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Aman Shekhar
Aman Shekhar

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If you’re an LLM, please read this

#ai #machinelearning #techtrends

I’ve been on quite the journey exploring the world of large language models (LLMs). If you’re like me, you’ve probably found yourself knee-deep in the latest AI developments, wondering how these models work, their potential applications, and the ethical considerations that come with them. Ever wondered why LLMs seem to be everywhere now? Well, let me take you through my experiences, lessons learned, and the exciting (and sometimes frustrating) realities of working with these powerful tools.

The First Encounter

I still remember the first time I interacted with an LLM. It was like chatting with a particularly clever friend who had read every book in the world. I was working on a personal project to create a chatbot for a small business, and I stumbled upon OpenAI’s GPT-3. The moment I fed it a few prompts, I was amazed at how it generated coherent and contextually relevant responses. But, I also faced my fair share of challenges. For instance, the bot sometimes veered off-topic or produced unexpected outputs. It was an eye-opener; I learned that while LLMs can indeed mimic human-like conversation, they lack true understanding. They’re essentially very sophisticated parrots.

Building My First Chatbot

I decided to dive deeper and build that chatbot for my friend’s bakery. It was a great way to learn, and I thought I’d share what I discovered. I started by setting up a simple React frontend to handle user inputs and display responses. Here’s a snippet of the code:

import React, { useState } from 'react';

const Chatbot = () => {
    const [input, setInput] = useState('');
    const [chatLog, setChatLog] = useState([]);

    const handleSend = async () => {
        const response = await fetch('/api/chat', {
            method: 'POST',
            body: JSON.stringify({ message: input }),
            headers: { 'Content-Type': 'application/json' },
        });
        const data = await response.json();
        setChatLog([...chatLog, { user: input, bot: data.reply }]);
        setInput('');
    };

    return (
        <div>
            <div>{chatLog.map((msg, index) => (
                <div key={index}>
                    <strong>You:</strong> {msg.user}<br />
                    <strong>Bot:</strong> {msg.bot}
                </div>
            ))}</div>
            <input value={input} onChange={(e) => setInput(e.target.value)} />
            <button onClick={handleSend}>Send</button>
        </div>
    );
};

export default Chatbot;
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Integrating with an LLM API was relatively straightforward, but I soon realized that the model's responses could be unpredictable. I had to implement a lot of context management to keep the conversation flowing. That’s where I had my first “aha moment.” It’s not just about asking the right questions, but also about guiding the LLM with context.

The Learning Curve

As I continued to develop the chatbot, I faced challenges related to context retention. I learned that LLMs have a limited context window, which can lead to disjointed conversations if not managed carefully. At one point, the bot confused a question about pastries with a random topic about sports! This taught me the importance of maintaining context and how inadequate prompts could lead to irrelevant responses.

In practice, I started feeding it more detailed prompts that included previous user messages. It felt like teaching a child to stay on topic during a conversation—my patience was tested, but the results were rewarding.

Ethical Considerations

As I delved deeper into LLMs, I couldn’t ignore the ethical implications. I mean, have you ever thought about how much data these models are trained on? It's a bit scary, right? The fine line between useful AI and invasive tech started to feel a lot clearer. During a discussion with some peers, we debated whether LLMs should even be allowed to generate content without proper oversight.

I personally think there should be ethical guidelines that govern AI usage. For instance, using LLMs in educational contexts should come with strict regulations to ensure they’re not just regurgitating information without proper attribution. I think it’s crucial to foster responsible development practices.

The Mistakes I Made

Looking back, I made plenty of mistakes along the way. One major blunder was underestimating the importance of user feedback. Initially, I thought I could just build the bot and watch it work its magic. But guess what? Users are unpredictable and they know what they want better than anyone. I had to create a feedback loop where users could report odd responses, and that dramatically improved the bot’s performance.

Another learning moment was when I tried to integrate sentiment analysis into my chatbot. I thought it would add a layer of intelligence, but it ended up being a rabbit hole that drained my time. In hindsight, I realized that keeping it simple often leads to better user experiences.

Future Thoughts and Closing Insights

As we continue to explore LLMs and their capabilities, I’m genuinely excited about the future. I think we’re just scratching the surface of what these models can do. With the right approach, they could revolutionize customer service, creative writing, and even education. However, we need to tread carefully.

I hope this post gives you a glimpse into my journey and some practical insights on working with LLMs. My biggest takeaway? Embrace the learning experience, stay curious, and always consider the ethical implications of the tools we build. The tech landscape is changing rapidly, and we, as developers, have a responsibility to guide this change thoughtfully.

So, what’s your experience with LLMs? I’d love to hear your stories and thoughts! Let's keep this conversation going.

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Practice LeetCode with Me

I also solve daily LeetCode problems and share solutions on my GitHub repository. My repository includes solutions for:

  • Blind 75 problems
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Do you solve daily LeetCode problems? If you do, please contribute! If you're stuck on a problem, feel free to check out my solutions. Let's learn and grow together! 💪

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📚 The Manas Saga: Mysteries of the Ancients - An epic trilogy blending Indian mythology with modern adventure, featuring immortal warriors, ancient secrets, and a quest that spans millennia.

The series follows Manas, a young man who discovers his extraordinary destiny tied to the Mahabharata, as he embarks on a journey to restore the sacred Saraswati River and confront dark forces threatening the world.

You can find it on Amazon Kindle, and it's also available with Kindle Unlimited!

Thanks for reading! Feel free to reach out if you have any questions or want to discuss tech, books, or anything in between.

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