AI News

SEPTEMBER 27, 2024

” He notes it’s powered by “a compound AI system that continuously learns from usage across an organisation’s entire data stack, including ETL pipelines, lineage, and other queries.”

Large Language Models 308

Large Language Models Big Data Explainability ETL 308

Marktechpost

JUNE 15, 2024

You can stay ahead with Lightski since it constantly absorbs the latest AI developments.

ChatGPT 111

ChatGPT ETL Data Scientist Artificial Intelligence 111

AWS Machine Learning Blog

MARCH 5, 2025

To scale ground truth generation and curation, you can apply a risk-based approach in conjunction with a prompt-based strategy using LLMs. Its important to note that LLM-generated ground truth isnt a substitute for use case SME involvement. To convert the source document excerpt into ground truth, we provide a base LLM prompt template.

Generative AI 76

Generative AI LLM AI AI 76

AWS Machine Learning Blog

JUNE 25, 2024

The raw data is processed by an LLM using a preconfigured user prompt. The LLM generates output based on the user prompt. Prerequisites This post is intended for developers with a basic understanding of LLM and prompt engineering. We use an LLM from Amazon Bedrock to generate a category label for each piece of feedback.

Automation 117

Automation Prompt Engineer Prompt Engineering Categorization 117

Marktechpost

MARCH 22, 2024

This facilitates a series of data transformations and enhances the effectiveness of the proposed LLM-based system. Bootstrapping ETL pipelines using the provided data transformation greatly reduces the user’s burden of writing their code.

Machine Learning 135

Machine Learning Explainability Categorization ETL 135

AWS Machine Learning Blog

FEBRUARY 2, 2024

Overview of RAG The RAG pattern lets you retrieve knowledge from external sources, such as PDF documents, wiki articles, or call transcripts, and then use that knowledge to augment the instruction prompt sent to the LLM. This allows the LLM to reference more relevant information when generating a response.

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ETL DevOps LLM Generative AI 109

AWS Machine Learning Blog

JUNE 18, 2024

Cost-effective – The solution should only invoke LLM to generate reusable code on an as-needed basis instead of manipulating the data directly to be as cost-effective as possible. LLMs excel at writing code and reasoning over text, but tend to not perform as well when interacting directly with time-series data.

Generative AI 118

Generative AI Data Ingestion Python LLM 118

Bugra Akyildiz

JANUARY 20, 2025

Berkeley researchers wrote a new mechanism to create diverse training dataset for a variety of different “personas” and through these personas to diversity the training corpus being used to train the LLM. This library is designed to offer valuable insights into the reliability of an LLM's structured outputs.

Python 52

Python LLM OpenAI ETL 52

Marktechpost

JULY 21, 2024

For instance, Palimpzest offers a declarative approach to data cleaning and ETL tasks, introducing a convert operator for entity extraction and an AI-based filter. It supports complex query patterns, including joins, aggregation, ranking, and search functions, beyond the capabilities of row-wise LLM UDFs.

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ETL LLM ML Large Language Models 108

Bugra Akyildiz

JUNE 29, 2024

Analytics/Answers are included(batteries included in LLM): In the consumption of the data after data janitor work, we no longer have to depend on tables, spreadsheets or any other your favorite analytics tool for messaging and formatting this dataset to build the decks/presentations that you want to communicate the insights and learnings.

LLM 40

LLM Big Data Data Quality ETL 40

AWS Machine Learning Blog

JANUARY 10, 2024

Shamika Ariyawansa , serving as a Senior AI/ML Solutions Architect in the Healthcare and Life Sciences division at Amazon Web Services (AWS),specializes in Generative AI, with a focus on Large Language Model (LLM) training, inference optimizations, and MLOps (Machine Learning Operations).

ML 117

ML Machine Learning Data Scientist ETL 117

Unite.AI

SEPTEMBER 6, 2024

Essentially, it performs ETL (Extract, Transform, Load) on the left side, powering experiences via APIs on the right side. Additionally, Pryon provides the flexibility to choose a public, custom, or Pryon-developed large language model (LLM), making the implementation process seamless and highly customizable.

Large Language Models 144

Large Language Models ETL Responsible AI Computer Vision 144

AWS Machine Learning Blog

SEPTEMBER 1, 2023

Furthermore, we deep dive on the most common generative AI use case of text-to-text applications and LLM operations (LLMOps), a subset of FMOps. LLM-powered evaluation – In this scenario, the prompt testers are replaced by an LLM, ideally one that is more powerful (although perhaps slower and most costly) than the ones being tested.

Generative AI 121

Generative AI Prompt Engineer Prompt Engineering ML 121

Bugra Akyildiz

JUNE 18, 2023

By taking a data-centric approach to AI MindsDB brings the process closer to the source of the data minimizing the need to build and maintain data pipelines and ETL’ing, speeding up the time to deployment and reducing complexity. Personalized Segment Anything Model (SAM) , termed as PerSAM.

LLM 52

LLM Deep Learning Large Language Models ETL 52

TheSequence

MAY 21, 2023

🔎 ML Research RL for Open Ended LLM Conversations Google Research published a paper detailing dynamic planning, a reinforcement learning(RL) based technique to guide open ended conversations. Self-Aligned LLM IBM Research published a paper introducing Dromedary, a self-aligned LLM trained with minimum user supervision.

Generative AI 64

Generative AI ML Engineer ETL LLM 64

AWS Machine Learning Blog

SEPTEMBER 6, 2024

RAG is a methodology to improve the accuracy of LLM responses answering a user query by retrieving and inserting relevant domain knowledge into the language model prompt. Tuning chunking and indexing in the retriever makes sure the correct content is available in the LLM prompt for generation.

Generative AI 88

Generative AI LLM AI AI 88

AWS Machine Learning Blog

APRIL 16, 2024

You can use these connections for both source and target data, and even reuse the same connection across multiple crawlers or extract, transform, and load (ETL) jobs. This adaptation is facilitated through the use of LLM prompts. To host your LLM as a SageMaker endpoint, you generate several artifacts.

Data Scientist 108

Data Scientist Generative AI Machine Learning ML 108

ODSC - Open Data Science

OCTOBER 9, 2024

Efficient Incremental Processing with Apache Iceberg and Netflix Maestro Dimensional Data Modeling in the Modern Era Building Big Data Workflows: NiFi, Hive, Trino, & Zeppelin An Introduction to Data Contracts From Data Mess to Data Mesh — Data Management in the Age of Big Data and Gen AI Introduction to Containers for Data Science / Data Engineering (..)

Software Engineer 40

Software Engineer Software Development DevOps Machine Learning 40

Flipboard

NOVEMBER 24, 2023

Anthropic, an AI safety and research lab that builds reliable, interpretable, and steerable AI systems, is one of the leading AI companies that offers access to their state-of-the art LLM, Claude, on Amazon Bedrock. Let’s combine these suggestions to improve upon our original prompt: Human: Your job is to act as an expert on ETL pipelines.

ETL 158

ETL Prompt Engineer Prompt Engineering Generative AI 158

Unite.AI

DECEMBER 11, 2024

It supports ETL/ELT, automation, API management, and secure deployments across cloud, on-premises, and hybrid environments. SnapLogic is an AI-powered integration platform that streamlines data and application workflows with no-code tools and over 1,000 pre-built connectors.

Automation 130

Automation AI AI ETL 130

AWS Machine Learning Blog

AUGUST 2, 2024

LLM chain service – This service orchestrates the solution by invoking the LLM models with a fitting prompt and creating the response that is returned to the user. Query variants – Prior to retrieving documents from the database, multiple variants of the user query are generated using an LLM.

Generative AI 109

Generative AI LLM Machine Learning Data Scientist 109

AWS Machine Learning Blog

SEPTEMBER 18, 2024

As an early adopter of large language model (LLM) technology, Zeta released Email Subject Line Generation in 2021. ZOE is a multi-agent LLM application that integrates with multiple data sources to provide a unified view of the customer, simplify analytics queries, and facilitate marketing campaign creation.

Machine Learning 111

Machine Learning Data Scientist ML Data Ingestion 111

Unite.AI

MAY 21, 2024

This will help them ensure data quality and speed – elements that are critical for driving valuable insights and fueling AI and LLM models. Before Exasol, Helsana relied on various reporting tools with data warehouses built on different technologies and ETL tools which created a tangled, inefficient architecture.

Software Development 157

Software Development Business Intelligence ETL Data Quality 157

TransOrg Analytics

SEPTEMBER 24, 2024

AWS Glue: Fully managed ETL service for easy data preparation and integration. Data & ML/LLM Ops on AWS Amazon SageMaker: Comprehensive ML service to build, train, and deploy models at scale. Amazon Comprehend & Translate: Leverage NLP and translation for LLM (Large Language Models) applications.

ETL 52

ETL LLM Data Ingestion Automation 52

TransOrg Analytics

SEPTEMBER 24, 2024

AWS Glue: Fully managed ETL service for easy data preparation and integration. Data & ML/LLM Ops on AWS Amazon SageMaker: Comprehensive ML service to build, train, and deploy models at scale. Amazon Comprehend & Translate: Leverage NLP and translation for LLM (Large Language Models) applications.

ETL 52

ETL LLM Data Ingestion Automation 52

Flipboard

NOVEMBER 27, 2024

Read triples from the Neptune database and convert them into text format using an LLM hosted on Amazon Bedrock. The following LLM models must be enabled. The following is a SPARQL query that inserts new metadata inferred from existing triples: PREFIX xsd: INSERT { ?asset account } WHERE { ?asset asset "GlueTableAssetType". ?asset

Metadata 149

Metadata Auto-complete Data Discovery ML Engineer 149

Bugra Akyildiz

FEBRUARY 16, 2025

By focusing on applications like AI-generated ad creatives, the framework enables self-interested LLM agents to influence joint outputs through strategic bidding while maintaining computational efficiency and incentive compatibility. a word or phrase) as a decision point where LLM agents bid to influence the next token’s selection.

LLM 52

LLM Python ETL Prompt Engineer 52

AWS Machine Learning Blog

JANUARY 7, 2025

Deterministic LLM-based workflows Parametas solution demanded more than just raw large language model (LLM) capabilitiesit required a structured approach while maintaining operational control. Martin Gregory is a Senior Market Data Technician at Parameta Solutions with over 25 years of experience.

Generative AI 96

Generative AI Automation Data Extraction ETL 96