AWS Machine Learning Blog

MAY 7, 2024

The Hugging Face containers host a large language model (LLM) from the Hugging Face Hub. The service allows for simple audio data ingestion, easy-to-read transcript creation, and accuracy improvement through custom vocabularies. Amazon Transcribe’s new ASR foundation model supports 100+ language variants.

Automation 131

Automation Auto-complete DevOps UX Design 131

AWS Machine Learning Blog

OCTOBER 23, 2024

SnapLogic , a leader in generative integration and automation, has introduced the industry’s first low-code generative AI development platform, Agent Creator , designed to democratize AI capabilities across all organizational levels. Not anymore! The following demo shows Agent Creator in action.

Generative AI 81

Generative AI IDP LLM Automation 81

Marktechpost

JUNE 16, 2024

This feature automates data layout optimization to enhance query performance and reduce storage costs. Key Features and Benefits: Automated Data Layout Optimization: Predictive Optimization leverages AI to analyze query patterns and determine the best optimizations for data layouts.

Data Ingestion 119

Data Ingestion Python Automation Data Scientist 119

AWS Machine Learning Blog

JUNE 18, 2024

This post presents a solution that uses a generative artificial intelligence (AI) to standardize air quality data from low-cost sensors in Africa, specifically addressing the air quality data integration problem of low-cost sensors. A human-in-the-loop mechanism safeguards data ingestion.

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Generative AI Data Ingestion Python LLM 126

AWS Machine Learning Blog

JANUARY 29, 2025

Large organizations often have many business units with multiple lines of business (LOBs), with a central governing entity, and typically use AWS Organizations with an Amazon Web Services (AWS) multi-account strategy. LLMs may hallucinate, which means a model can provide a confident but factually incorrect response.

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Generative AI AI AI Large Language Models 87

Marktechpost

DECEMBER 3, 2024

In the evolving landscape of artificial intelligence, language models are becoming increasingly integral to a variety of applications, from customer service to real-time data analysis. One key challenge, however, remains: preparing documents for ingestion into large language models (LLMs).

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LLM AI Tools Large Language Models Data Ingestion 103

AWS Machine Learning Blog

OCTOBER 2, 2024

This allows you to create rules that invoke specific actions when certain events occur, enhancing the automation and responsiveness of your observability setup (for more details, see Monitor Amazon Bedrock ). Model evaluation jobs allow you to compare model outputs and choose the best-suited model for your use case.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

An intelligent document processing (IDP) project typically combines optical character recognition (OCR) and natural language processing (NLP) to automatically read and understand documents. Effectively manage your data and its lifecycle Data plays a key role throughout your IDP solution.

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IDP Data Ingestion Automation Natural Language Processing 114

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. Hosted on Amazon ECS with tasks run on Fargate, this platform streamlines the end-to-end ML workflow, from data ingestion to model deployment.

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Machine Learning Data Scientist ML Data Ingestion 119

AWS Machine Learning Blog

NOVEMBER 15, 2023

As a first step, they wanted to transcribe voice calls and analyze those interactions to determine primary call drivers, including issues, topics, sentiment, average handle time (AHT) breakdowns, and develop additional natural language processing (NLP)-based analytics.

Data Ingestion 122

Data Ingestion Metadata NLP Data Scientist 122

AWS Machine Learning Blog

JULY 17, 2024

Amazon Q Business is a fully managed, secure, generative-AI powered enterprise chat assistant that enables natural language interactions with your organization’s data. By default, Amazon Q Business will only produce responses using the data you’re indexing. The deployment steps are fully automated using a shell script.

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IDP Automation Data Ingestion Generative AI 121

AWS Machine Learning Blog

NOVEMBER 26, 2023

Amazon Personalize has helped us achieve high levels of automation in content customization. You follow the same process of data ingestion, training, and creating a batch inference job as in the previous use case. For instance, FOX Sports experienced a 400% increase in viewership content starts post-event when applied.

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Generative AI Metadata Software Engineer AI 126

ODSC - Open Data Science

OCTOBER 7, 2024

One of the key challenges in AI development is building scalable pipelines that can handle the complexities of modern data systems and models. These challenges range from managing large datasets to automating model deployment and monitoring for performance drift.

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Software Engineer Data Ingestion Machine Learning Data Scientist 52

Snorkel AI

DECEMBER 2, 2024

Large language models (LLMs) fine-tuned on proprietary data have become a competitive differentiator for enterprises. When combined with Snorkel Flow, it becomes a powerful enabler for enterprises seeking to harness the full potential of their proprietary data. Sign up here!

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Data Ingestion Large Language Models LLM Machine Learning 52

The MLOps Blog

JUNE 27, 2023

Core features of end-to-end MLOps platforms End-to-end MLOps platforms combine a wide range of essential capabilities and tools, which should include: Data management and preprocessing : Provide capabilities for data ingestion, storage, and preprocessing, allowing you to efficiently manage and prepare data for training and evaluation.

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Machine Learning Metadata Data Scientist Data Quality 134

ODSC - Open Data Science

FEBRUARY 25, 2025

Generative AI TrackBuild the Future with GenAI Generative AI has captured the worlds attention with tools like ChatGPT, DALL-E, and Stable Diffusion revolutionizing how we create content and automate tasks. This track will cover the latest best practices for managing AI models from development to deployment.

Data Scientist 52

Data Scientist Machine Learning Large Language Models ML Engineer 52

Snorkel AI

JANUARY 8, 2025

At Snorkel, weve partnered with Databricks to create a powerful synergy between their data lakehouse and our Snorkel Flow AI data development platform. Ingesting raw data from Databricks into Snorkel Flow Efficient data ingestion is the foundation of any machine learning project. Sign up here!

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AI Developer AI Development Data Ingestion LLM 52

TransOrg Analytics

SEPTEMBER 24, 2024

Our cloud data engineering services are designed to transform your business by creating robust and scalable data foundations across any scale. We provide comprehensive solutions to assess, architect, build, deploy, and automate your data engineering landscape on the leading cloud platforms.

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ETL LLM Data Ingestion Automation 52

TransOrg Analytics

SEPTEMBER 24, 2024

Our cloud data engineering services are designed to transform your business by creating robust and scalable data foundations across any scale. We provide comprehensive solutions to assess, architect, build, deploy, and automate your data engineering landscape on the leading cloud platforms.

ETL 52

ETL LLM Data Ingestion Automation 52

John Snow Labs

FEBRUARY 18, 2025

Combining healthcare-specific LLMs along with a terminology service and scalable data ingestion pipelines, it excels in complex queries and is ideal for organizations seeking OMOP data enrichment.

Generative AI 52

Generative AI Data Ingestion Metadata Automation 52

AWS Machine Learning Blog

AUGUST 21, 2024

Amazon SageMaker Canvas is a no-code machine learning (ML) service that empowers business analysts and domain experts to build, train, and deploy ML models without writing a single line of code. He is focused on AI/ML technology, ML model management, and ML governance to improve overall organizational efficiency and productivity.

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Machine Learning Data Scientist ML Data Quality 119

Pickl AI

AUGUST 28, 2024

Unified ML Workflow: Vertex AI provides a simplified ML workflow, encompassing data ingestion, analysis, transformation, model training, evaluation, and deployment. This unified approach enables seamless collaboration among data scientists, data engineers, and ML engineers.

Machine Learning 52

Machine Learning ML Engineer ML Automation 52

AWS Machine Learning Blog

SEPTEMBER 19, 2024

In today’s rapidly evolving AI landscape, businesses are constantly seeking ways to use advanced large language models (LLMs) for their specific needs. Although foundation models (FMs) offer impressive out-of-the-box capabilities, true competitive advantage often lies in deep model customization through fine-tuning.

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ML Large Language Models Machine Learning Data Ingestion 97

ODSC - Open Data Science

DECEMBER 11, 2024

This evolution underscores the demand for innovative platforms that simplify data ingestion and transformation, enabling faster, more reliable decision-making. Tamer highlighted the potential of large language models in streamlining compliance checks and extracting valuable insights from unstructured data sources, such as SECfilings.

Data Ingestion 52

Data Ingestion Large Language Models Data Scientist Data Science 52

The MLOps Blog

MARCH 12, 2024

TL;DR LLMOps involves managing the entire lifecycle of Large Language Models (LLMs), including data and prompt management, model fine-tuning and evaluation, pipeline orchestration, and LLM deployment. What is Large Language Model Operations (LLMOps)? What the future of LLMOps looks like.

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Prompt Engineering Prompt Engineer Large Language Models LLM 52

The MLOps Blog

FEBRUARY 13, 2025

During my talk at NeurIPS, I broke down five key lessons learned from teams facing large-scale model training and monitoring. Real-time monitoring prevents costly failures Imagine this: you’re training a large language model on thousands of GPUs at a cost of hundreds of thousands of dollars per day.

Data Ingestion 59

Data Ingestion Automation Software Engineer Metadata 59

AWS Machine Learning Blog

SEPTEMBER 11, 2024

In order to train transformer models on internet-scale data, huge quantities of PBAs were needed. In November 2022, ChatGPT was released, a large language model (LLM) that used the transformer architecture, and is widely credited with starting the current generative AI boom. Firstly, to train a FM from scratch.

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ML Deep Learning Algorithm Large Language Models 101

Topbots

FEBRUARY 19, 2024

In the rapidly evolving AI landscape, Large Language Models (LLMs) have emerged as powerful tools, driving innovation across various sectors. From enhancing customer service experiences to providing insightful data analysis, the applications of LLMs are vast and varied.

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LLM Natural Language Processing Data Ingestion Automation 65

The MLOps Blog

MARCH 21, 2023

It should be able to version the project assets of your data scientists, such as the data, the model parameters, and the metadata that comes out of your workflow. Automation is a good MLOps practice for speeding up all parts of that lifecycle. This would let you roll back changes and inspect potentially buggy code.

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69

ODSC - Open Data Science

JULY 11, 2023

Whether that happens with many large language models is largely, but not entirely, up to you. [5] 5] For example, Bing’s new ChatGPT competitor (Bard) has been known to stray into strange conversations, so it’s up to you to keep your conversations with large language models on track.5

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ChatGPT AI AI Chatbots 40

Flipboard

NOVEMBER 26, 2024

Hallucinations in large language models (LLMs) refer to the phenomenon where the LLM generates an output that is plausible but factually incorrect or made-up. Additionally, agents streamline workflows and automate repetitive tasks. With the power of AI automation, you can boost productivity and reduce costs.

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Large Language Models LLM Natural Language Processing Responsible AI 155

AWS Machine Learning Blog

NOVEMBER 20, 2024

In the future, high automation will play a crucial role in this domain. Using generative AI allows businesses to improve accuracy and efficiency in email management and automation. The combination of retrieval augmented generation (RAG) and knowledge bases enhances automated response accuracy.

Automation 111

Automation Data Ingestion Auto-complete Software Engineer 111

Flipboard

NOVEMBER 27, 2024

Solution overview The code in the accompanying GitHub repo provided in this solution enables an automated deployment of Amazon Bedrock Knowledge Bases, Amazon Bedrock Guardrails, and the required resources to integrate the Amazon Bedrock Knowledge Bases API with a Slack slash command assistant using the Bolt for Python library.

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Generative AI Data Ingestion AI AI 143

ODSC - Open Data Science

FEBRUARY 24, 2025

This approach allows AI applications to interpret natural language queries, retrieve relevant data, and generate human-like responses grounded in accurate information. When a user inputs a query, an LLM (large language model) interprets it using Natural Language Understanding (NLU).

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Data Drift Data Ingestion Natural Language Processing LLM 52

AWS Machine Learning Blog

DECEMBER 4, 2024

AWS customers use Amazon Kendra with large language models (LLMs) to quickly create secure, generative AI –powered conversational experiences on top of your enterprise content. Amazon Kendra is an intelligent enterprise search service that helps you search across different content repositories with built-in connectors.

Metadata 101

Metadata Generative AI Data Ingestion Software Engineer 101

AWS Machine Learning Blog

OCTOBER 11, 2024

Generative AI is used in various use cases, such as content creation, personalization, intelligent assistants, questions and answers, summarization, automation, cost-efficiencies, productivity improvement assistants, customization, innovation, and more. The agent returns the LLM response to the chatbot UI or the automated process.

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