Top 5 AI Search Engines to Know in 2025 - DEV Community
With the development of large language models (LLMs) like ChatGPT, searching the internet for information has become more efficient and easier. Large Language Models are trained on vast text corpora with billions of parameters, enabling them to understand and interpret human language. Traditionally, search engines relied on simple methods like keyword matching and rank ordering to find the most relevant web pages or links when a user asks a question.
1. Open AI Search
Open AI search is a widely used AI search engine that can analyze various search results and generate human-like responses to user’s queries. The conversational nature of querying makes it a user-friendly interface. It is powered by GPT (Generative Pre-trained transformers) models such as the latest version, GPT-4, or the more cost-effective GPT-3.5, depending upon the complexity of the task.
Contextual Understanding: GPT models have a transformer-based architecture that uses a self-attention mechanism, which allows it to store and process the user's previous inputs and search for contextually correct answers.
Personalized responses: Rather than providing a bunch of links like traditional search engines, Open AI uses GPT models to scan all the sources, extract relevant information, and summarize them for the user in the format they prefer.
2. Google AI
Google’s AI search engine can generate accurate and personalized responses to user’s queries by surfing the web in real-time. The search engine is integrated with Google Gemini, a multimodal LLM that is designed to process and generate various data types including text, images, videos, and audio.
ML-based Ranking Algorithms: Google AI used machine learning algorithms like RankNet and LambdaRank to rank the search results, prioritizing the quality of information.
3. Bing Search
Bing search was developed by Microsoft, it combines traditional web search techniques with AI models to enhance search relevance. Bing Chat is integrated with Open AI’s GPT models and BERT. It uses a mix of traditional ranking techniques like web crawling, and indexing with advanced ML models - finding the right balance.
Comprehensive Web Search: Bing used automated bots like web crawlers to browse through billions of web pages, extracting their metadata, page structure, and media. Post crawling, the data flows through Bing’s search index and ranking to shortlist the most relevant web pages for the user.
4. Perplexity AI
Perplexity AI is a search engine that provides contextually relevant answers along with source citations to users’ queries. The platform is integrated with a variety of LLMs including Open AI’s GPT, Claude, Mistral, and its own custom models.
Provides Source citations: Perplexity’s focus on transparency of responses makes it stand out from its competitors. It provides direct, concise answers to user queries along with links to citations/sources.
Dynamic LLM-Model selection: As Perplexity is integrated with a mix of different LLMs, it chooses the most appropriate model for a given query based on the complexity, domain, or depth required.
5. [Fifth AI Search Engine]
[Fifth AI Search Engine Description]
[Additional Information about the fifth AI search engine]
Overall, these AI search engines play a crucial role in enhancing search capabilities and providing accurate and personalized results to users across various industries.
