Exploring GPT-4: AI Programming Capabilities and Limitations (DEMO)

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This article is a summary of a YouTube video "๐Ÿ”ด PROBANDO GPT-4 - ยฟEs mejor que ChatGPT? ยฟPrograma mejor? (DEMO)" by Dot CSV
TLDR The video discusses various topics related to programming and AI, including the capabilities and limitations of GPT-4, the potential for AI to generate code and impact the job market, and the need for accessible programming tools, while also highlighting the importance of security and the potential for future advancements in the field.

Timestamped Summary

  • ๐Ÿค–
    00:00
    GPT-4's release brings new possibilities for language models with its multimodal capabilities and 32,000 token context window.
  • ๐ŸŽฎ
    09:13
    GPT-4 can learn and implement simple games, but requires hyper parameter tuning and may encounter response limit issues.
  • ๐Ÿงฎ
    22:28
    GPT-4 struggles with certain math operations, but connecting language models to calculators can yield correct results.
  • ๐Ÿงฉ
    38:52
    Creating and solving riddles requires clear language and logical reasoning, as demonstrated by an example riddle about Jennifer traveling at high speeds.
  • ๐ŸŽน
    52:16
    AI can generate high-quality code faster and cheaper than humans, but it's important to be aware of the changing job market.
  • ๐Ÿค”
    1:02:54
    OpenAI's decision to keep the internal workings of gpt 4 private is concerning for the field of Deep learning and could lead to other companies following suit.
  • ๐ŸŽน
    1:15:32
    The speaker encountered issues with their piano file notes and attempted to fix it with a code, but faced further problems. ๐Ÿ•น๏ธ Implementing Doom in JavaScript and HTML requires extensive programming knowledge and effort. ๐Ÿ› ๏ธ The speaker hopes to see a tool that helps non-programmers create projects, but not for safety control systems, and wants it to be more accessible. ๐ŸŽจ The speaker shares code for creating a graphics processing pipeline with affine transformation matrices and analyzes potential overfitting. ๐Ÿ” The speaker encountered an error in their Jelly Matrix library implementation and needs to troubleshoot further. ๐Ÿ‘จโ€๐Ÿ’ป The speaker discusses iterative programming and the potential for future optimization and automation in code debugging.
  • ๐Ÿ‘จโ€๐Ÿซ
    1:30:30
    ๐Ÿ’ป The arrival of new educational tools like GPT-4 may require a rethinking of the current educational system as many skills being taught in class may become outdated in the labor market. ๐Ÿ›๐Ÿ’ป Ensure correct version and creation of Matrix library, correct code by initializing matrix, verify correct loading of library and Matrix file, download library if necessary, and extend odyssey while leaving only Flappy Bird to finish. ๐Ÿ”๐Ÿ’ป Modern computing is experiencing an unprecedented revolution, but we must be aware of potential security issues with applications like Duolingo and Spotify. ๐ŸŒŸ๐Ÿ’ป There are two parallel revolutions happening in the field of generative models, with tools like Control Net and GPT-4 leading the way towards a future of limitless possibilities. ๐Ÿ’ป๐Ÿ“ Microsoft may integrate GPT-4 into native software like Word and Excel, but these systems are still experimental and may have unknown problems or vulnerabilities.
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This article is a summary of a YouTube video "๐Ÿ”ด PROBANDO GPT-4 - ยฟEs mejor que ChatGPT? ยฟPrograma mejor? (DEMO)" by Dot CSV
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