• Types of AI Explained in a few Minutes – AI Glossary

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    1️⃣ 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 (𝗔𝗜) – The broadest category, covering automation, reasoning, and decision-making. Early AI was rule-based, but today, it’s mainly data-driven.
    2️⃣ 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 (𝗠𝗟) – AI that learns patterns from data without explicit programming. Includes decision trees, clustering, and regression models.
    3️⃣ 𝗡𝗲𝘂𝗿𝗮𝗹 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀 (𝗡𝗡) – A subset of ML, inspired by the human brain, designed for pattern recognition and feature extraction.
    4️⃣ 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 (𝗗𝗟) – Multi-layered neural networks that drives a lot of modern AI advancements, for example enabling image recognition, speech processing, and more.
    5️⃣ 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿𝘀 – A revolutionary deep learning architecture introduced by Google in 2017 that allows models to understand and generate language efficiently.
    6️⃣ 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 (𝗚𝗲𝗻𝗔𝗜) – AI that doesn’t just analyze data—it creates. From text and images to music and code, this layer powers today’s most advanced AI models.
    7️⃣ 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗣𝗿𝗲-𝗧𝗿𝗮𝗶𝗻𝗲𝗱 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿𝘀 (𝗚𝗣𝗧) – A specific subset of Generative AI that uses transformers for text generation.
    8️⃣ 𝗟𝗮𝗿𝗴𝗲 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹𝘀 (𝗟𝗟𝗠) – Massive AI models trained on extensive datasets to understand and generate human-like language.
    9️⃣ 𝗚𝗣𝗧-4 – One of the most advanced LLMs, built on transformer architecture, trained on vast datasets to generate human-like responses.
    🔟 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 – A specific application of GPT-4, optimized for conversational AI and interactive use.

  • Emmanuel Tsekleves – Writing Research Papers

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    Here’s the journey of crafting a compelling paper:

    1️. ABSTRACT
    This is your elevator pitch.
    Give a methodology overview.
    Paint the problem you’re solving.
    Highlight key findings and their impact.

    2️. INTRODUCTION
    Start with what we know.
    Set the stage for our current understanding.
    Hook your reader with the relevance of your work.

    3️. LITERATURE REVIEW
    Identify what’s unknown.
    Spot the gaps in current knowledge.
    Your job in the next sections is to fill this gap.

    4️. METHODOLOGY
    What did you do?
    Outline how you’ll fill that gap.
    Be transparent about your approach.
    Make it reproducible so others can follow.

    5️. RESULTS
    Let the data speak for itself.
    Present your findings clearly.
    Keep it concise and focused.

    6️. DISCUSSION
    Now, connect the dots.
    Discuss implications and significance.
    How do your findings bridge the knowledge gap?

    7️. CONCLUSION
    Wrap it up with future directions.
    What does this mean for us moving forward?
    Leave the reader with a call to action or reflection.

    8️. REFERENCES
    Acknowledge the giants whose shoulders you stand on.
    A robust reference list shows the depth of your research.