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#machinelearning

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Michael Martinez :verified:

"Search With Stateful Chat" patent (Cf. patents.google.com/patent/US20 ) - appears to describe the Gemini app for smartphones.

"Method for Text Ranking with Pairwise Ranking Prompting" (Cf. patents.google.com/patent/US20 ) - documents an experimental process described in this research paper titled "Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting" (Cf. arxiv.org/pdf/2306.17563 ). There is no indication this was introduced into a live agentic system like Gemini.

"User Embedding Models for Personalization of Sequence Processing Models" (Cf. patents.google.com/patent/WO20 ) - documents an experimental process for improving recommender (sub-)systems (like movie searches) that incorporate large language models. The process is described in this research paper titled "User Embedding Model for Personalized Language Prompting" (Cf. arxiv.org/pdf/2401.04858 ).

"Systems and methods for prompt-based query generation for diverse retrieval" (Cf. patents.google.com/patent/WO20 ) - updates a 2022 patent for a process named PROMPTAGATOR that generates queries more efficiently based on a small number of examples, as described in this research paper titled "Promptagator - Few-shot Dense Retrieval from 8 Examples" (Cf. arxiv.org/pdf/2209.11755 ). This could be used to generate query fan-outs (but query fan-out has been used in multiple systems at least since the 1990s, so there are many implementations).

"Instruction Fine-Tuning Machine-Learned Models Using Intermediate Reasoning Steps" (Cf. patents.google.com/patent/US20 ) - documents an older method for fine-tuning instructions submitted to LLMs, as described in this 2022 research paper titled "Scaling Instruction-Finetuned Language Models" (Cf. jmlr.org/papers/volume25/23-08 ). The work has been superseded by this paper titled "Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models" (Cf. arxiv.org/pdf/2305.14705 ).

This is the AI Overviews patent, titled "Generative summaries for search results" (Cf. patents.google.com/patent/US11 )

patents.google.comUS20240289407A1 - Search with stateful chat - Google Patents Implementations are described herein for augmenting a traditional search session with stateful chat—via what will be referred to as a “generative companion”—to facilitate more interactive searching. In various implementations, a query may be received, e.g., from a client device operated by a user. Contextual information associated with the user or the client device may be retrieved. Generative model (GM) output may be generated based on processing, using a generative model, data indicative of the query and the contextual information. Synthetic queries may be generated using the GM output, and search result documents (SRDs) may be selected. State data indicative of: the query, contextual information, one or more of the synthetic queries, and the set of search result documents, may be processed to identify a classification of the query. Based on the classification downstream GM(s) may be selected and used to generate one or more additional GM outputs.
#google#aioverviews#aimode
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pipTrends

In this article, Vitalii Honchar explained how to build AI-powered apps that can chat with uploaded PDF files. He showed how to implement Retrieval Augmented Generation (RAG) using FastAPI for the API and LangChain to interact with OpenAI.

vitaliihonchar.com/insights/py

Vitalii HoncharPython RAG API Tutorial with LangChain & FastAPI – Complete GuideLearn how to build a Retrieval-Augmented Generation (RAG) PDF chat service using FastAPI, Postgres pgvector, and OpenAI API in this step-by-step tutorial.
#python#Programming#PythonProgramming
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Joey de Villa 🪗

Want a head start on #AI #programming and #machinelearning at a discount? For the next 13 days, you can get the 18 O’Reilly books on those topics for $25 thanks to Humble Bundle’s “Machine Learning, AI, and Bots” bundle!

Global Nerdy article on the Humble Bundle deal:
globalnerdy.com/2025/06/03/get

Humble Bundle deal:
humblebundle.com/books/machine

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