Is ChatGPT Really a Google Killer?

Is ChatGPT Really a Google Killer?

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    ChatGPT has been touted as a Google killer many times before. It is often compared to the search engine giant. ChatGPT is better than Google because it is faster, more private and has more features. Is ChatGPT the next big thing? Let’s talk about it.

    chatgpt ai chatbot

    What is ChatGPT? 

    ChatGPT is a conversation AI software known as a chatbot trained to answer real-life queries. Although the intention is quite similar to search Engines, ChatGPT is much different than that, in the sense that ChatGPT is a dialogue-based software and gives answers in dialogues based on the data it has been trained on, while search engines maintain an index (a database of all relevant documents in the internet that is dynamically ranked based on a pre-defined set of dynamic ranking factors each time a search query is placed.

    How can ChatGPT influence Search Engines?

    Although Search Engines traditionally provide the most relevant information on the internet based on the search query, recently, Google has made great headways into giving quick answers in terms of Featured Snippets and structured data in SERPs.

    This is possible with Google’s recent advances in Natural Language Processing and AI in the form of several updates, including Rankbrain, BERT and Lambda.

    Lambda is the most significant as this uses similar Transformer architecture of neural networks, trained on 137B parameters and 1.57 Trillion words among publicly available data and documents.

    Is it true that Open AI uses the same Lambda Architecture as Google?

    It needs to be more accurate to say that OpenAI uses the same Lambda architecture as Google. The Lambda architecture is a generic architecture for building data processing systems that Nathan Marz first described in his book “Big Data.” It uses a batch, seed, and serving layer to process data in real-time. 

    The batch layer processes data in batch mode, while the speed layer processes data in real-time using a stream processing system. The serving layer is used to store and query the processed data. Google and other companies have used the Lambda architecture to build large-scale data processing systems.

    OpenAI, on the other hand, is a research organisation that focuses on developing and promoting advanced artificial intelligence technologies. The organisation has developed several machine learning models, including the GPT (Generative Pre-training Transformer) model, a natural language processing model that uses the Transformer architecture. 

    The Transformer architecture is an encoder-decoder architecture that uses self-attention mechanisms to process input data and generate output. It is designed to be efficient and effective for various natural language processing tasks.

    Similarity: 

    Like LaMDA, ChatGPT uses a supervised-learning model, where human AI trainers are given access to model suggestions to craft responses and train the model playing both sides—the user and AI assistant. Following this, the trainers ranked the responses from the chatbot’s conversation with them and the sampled alternative completions based on quality. 

    What Google Lambda Lacks:

    Even though there have been numerous mistakes accounted for by clients on the yield delivered by ChatGPT, one of the more intriguing angles about OpenAI’s model is that the GPT-3.5 engineering utilises a reinforcement learning model (RLHF), a prize-based system dependent on human input, consequently improving it step by step.

    Then again, LaMDA doesn’t utilise RLHF.

    Evolution of Dialogue-Based Models: Google Lambda and OpenAI’s ChatGPT

    Both ChatGPT and Google have been developed as a dialogue-based models. However, the actual feel of a dialogue or conversation is quite different in both cases.

    Scale AI’s Riley Goodside compares the outputs generated by ChatGPT and LaMDA, referring to the former as an “unlovable C-3PO”. While the answers from ChatGPT appear to be more of a Q&A format, LaMDA’s responses are friendly and, in reality, “conversational”.

    This can be attributed to the fact that LaMDA is trained on dialogues, while ChatGPT is said to have been trained on web texts.

    Additionally, OpenAI’s conversational AI has been criticised for producing shallow content which can appear to be lifted from Wikipedia. The AI has also earned criticism for providing incorrect information, generating fake quotes, and referencing nonexistent sources.

    Here is a popular reference from Google’s Cassie Kozyrkov, who highlights the flaws of ChatGPT > https://kozyrkov.medium.com/introducing-chatgpt-aa824ad89623

    When prompted on how ChatGPT is related to GAN, it promptly answered that it is a variant of GAN, which is grossly inaccurate.

    What should have been mentioned in the dialogue was how the model learns from its actions. The response was entirely different and correct when presented with the same prompt. It stated, “ChatGPT uses a neural network architecture known as a transformer, which is designed to process and analyse large amounts of data.”

    Access to the Internet

    The most important consideration of ChatGPT is that unlike popular AI applications like Google Assistant and Siri, ChatGPT has limited access to the internet.

    Here’s ChatGPT’s response when asked about its limitations: 

    And that training data is before 2021, as per ChatGPT’s home page.

    This is further evident when we searched for competitors of Websites like Apple and OpenAI; ChatGPT was able to share a fair response; however, when asked about competitors of newly found popular organisations like SliceLife.

    Advanced Functions Like WebScraping

    Web scraping is a complicated task. Although ChatGPT cannot explicitly scrape the web, it performs certain Web scraping operations using Python and applications like beautiful soup.

    web scrape https://books.toscrape.com/ using Python and beautiful soup

    Here’s the code.

    And here’s the data extracted.

    Web scraping without happening to code is marvellous in my eyes.

    Disability to Detect Intent

    One of the major drawbacks of ChatGPT is that it cannot detect certain well-known entities and websites on the internet.

    For example, when asked about Neil Patel, ChatGPT can quickly detect who Neil Patel is and what he does.

    However, when asked about npdigital.com, which is Neil Patel’s Website, ChatGPT cannot identify the same.

    Browsing the About Us page section of the website would give a clear relationship between Neil Patel and NPDigital. Google would have easily created the semantic relationship between the two entities and shared a relevant answer. However, the same cannot be done by ChatGPT. 

    ChatGPT can only answer on data that it was trained. Training needs to be updated to return answers on new data. 

    On the other hand, Google’s AI was specifically created to tackle new queries it receives daily.

    Final Thoughts

    Without a doubt, I’m incredibly impressed by ChatGPT. OpenAI has exceeded expectations with this remarkable achievement! I strongly urge everyone to try it; its endless possibilities should be on your radar.

    But is it really a Google Killer? Not yet. Google is still way ahead in understanding Natural Language and identifying and training itself with new data on the internet, an ability that ChatGPT lacks.

    FAQ

    ChatGPT is an AI chatbot designed to answer real-life queries through dialogue. Unlike search engines that index web documents, ChatGPT provides conversational responses based on training data, offering interactive and context-aware answers rather than a list of links or documents.

    ChatGPT focuses on conversational answers, whereas Google ranks and indexes web content. ChatGPT provides context-aware dialogue, while Google delivers links and structured snippets. ChatGPT is faster, private, and offers interactive responses, but it cannot fully replace search engines for live web information.

    No, ChatGPT has limited internet access. Its responses are based on pre-2021 training data and cannot fetch real-time information. While it can answer general queries, it may not recognize newly launched products, companies, or websites.

    ChatGPT and Google LaMDA use similar Transformer-based architectures for natural language processing. However, ChatGPT incorporates reinforcement learning with human feedback, while LaMDA does not. This approach allows ChatGPT to improve responses over time based on user interactions.

    ChatGPT cannot directly scrape the web, but it can assist in generating web scraping code using Python libraries like Beautiful Soup. Users can extract structured data from websites by running the code externally.

    ChatGPT cannot access live web data, detect certain websites or entities, or guarantee completely accurate answers. It may produce shallow content, outdated information, or occasional inaccuracies, and cannot interpret user intent perfectly in all cases.

    Yes, ChatGPT can enhance customer support, automate responses, and assist in content creation. Its dialogue-based interface improves user experience, although businesses must be aware of its limitations regarding real-time data and accuracy.

    ChatGPT learns through supervised training and reinforcement learning with human feedback (RLHF). Trainers review model suggestions, rank responses, and guide improvements, gradually enhancing accuracy and relevance over time.

    Not entirely. While ChatGPT can answer queries interactively and quickly, it cannot index or rank the internet’s vast content. It complements search engines but is not a complete replacement for real-time, live web search.

    ChatGPT emphasizes privacy by not storing individual user interactions for live web indexing. Conversations remain confidential within usage limits, but users should avoid sharing sensitive personal or financial information for safety.

    Summary of the Page - RAG-Ready Highlights

    Below are concise, structured insights summarizing the key principles, entities, and technologies discussed on this page.

    ChatGPT is often labeled a potential “Google killer,” but the comparison is misleading. While ChatGPT is a dialogue-based AI trained to answer queries conversationally, Google Search operates through a dynamic index of the entire web supported by advanced ranking algorithms. Google’s advances in NLP, such as RankBrain, BERT, and LaMDA, are designed to interpret real-time queries at scale. Although both ChatGPT and LaMDA use transformer-based architectures, ChatGPT’s RLHF (Reinforcement Learning from Human Feedback) gives it an edge in iterative learning, while LaMDA lacks this reinforcement layer. However, Google’s models are optimized for understanding new, unseen information on the web, something ChatGPT cannot do with its static, pre-2021 training data.

    ChatGPT’s limitations become clear when evaluating its ability to access live information, detect intent, or understand newly established entities. Unlike Google Assistant or Google Search, ChatGPT does not have real-time web access, which leads to outdated responses and gaps in awareness of newer companies or websites. It also struggles to consistently recognize semantic relationships, for example, identifying a well-known figure like Neil Patel but failing to connect him to his company’s website. Additionally, ChatGPT can generate shallow, incorrect, or fabricated information, misidentify technical concepts, and mimic content from sources like Wikipedia. These limitations highlight Google’s continued dominance in query relevance, semantic understanding, and real-time information retrieval.

    While ChatGPT demonstrates impressive capabilities, such as generating code for web scraping or answering complex queries, it is not yet a replacement for Google. Search engines are built to handle billions of new pages and queries daily, continuously training on fresh data and optimizing results for accuracy and intent. ChatGPT, on the other hand, excels as a conversational assistant but lacks the infrastructure for dynamic indexing and real-time web comprehension. For now, ChatGPT enhances how users interact with information but does not displace traditional search engines. The future likely lies in hybrid models where conversational AI and search algorithms complement one another rather than compete directly.

    Tuhin Banik - Author

    Tuhin Banik

    Thatware | Founder & CEO

    Tuhin is recognized across the globe for his vision to revolutionize digital transformation industry with the help of cutting-edge technology. He won bronze for India at the Stevie Awards USA as well as winning the India Business Awards, India Technology Award, Top 100 influential tech leaders from Analytics Insights, Clutch Global Front runner in digital marketing, founder of the fastest growing company in Asia by The CEO Magazine and is a TEDx speaker and BrightonSEO speaker.