AWS Machine Learning Blog

AUGUST 30, 2023

Our latest QnABot releases, v5.4.0+, can now use an LLM to disambiguate customer questions by taking conversational context into account, dynamically generating answers from relevant FAQs or Amazon Kendra search results and document passages. User queries often require a bot to interpret requests based on conversation memory and context.

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ODSC - Open Data Science

NOVEMBER 9, 2023

While traditional keyword-based search tools have long been the standard, they often fall short when it comes to understanding context, intent, and the nuances of human language. This article will explore the evolution of traditional search to generative AI-powered knowledge management strategies being used by data-driven organizations today.

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Hacker News

NOVEMBER 15, 2023

Like a good judge, large language models ( LLMs ) can respond to a wide variety of human queries. We always planned to have a nicer sounding name, but when it came time to write the paper, no one had a better idea,” said Lewis, who now leads a RAG team at AI startup Cohere. So, What Is Retrieval-Augmented Generation? That builds trust.

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AWS Machine Learning Blog

FEBRUARY 14, 2023

Amazon Kendra is an intelligent search service powered by machine learning (ML). It indexes the documents stored in a wide range of repositories and finds the most relevant document based on the keywords or natural language questions the user has searched for.

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AWS Machine Learning Blog

MARCH 26, 2024

We also provide a reference architecture to build an invoice automation pipeline that enables extraction, verification, archival, and intelligent search. For approved documents, you can search all the extracted fields and values using Amazon OpenSearch Service. You can visualize the indexed metadata using OpenSearch Dashboards.

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phData

MARCH 1, 2024

With our accelerator, clinical analysts and coordinators can use a simple interface to quickly filter through millions of patients based on their demographic and clinical data to find those that match specific inclusion criteria for a clinical trial. The accelerator then: Identifies patients who match the criteria.

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Mlearning.ai

JUNE 23, 2023

A database that help index and search at blazing speed. They can understand queries, provide information, and offer personalized recommendations. Content Generation : LLMs can generate human-like text, making them useful for content creation in areas such as writing articles, product descriptions, social media posts, and more.

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AWS Machine Learning Blog

AUGUST 2, 2023

Amazon Kendra is an intelligent search service powered by machine learning (ML). Amazon Kendra reimagines search for your websites and applications so your employees and customers can easily find the content they are looking for, even when it’s scattered across multiple locations and content repositories within your organization.

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Mlearning.ai

JANUARY 3, 2024

Is it relevant to the query? Is the response relevant to the query? GitHub - explodinggradients/ragas: Evaluation framework for your Retrieval Augmented Generation (RAG) pipelines Evaluation Data To evaluate RAG pipelines, the following four data points are recommended A set of Queries or Prompts for evaluation 2. Generation Q.

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Smart Data Collective

SEPTEMBER 13, 2020

Search Engine Watch has a great article on using data analytics for SEO. If you’re active in the world of online marketing, you’ve likely heard about the possibility of using link building for search engine optimization (SEO). What Is Search Engine Optimization (SEO)? Keep in mind that big data drives search engines in 2020.

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Pickl AI

JULY 12, 2023

The search of tools like chat GPT, Grammarly, Quillbot and many others in the league is an example of how AI-enabled platforms are transforming the education vertical. Grammarly: Polishing Your Writing Skills Writing is an essential skill for students, and Grammarly is an AI-powered tool to help them enhance their writing abilities.

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DrivenData Labs

DECEMBER 13, 2022

To be scored correctly, the order of your predictions must match the order of uid s in the submission format. In this section, we'll walk through the process of pulling in matching satellite imagery using Microsoft's Planetary Computer. Query the STAC API for scenes that capture our in situ labels. uid == "garm" ].

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Explosion

OCTOBER 1, 2019

You can now write commands like the following, just as you would when training the parser, entity recognizer or tagger: python -m spacy train en /output /train /dev --pipeline textcat --textcat-arch simple_cnn --textcat-multilabel You can read more about the data format required in the API docs. queries # matches v2.1.8

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Hacker News

DECEMBER 27, 2023

It uses return/jump oriented programming and multiple stages written in the NSExpression/NSPredicate query language, patching the JavaScriptCore library environment to execute a privilege escalation exploit written in JavaScript. This instruction had existed since the early nineties before a patch removed it.

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IBM Journey to AI blog

JUNE 26, 2023

Imagine the possibilities of providing text-based queries and opening a world of knowledge for improved learning and productivity. With generative AI , search becomes dramatically different. Instead of providing links to multiple articles, the user will receive direct answers synthesized from a myriad of data. What is generative AI?

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Kaggle

JULY 29, 2020

I also have experience in building large-scale distributed text search and Natural Language Processing (NLP) systems. The solution consisted of two main parts, a sentence embeddings based search index and a custom BERT QA model to extract column based answers, known as summary tables for a specific list of questions.

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phData

OCTOBER 23, 2023

The first approach, we can directly query the stage location using the $ notation. Method-1: Query Named Stage Directly -- accessing staged JSON data directly using $ notation select t.$1:customer_id::number, 1:customer_id::number, t.$1:first_name::text, 1:first_name::text, t.$1:last_name::text, 1:last_name::text, t.$1:personal_info.social_security_number::text

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Heartbeat

NOVEMBER 16, 2023

This helps quantify how closely the model’s prediction matches the desired output. But what if the evaluation criteria extend beyond mere string matching? These evaluators provide a way to systematically measure how well a language model produces textual output that matches an expected response or meets other specified criteria.

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IBM Journey to AI blog

FEBRUARY 13, 2024

The result will be unusable if a user prompts the model to write a factual news article. Code generation : Software developers and programmers use generative AI to write code. Generative AI allows project managers to search through and create instant summaries of essential business documents.

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AWS Machine Learning Blog

APRIL 11, 2024

By encoding both visual and textual components into unified numerical vectors that encapsulate semantic meaning, it enables rapid indexing, powerful contextual search, and accurate classification of documents. In our solution, when an application wants to perform a semantic search, the search document is first converted into an embedding.

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Mlearning.ai

AUGUST 18, 2023

Dockerizing the Application Writing the Dockerfile Requirements and Dependencies Building the Docker Image 5. Using Docker Compose Writing the docker-compose.yml File Environment Variables and .env PostgreSQL Database Interacting with the Database You can now run SQL commands to query or manage the database.

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ML Review

MARCH 5, 2019

Secondly, we heard (and matched) the tortured wails of researchers distraught at their inability to keep up with progress, even in the most esoteric of AI sub-subfields. The looming monster of AI-progress is unrelenting in its push forward as we desperately tried to digest, quantify and write about its adventures.

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AWS Machine Learning Blog

DECEMBER 6, 2023

Another driver behind RAG’s popularity is its ease of implementation and the existence of mature vector search solutions, such as those offered by Amazon Kendra (see Amazon Kendra launches Retrieval API ) and Amazon OpenSearch Service (see k-Nearest Neighbor (k-NN) search in Amazon OpenSearch Service ), among others.

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Heartbeat

AUGUST 2, 2023

Virtual Assistants : Language models can serve as the foundation for virtual assistants, enabling them to understand and respond to user queries, perform tasks, and provide personalized recommendations. The architecture of this method involves introducing an intermediary layer, like middleware, between the user’s query and the OpenAI APIs.

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AWS Machine Learning Blog

OCTOBER 23, 2023

The result is a platform that matches millions of job seekers with available jobs. Talent.com’s mission is to centralize all jobs available on the web to help job seekers find their best match while providing them with the best search experience. The recommendation system has driven an 8.6%

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AWS Machine Learning Blog

MAY 7, 2024

Only write the masked text in the response. """ In the following example, you define the llama2_chat function that encapsulates sending the prompt to the Llama-2 model. system = """ Your task is to precisely identify any email addresses from the given text and then write them, one per line. Use ' *' for masking text of any length.

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The MLOps Blog

MARCH 28, 2023

In this second installment of the series “Real-world MLOps Examples,” Paweł Pęczek , Machine Learning Engineer at Brainly , will walk you through the end-to-end Machine Learning Operations (MLOps) process in the Visual Search team at Brainly. At the time of this writing, Brainly has over 300 million monthly users across the globe.

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IBM Journey to AI blog

FEBRUARY 14, 2024

Voice-based queries use natural language processing (NLP) and sentiment analysis for speech recognition so their conversations can begin immediately. With text to speech and NLP, AI can respond immediately to texted queries and instructions. AI software can identify when and how resources are used, and match actual demand in real time.

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Dataconomy

APRIL 13, 2023

AutoGPT uses GPT-4 to autonomously develop and manage businesses, such as creating websites, writing articles, generating logos, and marketing products. AutoGPT also has access to the internet and can perform searches, gather information, and interact with popular platforms like ChaosGPT’s tweets. All-In podcast example.

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ML @ CMU

JUNE 5, 2023

ReLM enables writing tests that are guaranteed to come from the set of valid strings, such as dates. We introduce ReLM (MLSys ’23), a system for validating and querying LLMs using standard regular expressions. writing emails , filing taxes ), we’ll want to have more confidence that they work as intended.

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AWS Machine Learning Blog

FEBRUARY 19, 2024

Amazon Bedrock provides a broad range of high-performing foundation models from Amazon and other leading AI companies, including Anthropic , AI21 , Meta , Cohere , and Stability AI , and covers a wide range of use cases, including text and image generation, searching, chat, reasoning and acting agents, and more. b64encode(image_file.read()).decode(

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Mlearning.ai

DECEMBER 21, 2023

The first one being setting up the knowledge sources for efficient search and retrieval and the second one being the five steps of the generation. Smaller chunks are easier to search and to use in LLM context windows. Vectors are typically stored in Vector Databases which are best suited for searching.

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Explosion

OCTOBER 22, 2016

We need to store these memories in a structured way — we want information we can act on, not just text we can search. The graph is contextual so that a query can automatically resolve into ground knowledge as a path in the graph. For example, a query “call John” will invoke the function “call”, and a context “John”.

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Mlearning.ai

AUGUST 5, 2023

Regular Expressions — Searching in the ocean of text. So, in this article, we will explore the different operators of Regular Expressions while we try and match this Sunday, 23 July 2023. Searching directly One of the simplest ways to search a string is to search for the string directly.

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Mlearning.ai

FEBRUARY 9, 2023

You might even need to write custom data crawling code, find public datasets, and find pragmatic ways to augment data to solve the problem. You will need to learn to query different databases depending on which ones your company uses. This will help match your expectations to reality. Remember the principle of Occam’s razor.

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AWS Machine Learning Blog

DECEMBER 5, 2023

Enterprises may want to add custom metadata like document types (W-2 forms or paystubs), various entity types such as names, organization, and address, in addition to the standard metadata like file type, date created, or size to extend the intelligent search while ingesting the documents.

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AWS Machine Learning Blog

JANUARY 31, 2024

Amazon Titan Text Embeddings is a text embeddings model that converts natural language text—consisting of single words, phrases, or even large documents—into numerical representations that can be used to power use cases such as search, personalization, and clustering based on semantic similarity.

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