2020, Blog, Clustering and Database

What Is Retrieval-Augmented Generation?

Hacker News

NOVEMBER 15, 2023

The Story of the Name Patrick Lewis, lead author of the 2020 paper that coined the term , apologized for the unflattering acronym that now describes a growing family of methods across hundreds of papers and dozens of commercial services he believes represent the future of generative AI. Another great advantage of RAG is it’s relatively easy.

Database

Database AI AI Natural Language Processing

Getting the Most from LLMs: Building a Knowledge Brain for Retrieval Augmented Generation

Mlearning.ai

DECEMBER 21, 2023

In May 2020, researchers in their paper “ Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks ” explored models which combine pre-trained parametric and non-parametric memory for language generation. Vectors are typically stored in Vector Databases which are best suited for searching. What is a Vector Database?

Database

Database AI AI Machine Learning

What is the Snowflake Data Cloud and How Much Does it Cost?

phData

NOVEMBER 9, 2023

This blog was originally written by Keith Smith and updated for 2024 by Justin Delisi. In this blog, we’ll explain what makes up the Snowflake Data Cloud, how some of the key components work, and finally some estimates on how much it will cost your business to utilize Snowflake. What is the Snowflake Data Cloud?

Data Warehouse

Data Warehouse Data Lakes Clustering Cloud Data

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Generative AI Deep Dive: Advancing from Proof of Concept to Production

Understanding User Needs and Satisfying Them

Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

The Project Clinic: Assessing Project Health, Planning, and Execution

Leading the Development of Profitable and Sustainable Products

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Talk to your slide deck using multimodal foundation models hosted on Amazon Bedrock and Amazon SageMaker – Part 2

AWS Machine Learning Blog

APRIL 19, 2024

We stored the embeddings in a vector database and then used the Large Language-and-Vision Assistant (LLaVA 1.5-7b) 7b) model to generate text responses to user questions based on the most similar slide retrieved from the vector database. Claude 3 Sonnet is the next generation of state-of-the-art models from Anthropic.

AWS

AWS ML ML Database

Build a powerful question answering bot with Amazon SageMaker, Amazon OpenSearch Service, Streamlit, and LangChain

AWS Machine Learning Blog

MAY 25, 2023

In the RAG-based approach we convert the user question into vector embeddings using an LLM and then do a similarity search for these embeddings in a pre-populated vector database holding the embeddings for the enterprise knowledge corpus. Select the notebook aws-llm-apps-blog and choose Open JupyterLab.

AWS

AWS Clustering Python ML

Build protein folding workflows to accelerate drug discovery on Amazon SageMaker

AWS Machine Learning Blog

JULY 31, 2023

Genetic databases – A genetic database is one or more sets of genetic data stored together with software to enable users to retrieve genetic data. Several genetic databases are required to run AlphaFold and OpenFold algorithms, such as BFD , MGnify , PDB70 , PDB , PDB seqres , UniRef30 (FKA UniClust30) , UniProt , and UniRef90.

ML

ML ML Database Algorithm

Power BI Tutorial– A Complete Guide

Pickl AI

APRIL 9, 2023

In this blog, we will unfold the benefits of Power BI and key Power BI features , along with other details. In 2020, manufacturing companies majorly adopted the BI tools Key Power BI Features So, what are the key features of Power BI that make it a useful tool for businesses across different industrial spectrums? What is Power BI?

Power BI

Power BI Business Intelligence Business Intelligence Cloud Computing

Analyzing the history of Tableau innovation

Tableau

DECEMBER 1, 2021

In this blog post, I'll describe my analysis of Tableau's history to drive analytics innovation—in particular, I've identified six key innovation vectors through reflecting on the top innovations across Tableau releases. Query allowed customers from a broad range of industries to connect to clean useful data found in SQL and Cube databases.

Tableau

Tableau ML ML Database

Analyzing the history of Tableau innovation

Tableau

DECEMBER 1, 2021

In this blog post, I'll describe my analysis of Tableau's history to drive analytics innovation—in particular, I've identified six key innovation vectors through reflecting on the top innovations across Tableau releases. Query allowed customers from a broad range of industries to connect to clean useful data found in SQL and Cube databases.

Tableau

Tableau ML ML Database

Introduction to LangChain for Including AI from Large Language Models (LLMs) Inside Data…

Heartbeat

JANUARY 5, 2024

Image by Author Large Language Models (LLMs) entered the spotlight with the release of OpenAI’s GPT-3 in 2020. For instance, we may extract data from sources like databases, which we then pass into an LLM and send a processed output to another system. We have seen exploding interest in LLMs and in a broader discipline, Generative AI.

AI

AI AI Data Pipeline Deep Learning

Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 2

AWS Machine Learning Blog

JANUARY 13, 2023

This blog post is co-written with Chaoyang He and Salman Avestimehr from FedML. This dataset comprises a multi-center critical care database collected from over 200 hospitals, which makes it ideal to test our FL experiments. It is available as a set of CSV files, which can be loaded into any relational database system.

AWS

AWS Analytics Analytics Machine Learning

Question answering using Retrieval Augmented Generation with foundation models in Amazon SageMaker JumpStart

AWS Machine Learning Blog

MAY 2, 2023

For example, a health insurance company may want their question answering bot to answer questions using the latest information stored in their enterprise document repository or database, so the answers are accurate and reflect their unique business rules. RAG models were introduced by Lewis et al. For more details, see the GitHub repo.

Algorithm

Algorithm Machine Learning Machine Learning Natural Language Processing

ML Collaboration: Best Practices From 4 ML Teams

The MLOps Blog

DECEMBER 28, 2022

Organization Gigaforce Inc Industry InsurTech provider Team size Gigaforce built an ML team three years ago in 2020 and has a team size of 5-7. Team composition The team comprises domain experts, data engineers, data scientists, and ML engineers. Machine learning collaboration Gigaforce allocates work based on the phase of the project.

ML

ML ML Data Scientist Machine Learning

Against LLM maximalism

Explosion

MAY 17, 2023

For instance, you could extract a few noisy metrics, such as a general “positivity” sentiment score that you track in a dashboard, while you also produce more nuanced clustering of the posts which are reviewed periodically in more detail. So you do have to work around things, and use things like vector databases or other tricks.

Supervised Learning

Supervised Learning Natural Language Processing Clustering Machine Learning

Financial text generation using a domain-adapted fine-tuned large language model in Amazon SageMaker JumpStart

AWS Machine Learning Blog

APRIL 18, 2023

c/o Ernst & Young LLPSeattle, Washington Attention: Corporate Secretary (2) For the purpose of Article III of the Securities Exchange Act of 1934, the registrant’s name and address are as follows:(3) The registrant’s Exchange Act reportable time period is from and includingJanuary 1, 2020 to the present.(4)

ML

ML ML Deep Learning Deep Learning

Healthsea: an end-to-end spaCy pipeline for exploring health supplement effects

Explosion

DECEMBER 14, 2021

In this blog post, I’ll take you on the journey of training different NLP models, creating custom components and assembling them into a spaCy v3 pipeline! ? Clustering health aspects ? What to expect This blog post presents a technical approach to analyzing user reviews and acts as a proof of concept. Segmentation component 2.1

Clustering

Clustering Machine Learning Machine Learning Natural Language Processing

Domain-adaptation Fine-tuning of Foundation Models in Amazon SageMaker JumpStart on Financial data

AWS Machine Learning Blog

APRIL 18, 2023

c/o Ernst & Young LLPSeattle, Washington Attention: Corporate Secretary (2) For the purpose of Article III of the Securities Exchange Act of 1934, the registrant’s name and address are as follows:(3) The registrant’s Exchange Act reportable time period is from and includingJanuary 1, 2020 to the present.(4)

ML

ML ML Deep Learning Deep Learning

Data Science Current

What Is Retrieval-Augmented Generation?

Getting the Most from LLMs: Building a Knowledge Brain for Retrieval Augmented Generation

Webinars

Trending Sources

What is the Snowflake Data Cloud and How Much Does it Cost?

Webinars

Talk to your slide deck using multimodal foundation models hosted on Amazon Bedrock and Amazon SageMaker – Part 2

Build a powerful question answering bot with Amazon SageMaker, Amazon OpenSearch Service, Streamlit, and LangChain

Build protein folding workflows to accelerate drug discovery on Amazon SageMaker

Power BI Tutorial– A Complete Guide

Analyzing the history of Tableau innovation

Analyzing the history of Tableau innovation

Introduction to LangChain for Including AI from Large Language Models (LLMs) Inside Data…

Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 2

Question answering using Retrieval Augmented Generation with foundation models in Amazon SageMaker JumpStart

ML Collaboration: Best Practices From 4 ML Teams

Against LLM maximalism

Financial text generation using a domain-adapted fine-tuned large language model in Amazon SageMaker JumpStart

Healthsea: an end-to-end spaCy pipeline for exploring health supplement effects

Domain-adaptation Fine-tuning of Foundation Models in Amazon SageMaker JumpStart on Financial data

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