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Google’s AI-powered search experience expands globally to 120+ countries and territories

Google’s AI-powered search experience is rolling out worldwide, after initial launches in select markets, including the U.S., India and Japan. Starting today, the AI-based conversational experience often called SGE, or Search Generative Experience, shall...

Vector Search Is Not All You Need

Retrieval Augmented Generation (RAG) has revolutionized open-domain query answering, enabling systems to supply human-like responses to a wide selection of queries. At the guts of RAG lies a retrieval module that scans an unlimited...

Google’s AI-powered search expands outside U.S. to India and Japan

Google is bringing its generative AI search experience to the primary countries outside the U.S., the corporate announced today, starting with expansions in India and Japan. The brand new AI-powered search feature, also referred...

China’s search engine pioneer unveils open source large language model to rival OpenAI

In February, Sogou founder Wang Xiaochuan said on Weibo that “China needs its own OpenAI.” The Chinese entrepreneur is now inching closer to his dream as his nascent startup Baichuan Intelligence rolled out its...

‘GPT’-based domestic search solution installed in Samsung Web browser

Samsung Electronics' mobile app can be equipped with a domestic search solution based on 'ChatGPT'. Artificial intelligence (AI) startup Liner (CEO Kim Jin-woo) announced on the sixth that it has released 'Liner Co-Pilot', which might...

Document-Oriented Agents: A Journey with Vector Databases, LLMs, Langchain, FastAPI, and Docker Introduction Vector Databases: The Essential Core of Semantic Search Applications Constructing a Document-Oriented Agent Experiment: Understanding...

Leveraging ChromaDB, Langchain, and ChatGPT: Enhanced Responses and Cited Sources from Large Document DatabasesDocument-oriented agents are beginning to get traction within the business landscape. Corporations increasingly leverage these tools to capitalize on internal documentation,...

Document-Oriented Agents: A Journey with Vector Databases, LLMs, Langchain, FastAPI, and Docker Introduction Vector Databases: The Essential Core of Semantic Search Applications Constructing a Document-Oriented Agent Experiment: Understanding...

Leveraging ChromaDB, Langchain, and ChatGPT: Enhanced Responses and Cited Sources from Large Document DatabasesDocument-oriented agents are beginning to get traction within the business landscape. Corporations increasingly leverage these tools to capitalize on internal documentation,...

Similarity Search, Part 5: Locality Sensitive Hashing (LSH) Introduction Shingling MinHashing LSH Function Error rate Conclusion Resources

Explore how similarity information might be incorporated into hash functionS is an issue where given a question the goal is to search out probably the most similar documents to it amongst all of the...

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