How crazy right? Then we said well, perhaps we should make it even easier for repetitive tasks, and created pure simple tools for everyone to use to create websites, simple apps and get their work done. We made website builders that needed NO CODE AT ALL. We have Excel, Google, etc. Why? To not spend time over and over again on same things. But wait, did we stop using C/C++ or Assembly just because we created Python? No. Did we stop creating very low level code that is too hard to understand? No. Did we stop welding wires just because we already did it before? No. Because we still need to do things with them, to create better versions of the things we already made. Do we still do everything with C? Never. Do we write a lot of C everyday? Yes, when we need to, and sometimes to train our brains, which in return provides us with better ideas and makes us realize more details. These days, I use 4-5 AI chatbots as I write my code. I write certain logic in a mathematical syntax, and sometimes in a specific programming language syntax, and add natural language statements to it. The chatbots generate me all the boilerplate I need and I only need to make small changes in very specific details. These details can only be seen if you know a lot about the thing you are doing within the code. This is also a reason to be able to read, write, understand computer code in different languages if you are dealing with code in your daily life even if you don't write it all the time. What I assume for the future (near) is that we programmers will be more of supervisors. Downside is, we will be under much more stress, always making sure the AI didn't make a small mistake that can collapse the whole system we spent years on. Most probably we will be using mathematical symbolism and natural language expressions in a much much more simple way and it will not look like the code we write today, will be much shorter and brief. When we implements chips into our brains, we will only imagine concepts and generate instant outputs. The funny thing is, we still need to know a lot about advanced logic, mathematics, symbolism, how to think properly for strict concepts like computing or planning. These may seem simple at first, but believe me, even after long years, I still crave more and more of detailed strict mathematical logic in my work. You can never get enough of it. Therefore, if you learn how to build tetris without using a library and using only fundemental tools such as C/C++, you will learn much much much more than just tetris or C/C++. You will learn how to think like a tetris-maker (lol). But if you copy-paste the code from someone else, or a chatbot, you will never learn how to think like a tetris-maker. Will tetris earn you money? no. Will people respect you for it? no. Will you become a super cool master of programming? no. BUT you will have a new power. This new power will lead you to a new idea. this will continue forever. So, this comment turned into an essay for some reason. Anyways hope more people read this.

Bro pls english i don't understand the technicalities😅

@@Paritosh___ these are open source models you can run on consumer hardware. I have a whole 16gb and no GPU, so I've been working with small models. I've picked up a lot of tricks and my data pipelines are pretty clean now. Here's a high level overview of my chain, by model: * Hermes 2 Theta Llama 3 - best Llama 3 8B fine-tune. OpenHermes models have been consistently excellent open source models. This is the latest one, built on Llama 3, and it has extra training and special tokens for JSON output, which means it can label its own responses, assign a tool with a response simultaneously, tons of fun stuff. This is my main model. * Nomic - embedding models, coupled with a vector store are basically a memory librarian. It sorts texts by semantic similarity. If you chunk up everything that enters your app, it will return the most semantically similar text to use as context to answer your prompt - or - RAG. * LlaVa - Vision model. This can understand pictures you feed it, or screenshots of videos or your desktop. This can add a lot of functionality and also scrape pages that can't be scraped by other methods. * Whisper/Bark - Text to Speech and Speech to Text models. More specifically, I use faster-whisper. Bark is a personal preference because it can be prompted to generate other sounds besides speech pretty easily. I have them all stitched together using primarily Ollama. I use the tools from CrewAI and Langchain, but I use my own agent framework.

You said a bunch of nothing. What a waste of characters.

@@Paritosh___ I'm using Ollama and tools from CrewAI and Langchain. I don't use either one's framework, I like to DIY my own agent chains in functions. My primary model is Hermes Theta because of Nous Research's track record with OpenHermes, and it also comes with extra tokens to force a JSON response, which is handy for function calling and context classification. LlaVa is a vision model and can see my desktop at all times. Nomic is my embedding model for RAG Whisper/Bark is my Speech-to-speech pair. Specifically faster-whisper. Bark is a personal preference because it can generate other sounds besides speech pretty easily. They all work together as a general copilot.

I've tried to explain my agent chain twice and yt is deleting it for some reason. I made a copilot with open source models. It's greatly enhanced my life.

helps me breathe

He is just like to wear this

He uses it to help him breathe hehe

False. Use it as a tutor.

@@InnocentiusLacrimosa to each their own, you may want to learn about ur trivial math but it sucks

@@RoqueMatusIII Having worked in education and also in coaching, I truly do think that AIs will (already do) enhance our learning processes. There is nothing noble about going through badly designed documentation or internet forum answers line by line instead of asking context specific questions on how to approach some specific issue. The speed of learning through more focused and relevant advice is a very important quality in the process of learning.

@@InnocentiusLacrimosa Ai sucks, plus I use much better systems like RemNote, and Forest App. These applications already do alot of things that are backed up by years of nueroscience.

went with perplexity pro and there is a year paid, $400 Ty, SIr