AWS Machine Learning Blog

OCTOBER 14, 2024

The following system architecture represents the logic flow when a user uploads an image, asks a question, and receives a text response grounded by the text dataset stored in OpenSearch. This script can be acquired directly from Amazon S3 using aws s3 cp s3://aws-blogs-artifacts-public/artifacts/ML-16363/deploy.sh.

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Snorkel AI

MAY 3, 2023

In this article, we share our journey and hope that it helps you design better machine learning systems. Table of contents Why we needed to redesign our interactive ML system In this section, we’ll go over the market forces and technological shifts that compelled us to re-architect our ML system.

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AWS Machine Learning Blog

MAY 23, 2023

With organizations increasingly investing in machine learning (ML), ML adoption has become an integral part of business transformation strategies. However, implementing ML into production comes with various considerations, notably being able to navigate the world of AI safely, strategically, and responsibly.

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AWS Machine Learning Blog

FEBRUARY 24, 2023

AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers for these types of use cases. For more information, refer to Preview: Use Amazon SageMaker to Build, Train, and Deploy ML Models Using Geospatial Data.

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O'Reilly Media

NOVEMBER 19, 2024

What’s old becomes new again: Substitute the term “notebook” with “blackboard” and “graph-based agent” with “control shell” to return to the blackboard system architectures for AI from the 1970s–1980s. See the Hearsay-II project , BB1 , and lots of papers by Barbara Hayes-Roth and colleagues. Does GraphRAG improve results?

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AWS Machine Learning Blog

NOVEMBER 17, 2023

Amazon Rekognition Content Moderation , a capability of Amazon Rekognition , automates and streamlines image and video moderation workflows without requiring machine learning (ML) experience. This process involves the utilization of both ML and non-ML algorithms. In this section, we briefly introduce the system architecture.

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Towards AI

MARCH 1, 2023

The technology behind GitHub’s new code search This post provides a high-level explanation of the inner workings of GitHub’s new code search and offers a glimpse into the system architecture and technical underpinnings of the product.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

The compute clusters used in these scenarios are composed of more than thousands of AI accelerators such as GPUs or AWS Trainium and AWS Inferentia , custom machine learning (ML) chips designed by Amazon Web Services (AWS) to accelerate deep learning workloads in the cloud. Because you use p4de.24xlarge You can then take the easy-ssh.sh

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AWS Machine Learning Blog

MARCH 10, 2025

Solution overview The following figure illustrates our system architecture for CreditAI on AWS, with two key paths: the document ingestion and content extraction workflow, and the Q&A workflow for live user query response. He specializes in generative AI, machine learning, and system design.

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AWS Machine Learning Blog

SEPTEMBER 6, 2024

Understanding the intrinsic value of data network effects, Vidmob constructed a product and operational system architecture designed to be the industry’s most comprehensive RLHF solution for marketing creatives. Use case overview Vidmob aims to revolutionize its analytics landscape with generative AI.

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AWS Machine Learning Blog

JANUARY 30, 2023

Amazon Forecast is a fully managed service that uses machine learning (ML) to generate highly accurate forecasts, without requiring any prior ML experience. With Forecast, there are no servers to provision or ML models to build manually. Delete the S3 bucket.

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Snorkel AI

MAY 3, 2023

In this article, we share our journey and hope that it helps you design better machine learning systems. Table of contents Why we needed to redesign our interactive ML system In this section, we’ll go over the market forces and technological shifts that compelled us to re-architect our ML system.

Machine Learning 52

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Snorkel AI

MAY 3, 2023

In this article, we share our journey and hope that it helps you design better machine learning systems. Table of contents Why we needed to redesign our interactive ML system In this section, we’ll go over the market forces and technological shifts that compelled us to re-architect our ML system.

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Google Research AI blog

FEBRUARY 14, 2023

Further improvements are gained by utilizing a novel structured dynamical systems architecture and combining RL with trajectory optimization , supported by novel solvers. We improved the efficiency of RL approaches by incorporating prior information, including predictive information , adversarial motion priors , and guide policies.

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AWS Machine Learning Blog

NOVEMBER 24, 2023

The system architecture comprises several core components: UI portal – This is the user interface (UI) designed for vendors to upload product images. As an ML enthusiast, Dhaval is driven by his passion for creating impactful solutions that bring positive change.

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Heartbeat

JANUARY 9, 2024

" The LLMOps Steps LLMs, sophisticated artificial intelligence (AI) systems trained on enormous text and code datasets, have changed the game in various fields, from natural language processing to content generation. Deployment : The adapted LLM is integrated into this stage's planned application or system architecture.

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Flipboard

DECEMBER 6, 2023

He is a multi patent inventor with three granted patents and his experience spans multiple technology domains including telecom, networking, application integration, AI/ML, and cloud deployments. She leads machine learning (ML) projects in various domains such as computer vision, natural language processing and generative AI.

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The MLOps Blog

APRIL 17, 2023

As an MLOps engineer on your team, you are often tasked with improving the workflow of your data scientists by adding capabilities to your ML platform or by building standalone tools for them to use. Giving your data scientists a platform to track the progress of their ML projects. Experiment tracking is one such capability.

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IBM Journey to AI blog

JULY 18, 2024

Computing Computing is being dominated by major revolutions in artificial intelligence (AI) and machine learning (ML). The algorithms that empower AI and ML require large volumes of training data, in addition to strong and steady amounts of processing power. Distributed computing supplies both.

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Pickl AI

DECEMBER 10, 2024

The systems architecture combines Oracles hardware expertise with software optimisation to deliver unmatched performance. Evolving Use Cases Engineered systems are expanding their applications beyond traditional database and middleware optimisation. Core Features Exalytics is engineered for speed and scalability.

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AWS Machine Learning Blog

AUGUST 15, 2023

The decision handler determines the moderation action and provides reasons for its decision based on the ML models’ output, thereby deciding whether the image required a further review by a human moderator or could be automatically approved or rejected.

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AWS Machine Learning Blog

APRIL 10, 2025

This means users can build resilient clusters for machine learning (ML) workloads and develop or fine-tune state-of-the-art frontier models, as demonstrated by organizations such as Luma Labs and Perplexity AI. Frontier model builders can further enhance model performance using built-in ML tools within SageMaker HyperPod.

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Flipboard

JANUARY 15, 2025

System architecture for GNN-based network traffic prediction In this section, we propose a system architecture for enhancing operational safety within a complex network, such as the ones we discussed earlier. To learn how to use GraphStorm to solve a broader class of ML problems on graphs, see the GitHub repo.

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AWS Machine Learning Blog

APRIL 2, 2025

Ray promotes the same coding patterns for both a simple machine learning (ML) experiment and a scalable, resilient production application. Overview of Ray This section provides a high-level overview of the Ray tools and frameworks for AI/ML workloads. We primarily focus on ML training use cases.

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AWS Machine Learning Blog

APRIL 14, 2025

The key features of LangGraph Studio are: Visual agent graphs The IDEs visualization tools allow developers to represent agent flows as intuitive graphic wheels, making it straightforward to understand and modify complex system architectures. Rupinder Grewal is a Senior AI/ML Specialist Solutions Architect with AWS.

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AWS Machine Learning Blog

NOVEMBER 12, 2024

There are various technologies that help operationalize and optimize the process of field trials, including data management and analytics, IoT, remote sensing, robotics, machine learning (ML), and now generative AI. The transformed data acts as the input to AI/ML services. AWS Lambda is then used to further enrich the data.

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AWS Machine Learning Blog

MARCH 5, 2025

It requires checking many systems and teams, many of which might be failing, because theyre interdependent. Developers need to reason about the system architecture, form hypotheses, and follow the chain of components until they have located the one that is the culprit.

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ODSC - Open Data Science

MARCH 31, 2025

Building Multimodal AI Agents: Agentic RAG with Vision-Language Models Suman Debnath, Principal AI/ML Advocate at Amazon WebServices Learn how to create AI agents that integrate both vision and language using retrieval-augmented generation (RAG).

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AWS Machine Learning Blog

JANUARY 28, 2025

In this section, we explore how different system components and architectural decisions impact overall application responsiveness. System architecture and end-to-end latency considerations In production environments, overall system latency extends far beyond model inference time.

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AWS Machine Learning Blog

MARCH 13, 2025

Agent broker methodology Following an agent broker pattern, the system is still fundamentally event-driven, with actions triggered by the arrival of messages. New agents can be added to handle specific types of messages without changing the overall system architecture.

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AWS Machine Learning Blog

FEBRUARY 19, 2025

Rather than using probabilistic approaches such as traditional machine learning (ML), Automated Reasoning tools rely on mathematical logic to definitively verify compliance with policies and provide certainty (under given assumptions) about what a system will or wont do. However, its important to understand its limitations.

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