AWS Machine Learning Blog

SEPTEMBER 25, 2024

is the first Llama model to support vision tasks, with a new model architecture that integrates image encoder representations into the language model. models help you build and deploy cutting-edge generative AI models to ignite new innovations like image reasoning and are also more accessible for on-edge applications.

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AWS Machine Learning Blog

MAY 15, 2024

Here, Amazon SageMaker Ground Truth allowed ML engineers to easily build the human-in-the-loop workflow (step v). The workflow allowed the Amazon Ads team to experiment with different foundation models and configurations through blind A/B testing to ensure that feedback to the generated images is unbiased. with minimal effort.

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AWS Machine Learning Blog

AUGUST 22, 2024

Building a deployment pipeline for generative artificial intelligence (AI) applications at scale is a formidable challenge because of the complexities and unique requirements of these systems. Generative AI models are constantly evolving, with new versions and updates released frequently.

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AWS Machine Learning Blog

NOVEMBER 21, 2023

Amazon Music uses the power of AI to accomplish this. However, optimizing the customer experience while managing cost of training and inference of AI models that power the search bar’s capabilities, like real-time spellcheck and vector search, is difficult during peak traffic times.

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AWS Machine Learning Blog

JUNE 25, 2024

Ziwen Ning is a software development engineer at AWS. He currently focuses on enhancing the AI/ML experience through the integration of AWS Neuron with containerized environments and Kubernetes. Rohit Talluri is a Generative AI GTM Specialist (Tech BD) at Amazon Web Services (AWS).

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AWS Machine Learning Blog

OCTOBER 15, 2024

Bria’s commitment to responsible AI and the robust security framework of SageMaker provide enterprises with the full package for data privacy, regulatory compliance, and responsible AI models for commercial use. Explore Bria models in SageMaker JumpStart today and revolutionize your visual content creation process!

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Snorkel AI

MAY 4, 2023

Join us on June 7-8 to learn how to use your data to build your AI moat at The Future of Data-Centric AI 2023. The free virtual conference is the largest annual gathering of the data-centric AI community.

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Snorkel AI

MAY 4, 2023

Join us on June 7-8 to learn how to use your data to build your AI moat at The Future of Data-Centric AI 2023. The free virtual conference is the largest annual gathering of the data-centric AI community.

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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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Viso.ai

MARCH 29, 2024

MLflow is an open-source platform designed to manage the entire machine learning lifecycle, making it easier for ML Engineers, Data Scientists, Software Developers, and everyone involved in the process. Several models fail and many just reach the production stage.

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The MLOps Blog

JULY 18, 2023

Build vs. open-source : which conversational AI model should you choose? Stephen: It seems like a lot of models and sequences. And even on the operation side of things, is there a separate operations team, and then you have your research or ml engineers doing these pipelines and stuff?

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AWS Machine Learning Blog

APRIL 29, 2024

We then show how to set up the infrastructure stack you need to take your own data assets and pre-train or fine-tune a state-of-the-art Llama2 model on Trainium hardware. How Metaflow integrates with Trainium From a Metaflow developer perspective, using Trainium is similar to other accelerators.

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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. Data interactions: Monitor data quality and usage Generative AI models such as LLMs generally work well because they have been trained on a large amount of data.

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AWS Machine Learning Blog

DECEMBER 2, 2024

Today at AWS re:Invent 2024, we are excited to announce the new Container Caching capability in Amazon SageMaker, which significantly reduces the time required to scale generative AI models for inference. In our tests, we’ve seen substantial improvements in scaling times for generative AI model endpoints across various frameworks.

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AWS Machine Learning Blog

JUNE 24, 2024

At the core of Krikey AI’s offering is their powerful foundation model trained to understand human motion and translate text descriptions into realistic 3D character animations. However, building such a sophisticated artificial intelligence (AI) model requires tremendous amounts of high-quality training data.

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AWS Machine Learning Blog

SEPTEMBER 12, 2024

State-of-the-art generative AI models are averaging latencies in the order of seconds, and many of today’s massive models are too large to fit into a single instance. We believe that businesses creating customer or consumer-facing generative AI applications shouldn’t have to sacrifice performance for cost-efficiency.

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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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AWS Machine Learning Blog

DECEMBER 2, 2024

In Part 2 , we provide a detailed, hands-on guide to implementing Fast Model Loader in your LLM deployments. The rapid evolution of LLMs, with some models now using hundreds of billions of parameters, has led to a significant increase in the computational resources and sophisticated infrastructure required to run them effectively.

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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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