{"id":3673,"date":"2023-06-07T10:38:37","date_gmt":"2023-06-07T10:38:37","guid":{"rendered":"http:\/\/blog.kindgeek.com\/?p=3673"},"modified":"2024-10-31T11:15:31","modified_gmt":"2024-10-31T11:15:31","slug":"to-chatgpt-or-not-to-chatgpt-that-is-the-question","status":"publish","type":"post","link":"https:\/\/kindgeek.com\/blog\/post\/to-chatgpt-or-not-to-chatgpt-that-is-the-question","title":{"rendered":"To ChatGPT, or not to ChatGPT: What You Need to Know"},"content":{"rendered":"

Recently updated on October 31, 2024<\/p><\/div>\n

For this article, we had a talk with <\/em>Michael Kramarenko<\/em><\/a>, our CTO, to examine both the hype and criticism aspects of ChatGPT with real-world examples and cases. Here, we’ll also delve into what makes ChatGPT such a groundbreaking tool, and of course, we’ll try to figure out whether to use it or rather stay aside<\/em><\/p>\n\n\n\n

Introduction<\/strong><\/h2>\n\n\n\n

Whether we embrace it or not, our world is already shaped by the presence of ChatGPT and similar tools. <\/p>\n\n\n\n

But like any new tech, these GPT-like tools offer both benefits and risks<\/strong> that we cannot disregard. Hence, the logical question arises, “To be, or not to be?”<\/s> “To ChatGPT, or not to ChatGPT?”.<\/p>\n\n\n\n

Delve into this article to learn some intriguing facts about ChatGPT and have large language models explained superficially.<\/p>\n\n\n\n

Content<\/strong><\/h2>\n\n\n\n
  1. Debunking common ChatGPT myths<\/a><\/li>
  2. Decoding hype around ChatGPT<\/a><\/li>
  3. What makes ChatGPT so revolutionary?<\/a><\/li>
  4. Navigating ChatGPT Criticism <\/a><\/li>
  5. So, to ChatGPT or not to ChatGPT?<\/a><\/li><\/ol>\n\n\n\n<\/a>\n\n\n\n

    Debunking common ChatGPT myths<\/strong><\/h2>\n\n\n\n

    Myth 1: ChatGPT is new<\/strong><\/h3>\n\n\n\n

    ChatGPT is a chatbot \u2013 a type of conversational AI built \u2013 but on top of a Large Language Model.\u00a0What is LLM in AI? It is a specific type of machine learning model that processes, understands, and generates human language. These models are distinguished by their large number of parameters\u2014typically in the billions\u2014and the vast datasets on which they are trained.<\/p>\n\n\n\n

    Although having boomed in late 2022, the technology behind ChatGPT \u2013 Transformer-based LM\/LLM + self-attention mechanisms \u2013 was originally invented<\/a> by the Google Brain team in 2017. However, it is somewhat surprising that eventually they have not capitalized on this innovation.<\/p>\n\n\n\n

    On the other hand, OpenAI pursued the idea and invested lots of time and effort to arrive at the point<\/a> where they are now. And with it, perhaps tens of millions of dollars<\/a> just to train the model. Not to mention daily computing expenses just to keep the model running. <\/p>\n\n\n\n

    Myth 2: ChatGPT understands language the way humans do<\/strong><\/h3>\n\n\n\n

    While ChatGPT can generate impressive responses, using words like “understanding,” “feeling,” and “sense” to describe a communication process with GPT-based tools is incorrect. GPT is about parsing text to tokens, producing fixed-length embeddings, and generating the output sequence conditioned on the encoded input where does ChatGPT get its information from, and the previously generated tokens.<\/p>\n\n\n\n

    ChatGPT’s ability to engage in conversations stems from its advanced capabilities to predict the most suitable next word<\/strong> or phrase<\/strong> based on the context of the input, and chatgpt training data size.<\/p>\n\n\n\n

    Thus, its responses are rather based on probabilities<\/strong> than personal feelings or subjective understanding. ChatGPT is just a sophisticated “word guesser,”<\/strong> so to speak.<\/p>\n\n\n\n

    Myth 3: ChatGPT will replace people.<\/strong><\/h3>\n\n\n\n

    ChatGPT has its limitations<\/strong> and can rather serve as a routine task performer and helper<\/strong>, not a problem solver<\/strong>. <\/p>\n\n\n\n

    But ultimately, only human workers are held accountable<\/strong> for the decision-making part and the outcomes it entails, as GPT-based<\/strong> tools are not infallible<\/strong>.<\/p>\n\n\n\n

    The tool can significantly enhance productivity<\/strong> and efficiency<\/strong>, helping do information processing tasks better and faster. The example of this may be an ai-powered assistant for fintech<\/a>. It provides a quick, personalized, and human-like service to build strong customer relationships that propel business growth and help maximize revenue potential. This assistant allows humans to focus on more complex tasks.<\/p>\n\n\n\n

    Most disruptive technologies are changing professions and the labor market. It’s worth mentioning the times<\/a> when “computers wore skirts” \u2013 here we’re talking about NASA Langley\u2019s computer workers, who later retrained as programmers.  <\/p>\n\n\n\n

    To sum up, only time will tell what the future of the labor market would look like. <\/p>\n\n\n\n<\/a>\n\n\n\n

    Decoding hype around ChatGPT<\/strong><\/h2>\n\n\n\n

    The hype surrounding ChatGPT is characterized by the enthusiasm of millions of people who have eagerly signed up for it. And while social media is abuzz with public awe, each passing day ushers in a plethora of new plugins and extensions. <\/p>\n\n\n\n

    <\/p>\n\n\n\n

    Therefore, if we consider the Gartner hype cycle within present-day reality, it becomes progressively challenging not only to define<\/strong> a plateau<\/strong> point of ChatGPT but at least to see any degree of enlightenment<\/strong> so far.<\/p>\n\n\n\n

    \"\"<\/figure>\n\n\n\n

    Productivity boosting: a key aspect of public hype<\/strong><\/h3>\n\n\n\n

    While ChatGPT has garnered attention for its impressive capabilities, its underlying technology is set to transform <\/strong>the professional<\/strong>, legislative<\/strong>, educational<\/strong>, and social<\/strong> aspects of our lives for its superb ability to enhance <\/strong>human productivity<\/strong> and efficiency <\/strong>across various domains.<\/p>\n\n\n\n

    Recent studies have found that AI assistance increases customer service worker productivity by a prominent 14% and empowers least-skilled workers to complete their tasks 35% faster. Remarkably, agents with 2 months of experience aided by AI performed just as well or better<\/a> than those with 6 months of experience without artificial intelligence.<\/p>\n\n\n\n

    Thus, productivity boosting is the main benefit of ChatGPT and is the main aspect of public hype. <\/p>\n\n\n\n

    But as AI is constantly evolving, its impact<\/strong> on various aspects of our lives is yet to be fully understood<\/strong>.<\/p>\n\n\n\n<\/a>\n\n\n\n

    What makes ChatGPT so revolutionary?<\/strong><\/h2>\n\n\n\n

    Unlike traditional programming, where we develop software and can see the final code, the neural network<\/strong> itself becomes a valuable entity<\/strong>, representing the outcome of an extensively trained multi-billion-parameter network<\/strong>.<\/p>\n\n\n\n

    And that’s the case of revolutionary ChatGPT \u2013 an extensively-trained<\/strong>, enormous 175 billion-parameter neural network<\/strong> that has developed the ability to produce sophisticated<\/a>, human-like outputs. <\/p>\n\n\n\n

    Here are key hype aspects of the ChatGPT tool.<\/p>\n\n\n\n

    \"\"<\/figure>\n\n\n\n

    Transformer-based LLM <\/strong><\/h3>\n\n\n\n

    Is ChatGPT a large language model<\/strong>? Yes, and it operates based on the principles of GPT<\/strong> (Generative pre-trained transformers).\u00a0<\/p>\n\n\n\n