What’s the different between LLMs and AI-powered Search Experiences / interfaces? That’s the key question we are answering in this article.

TLDR: Large Language Models (LLMs) are powering many so-called AI-powered Search Experiences right now. Various different LLMs are used in different Search Interfaces. The most prominent LLMs are right now GPT-4 (from Open AI), Gemini (from Google) that power popular search experiences such as ChatGPT, Google Search, Bing Copilot.


What is a LLM?

A large language model (LLM) is a type of artificial intelligence model that is trained to understand and generate human language.

LLMs are capable of processing and generating text in a way that mimics human language, allowing them to perform tasks such as text generation, translation, summarization, and more.

These models are typically trained on vast amounts of text data to improve their ability to understand and generate language. Examples of popular LLMs include GPT-3 (Generative Pre-trained Transformer 3) and BERT (Bidirectional Encoder Representations from Transformers).

What are the most popular LLMs?

Some of the most popular Large Language Models include:

  1. GPT-4 and GPT-3 (Generative Pre-trained Transformer) by OpenAI
  2. BERT (Bidirectional Encoder Representations from Transformers) by Google
  3. T5 (Text-to-Text Transfer Transformer) by Google
  4. XLNet by Google/CMU
  5. RoBERTa (Robustly optimized BERT approach) by Facebook AI
  6. ALBERT (A Lite BERT) by Google
  7. ELECTRA (Efficiently Learning an Encoder that Classifies Token Replacements Accurately) by Google/Stanford
  8. CTRL (Conditional Transformer Language Model) by Salesforce AI
  9. GPT-2 (Generative Pre-trained Transformer 2) by OpenAI
  10. Transformer-XL by Google/CMU

These models have been widely used in various natural language processing tasks such as text generation, translation, summarization, and more.

Large Language Models power AI-searches

Large language models are designed to generate human-like text based on the input they receive. They can answer questions, draft content, provide suggestions, assist in tasks, and more.

Think of LLMs as the backend that power AI-Search Experiences. In other words: If you are using ChatGPT – browsing it as a user on it’s website, it’s the frontend interface. On the other hand, LLMs are at the backend, they power the frontend, but by now ChatGPT for example can also search the web and add citations and links to it. This is a feature of ChatGPT and not GPT-4.

What’s the difference between LLMs and AI powered Search experiences?

LLMs (Large Language Models) and AI-powered search experiences are both advanced technologies that use artificial intelligence to improve search results and user experiences.

However, there are some key differences between the two:

  1. LLMs are language models that are trained on vast amounts of text data to understand and generate human language. They can be used to improve natural language understanding and generation in search engines, chatbots, and other applications. In contrast, AI-powered search experiences use a combination of machine learning algorithms and natural language processing techniques to enhance search results and provide more relevant and personalized recommendations to users.
  2. LLMs are typically used to improve the overall language understanding capabilities of a system, while AI-powered search experiences focus specifically on improving the search functionality and user experience of a website, app, or platform.
  3. LLMs are often used to power conversational AI systems, such as chatbots and virtual assistants, to provide more human-like interactions with users. AI-powered search experiences, on the other hand, are focused on optimizing search results and recommendations based on user behavior and preferences.

In summary, LLMs are more focused on language understanding and generation, while AI-powered search experiences are specifically designed to enhance search functionality and user experiences.


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