Best of GPT — December 2024

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    Article
    Avatar of developsenseDevelopSense·1y

    Voldemort Syndrome

    Since June 2023, James Bach and another researcher have been studying 'syndromes' related to AI chatbots, specifically those based on LLMs and GPTs like ChatGPT. Recently, they identified 'Voldemort Syndrome,' where the chatbot censors specific names, such as 'David Mayer.' The phenomenon suggests both input and output filtering are being used to restrict content. The post highlights the importance of interactive testing and understanding technology to identify issues without requiring deep technical knowledge.

  2. 2
    Video
    Avatar of bytegradByteGrad·1y

    Web Scraping With GPT-4 Vision AI & Playwright Is Ridiculously EASY - I Can't Believe This Works

    AI advancements, particularly GPT-4 Vision AI, have simplified web scraping. Techniques like using network requests directly, scraping from server-side rendered websites via embedded HTML data, and utilizing proxies to avoid detection are discussed. Methods to scrape using both text-based and vision-based approaches with tools like Playwright and Smart Proxy are outlined, all while tapping into modern AI models to efficiently extract data.

  3. 3
    Article
    Avatar of communityCommunity Picks·1y

    HarperJonesGPT/PokerGPT: Pokerstars bot that plays real-time poker using GPT4

    PokerGPT is a sophisticated bot designed for playing 6-player Texas Hold'em on Pokerstars, using the OpenAI GPT-4 API for real-time game analysis and decision-making. It utilizes Tesseract OCR for card and action recognition and includes a GUI for data visualization and audio playback. The bot reads data directly from the Pokerstars client and simulates mouse clicks for automated gameplay. Requirements include Python 3.8+, OpenAI GPT-4 API access, and Tesseract OCR. The bot is tailored for specific screen resolutions and the Pokerstars 6-player table format.

  4. 4
    Article
    Avatar of taiTowards AI·1y

    Build And Train GPT From Scratch

    Learn how to build and train a Generative Pretrained Transformer (GPT) model from scratch using Python and PyTorch. Understand the internal mechanisms of GPT models, including self-attention and multi-head attention. Follow step-by-step instructions to construct the GPT architecture, tokenize data, implement self-attention, and train the model on a dataset. Discover techniques to improve model performance and optimize training and inference processes.

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