AWS Machine Learning Blog

MAY 15, 2024

Acting as a model hub, JumpStart provided a large selection of foundation models and the team quickly ran their benchmarks on candidate models. After selecting candidate large language models (LLMs), the science teams can proceed with the remaining steps by adding more customization.

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AWS Machine Learning Blog

JANUARY 10, 2024

Specialist Data Engineering at Merck, and Prabakaran Mathaiyan, Sr. ML Engineer at Tiger Analytics. The large machine learning (ML) model development lifecycle requires a scalable model release process similar to that of software development.

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AWS Machine Learning Blog

APRIL 29, 2024

Historically, natural language processing (NLP) would be a primary research and development expense. In 2024, however, organizations are using large language models (LLMs), which require relatively little focus on NLP, shifting research and development from modeling to the infrastructure needed to support LLM workflows.

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AWS Machine Learning Blog

FEBRUARY 11, 2025

Conclusion In this post, we explored how SageMaker JumpStart empowers data scientists and ML engineers to discover, access, and deploy a wide range of pre-trained FMs for inference, including Metas most advanced and capable models to date. models today. On the endpoint details page, choose Delete.

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AWS Machine Learning Blog

AUGUST 22, 2024

The solution in this post shows how you can take Python code that was written to preprocess, fine-tune, and test a large language model (LLM) using Amazon Bedrock APIs and convert it into a SageMaker pipeline to improve ML operational efficiency. Building a robust MLOps pipeline demands cross-functional collaboration.

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AWS Machine Learning Blog

AUGUST 1, 2024

This is the first in a series of posts about model customization scenarios that can be imported into Amazon Bedrock to simplify the process of building scalable and secure generative AI applications. Using the Amazon Bedrock Text Playground You can test the model using the Amazon Bedrock Text Playground.

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AWS Machine Learning Blog

JULY 23, 2024

collection of multilingual large language models (LLMs), which includes pre-trained and instruction tuned generative AI models in 8B, 70B, and 405B sizes, is available through Amazon SageMaker JumpStart to deploy for inference. models are available today in SageMaker JumpStart initially in the US East (N.

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Snorkel AI

MAY 4, 2023

In the era of large language models (LLMs), your data is the difference maker. Large Language Models (LLMs) such as GPT-4 and LLaMA have revolutionized natural language processing and understanding, enabling a wide range of applications, from conversational AI to advanced text generation.

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Snorkel AI

MAY 4, 2023

In the era of large language models (LLMs), your data is the difference maker. Large Language Models (LLMs) such as GPT-4 and LLaMA have revolutionized natural language processing and understanding, enabling a wide range of applications, from conversational AI to advanced text generation.

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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.

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AWS Machine Learning Blog

DECEMBER 13, 2023

ML operations, known as MLOps, focus on streamlining, automating, and monitoring ML models throughout their lifecycle. Data scientists, ML engineers, IT staff, and DevOps teams must work together to operationalize models from research to deployment and maintenance.

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AWS Machine Learning Blog

JUNE 8, 2023

However, businesses can meet this challenge while providing personalized and efficient customer service with the advancements in generative artificial intelligence (generative AI) powered by large language models (LLMs). Ryan Gomes is a Data & ML Engineer with the AWS Professional Services Intelligence Practice.

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AWS Machine Learning Blog

NOVEMBER 21, 2023

Optimizing training with NVIDIA Tensor Core GPUs Gaining access to an NVIDIA Tensor Core GPU for large language model training is not enough to capture its true potential. Prior to working at Amazon Music, Siddharth was working at companies like Meta, Walmart Labs, Rakuten on E-Commerce centric ML Problems.

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ODSC - Open Data Science

FEBRUARY 21, 2025

AI Agents AI Software Engineering Agents: What Works and WhatDoesnt Robert Brennan | CEO | All HandsAI AI is reshaping software development, but are autonomous coding agents like Devin and OpenHands a game-changer or just hype? Discover what they will be presenting at ODSC Eastbelow.

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The MLOps Blog

MARCH 21, 2023

From gathering and processing data to building models through experiments, deploying the best ones, and managing them at scale for continuous value in production—it’s a lot. As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale.

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The MLOps Blog

JULY 18, 2023

I think another huge component, as I kind of was mentioning earlier, is Conversational AI tends to require large pipelines of machine learning. You usually cannot do a one-shot, “here’s a model,” then it handles everything no matter what you’re reading today. And so we actually need to have a full pipeline of models.

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AWS Machine Learning Blog

JANUARY 26, 2024

Generative artificial intelligence (AI) applications built around large language models (LLMs) have demonstrated the potential to create and accelerate economic value for businesses. Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications.

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AWS Machine Learning Blog

DECEMBER 2, 2024

The generative AI landscape has been rapidly evolving, with large language models (LLMs) at the forefront of this transformation. These models have grown exponentially in size and complexity, with some now containing hundreds of billions of parameters and requiring hundreds of gigabytes of memory.

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AWS Machine Learning Blog

DECEMBER 4, 2024

Available in SageMaker AI and SageMaker Unified Studio (preview) Data scientists and ML engineers can access these applications from Amazon SageMaker AI (formerly known as Amazon SageMaker) and from SageMaker Unified Studio. Zuoyuan Huang is a Software Development Manager at AWS. You can find him on LinkedIn.

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Marktechpost

APRIL 10, 2025

Bio: Hamza Tahir is a software developer turned ML engineer. Based on his learnings from deploying ML in production for predictive maintenance use-cases in his previous startup, he co-created ZenML , an open-source MLOps framework for creating production grade ML pipelines on any infrastructure stack.

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