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Atmrix

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Atmrix

About

SN

Satya Nadella

05/20/25

@ Microsoft

A modern knowledge retrieval stack for agents should understand user intent and data context, enabling complex queries to be processed efficiently.

Video

M

Microsoft Build 2025 | Satya Nadella Opening Keynote

@ Microsoft

Microsoft Build 2025 | Satya Nadella Opening Keynote

05/20/25

Related Takeaways

SP

Sundar Pichai

05/27/25

@ The Verge

The future web may not require rendering web pages for agents, suggesting a shift towards databases that agents can query for answers.

SP

Sundar Pichai

06/05/25

@ Lex Fridman

The integration of AI in search aims to improve user engagement by providing more relevant and contextual information.

YC

Y Combinator Cast

10/18/24

@ Y Combinator

Retrieval is crucial for AI agents, requiring them to perform lookups for functions and symbols within the code, which is essential for effective operation.

SC

Sequoia Capital Cast

02/25/25

@ Sequoia Capital

The ultimate goal for future AI agents is to seamlessly integrate various tasks, such as web searching and computer operations, in a more natural and human-like manner.

Gf

Google for Developers Cast

05/23/25

@ Google for Developers

The future of search will shift from merely providing information to delivering intelligence that better understands user needs.

SN

Satya Nadella

05/20/25

@ Microsoft

Building retrieval-augmented generation (RAG) applications requires a sophisticated retrieval system, not just vector search and embeddings.

IF

Isa Fulford

05/08/25

@ Sequoia Capital

Deep research is capable of handling complex queries that traditional search methods struggle with, such as finding specific markets based on multiple constraints.

SC

Sequoia Capital Cast

02/25/25

@ Sequoia Capital

The model is effective at following complex instructions, allowing users to request multiple types of information in one query, such as product details, comparisons, and reviews from various sources.

ZX

Zheng Xue

05/30/25

@ LangChain

The structured data agent translates natural language into SQL queries or API calls, while the unstructured data agent processes various documentations and media to derive insights.