ODSC - Open Data Science

JANUARY 10, 2024

The AI Paradigm Shift: Under the Hood of a Large Language Models Valentina Alto | Azure Specialist — Data and Artificial Intelligence | Microsoft Develop an understanding of Generative AI and Large Language Models, including the architecture behind them, their functioning, and how to leverage their unique conversational capabilities.

Large Language Models 52

Large Language Models LLM Deep Learning Data Science 52

AWS Machine Learning Blog

OCTOBER 16, 2024

Amazon SageMaker supports geospatial machine learning (ML) capabilities, allowing data scientists and ML engineers to build, train, and deploy ML models using geospatial data. His current area of research includes LLM evaluation and data generation. About the Author Xiong Zhou is a Senior Applied Scientist at AWS.

Machine Learning 103

Machine Learning ML Data Scientist Robotics 103

The MLOps Blog

JUNE 27, 2023

Collaborative workflows : Dataset storage and versioning tools should support collaborative workflows, allowing multiple users to access and contribute to datasets simultaneously, ensuring efficient collaboration among ML engineers, data scientists, and other stakeholders.

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Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

DECEMBER 9, 2024

MLflow , a popular open-source tool, helps data scientists organize, track, and analyze ML and generative AI experiments, making it easier to reproduce and compare results. Amazon SageMaker with MLflow is a capability in SageMaker that enables users to create, manage, analyze, and compare their ML experiments seamlessly.

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ML Data Scientist Machine Learning Software Engineer 74

AWS Machine Learning Blog

NOVEMBER 29, 2023

However, harnessing this potential while ensuring the responsible and effective use of these models hinges on the critical process of LLM evaluation. An evaluation is a task used to measure the quality and responsibility of output of an LLM or generative AI service. Who needs to perform LLM evaluation?

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LLM Data Scientist Algorithm Generative AI 102

AWS Machine Learning Blog

JANUARY 26, 2024

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. Understanding and addressing LLM vulnerabilities, threats, and risks during the design and architecture phases helps teams focus on maximizing the economic and productivity benefits generative AI can bring.

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Generative AI LLM ML AI 135

AWS Machine Learning Blog

DECEMBER 2, 2024

For LLMs that often require high throughput and low-latency inference requests, this loading process can add significant overhead to the total deployment and scaling time, potentially impacting application performance during traffic spikes. During our performance testing we were able to load the llama-3.1-70B 70B model on an ml.p4d.24xlarge

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Large Language Models Auto-complete Machine Learning LLM 100

AWS Machine Learning Blog

NOVEMBER 18, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

LLM 95

LLM Generative AI Data Science Data Scientist 95

AWS Machine Learning Blog

DECEMBER 17, 2024

Amazon SageMaker helps data scientists and machine learning (ML) engineers build FMs from scratch, evaluate and customize FMs with advanced techniques, and deploy FMs with fine-grain controls for generative AI use cases that have stringent requirements on accuracy, latency, and cost. Of the six challenges, the LLM met only one.

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LLM Prompt Engineering Prompt Engineer Generative AI 86

AWS Machine Learning Blog

OCTOBER 11, 2024

This post dives deep into Amazon Bedrock Knowledge Bases , which helps with the storage and retrieval of data in vector databases for RAG-based workflows, with the objective to improve large language model (LLM) responses for inference involving an organization’s datasets. The LLM response is passed back to the agent.

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Metadata Generative AI LLM Data Ingestion 96