A Comparative Analysis of AI Tools: ChatGPT, Copilot, and Perplexibility AI Search

In the rapidly evolving world of artificial intelligence, three tools have emerged as game-changers in their respective domains: ChatGPT, Copilot, and Perplexibility Search. Each of these tools brings unique capabilities to the table, and this post aims to provide a comparative analysis of their pros, cons, and how they handle a specific type of prompt.

ChatGPT

ChatGPT is an AI model developed by OpenAI that excels in generating human-like text responses. It offers users control over the response’s length, format, style, level of detail, and language. This makes it a versatile tool capable of generating detailed and contextually relevant responses. It can even serve as a round-the-clock customer support assistant. However, it’s not without its drawbacks. For instance, it may promote cheating and plagiarism in academic settings, and its responses can sometimes feel robotic.

link: ChatGPT

Copilot

GitHub Copilot, on the other hand, is a coding assistant that suggests code as you type. It can generate unit test cases, propose code fixes, answer coding questions, and even explain your code. It also suggests refactoring using the context of your codebase and generates commit messages and PR descriptions. However, developers who heavily rely on Copilot risk becoming overdependent on automated suggestions. Additionally, it may generate inaccurate code that appears to be valid.

link: https://www.bing.com/chat

Perplexibility Search

Perplexibility Search is a tool that combines the usefulness of search engines and the generative capabilities of AI chatbots. It provides an interactive and conversational web search experience and uses large language models for better information retrieval and reduced hallucination. However, it lacks a natural language flow, and its responses, while accurate most of the time, can sometimes feel robotic. It is also dependent on facts or information.

Link: Perplexity

Comparative Example

To illustrate how these tools handle a specific type of prompt, let’s consider the financial question: “Should I buy Nvidia shares now or is it overvalued?”

ChatGPT might respond with: “Investing in stocks requires careful analysis of financial data to find out the company’s true worth. This is generally done by examining the company’s profit margins, P/E ratio, dividends, etc. If you’re interested in Nvidia, a good idea would be to start by looking at these factors and comparing them with the company’s performance over the years.”
Copilot might generate a Python function like this:

Python

def should_buy_nvidia_shares(price, pe_ratio):
    if price < 100 and pe_ratio < 30:
        return 'Yes, it is a good time to buy Nvidia shares.'
    else:
        return 'No, Nvidia shares seem to be overvalued.'

Perplexibility Search might respond with: “According to recent reports, Nvidia’s share price is currently at $133.78. Some analysts believe that the shares are overvalued, while others think there’s still room for growth. It’s important to do your own research and consider your financial situation and investment goals before making a decision.”

Conclusion

All three tools, ChatGPT, Copilot, and Perplexibility Search, have their unique strengths and weaknesses. Users should choose the tool that best fits their specific needs and always review and verify the generated content. When it comes to financial decisions, it’s always best to do thorough research and consider seeking advice from a financial advisor.

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