AWS Machine Learning Blog

MAY 15, 2024

ONNX is an open source machine learning (ML) framework that provides interoperability across a wide range of frameworks, operating systems, and hardware platforms. ONNX Runtime is the runtime engine used for model inference and training with ONNX. Then we compared the improvements from bfloat16 fast math kernels from ONNX Runtime 1.17.1

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AWS Machine Learning Blog

FEBRUARY 27, 2024

In this post, we share how Axfood, a large Swedish food retailer, improved operations and scalability of their existing artificial intelligence (AI) and machine learning (ML) operations by prototyping in close collaboration with AWS experts and using Amazon SageMaker. This is a guest post written by Axfood AB.

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IBM Journey to AI blog

FEBRUARY 5, 2024

Every asset manager, regardless of the organization’s size, faces similar mandates: streamline maintenance planning, enhance asset or equipment reliability and optimize workflows to improve quality and productivity. These foundation models, built on large language models, are trained on vast amounts of unstructured and external data.

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AWS Machine Learning Blog

DECEMBER 19, 2023

Artificial intelligence (AI) and machine learning (ML) are becoming an integral part of systems and processes, enabling decisions in real time, thereby driving top and bottom-line improvements across organizations. However, putting an ML model into production at scale is challenging and requires a set of best practices.

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AWS Machine Learning Blog

OCTOBER 5, 2023

Artificial intelligence (AI) and machine learning (ML) have seen widespread adoption across enterprise and government organizations. Processing unstructured data has become easier with the advancements in natural language processing (NLP) and user-friendly AI/ML services like Amazon Textract , Amazon Transcribe , and Amazon Comprehend.

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AWS Machine Learning Blog

APRIL 29, 2024

In recent years, large language models (LLMs) have gained attention for their effectiveness, leading various industries to adapt general LLMs to their data for improved results, making efficient training and hardware availability crucial. This is a guest post by Mark McQuade, Malikeh Ehghaghi, and Shamane Siri from Arcee.

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AWS Machine Learning Blog

APRIL 18, 2024

We are excited to announce that Slack, a Salesforce company, has collaborated with Amazon SageMaker JumpStart to power Slack AI’s initial search and summarization features and provide safeguards for Slack to use large language models (LLMs) more securely. None of your data is used to train the underlying models.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

Amazon SageMaker makes it straightforward to deploy machine learning (ML) models for real-time inference and offers a broad selection of ML instances spanning CPUs and accelerators such as AWS Inferentia. The endpoint uniformly distributes incoming requests to ML instances using a round-robin algorithm.

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Heartbeat

JUNE 12, 2023

Source: Author Introduction Machine learning model monitoring tracks the performance and behavior of a machine learning model over time. It involves collecting and analyzing data on various aspects of the model’s performance, including its accuracy, precision, recall, and F1 score, as well as its bias , fairness , and stability.

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AWS Machine Learning Blog

FEBRUARY 13, 2024

In this post, we discuss how BigBasket used Amazon SageMaker to train their computer vision model for Fast-Moving Consumer Goods (FMCG) product identification, which helped them reduce training time by approximately 50% and save costs by 20%. To keep pace with new products, a new model was produced each month using the latest training data.

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AWS Machine Learning Blog

DECEMBER 12, 2023

Vodafone is transitioning from a telecommunications company (telco) to a technology company (TechCo) by 2025, with objectives of innovating faster, reducing costs, improving security, and simplifying operations. In this post, we share how Vodafone is advancing its ML skills using AWS DeepRacer and Accenture. Why AWS DeepRacer?

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Google Research AI blog

APRIL 21, 2023

However, developing and iterating on these ML-based multimedia prototypes can be challenging and costly. However, developing and iterating on these ML-based multimedia prototypes can be challenging and costly. Visual Blocks for ML, formerly called Rapsai, provides a no-code graph building experience through its node-graph editor.

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AWS Machine Learning Blog

OCTOBER 26, 2023

Intuitivo, a pioneer in retail innovation, is revolutionizing shopping with its cloud-based AI and machine learning (AI/ML) transactional processing system. Our innovative new A-POPs (or vending machines) deliver enhanced customer experiences at ten times lower cost because of the performance and cost advantages AWS Inferentia delivers.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

The IDP Well-Architected Custom Lens follows the AWS Well-Architected Framework, reviewing the solution with six pillars with the granularity of a specific AI or machine learning (ML) use case, and providing the guidance to tackle common challenges. This post focuses on the Performance Efficiency pillar of the IDP workload.

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AWS Machine Learning Blog

MARCH 3, 2023

Machine learning (ML) can help companies make better business decisions through advanced analytics. Companies across industries apply ML to use cases such as predicting customer churn, demand forecasting, credit scoring, predicting late shipments, and improving manufacturing quality. MB to 100 MB in size.

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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. All the principles of the AWS Shared Responsibility Model are applicable to generative AI solutions.

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AWS Machine Learning Blog

APRIL 3, 2024

Search engines and recommendation systems powered by generative AI can improve the product search experience exponentially by understanding natural language queries and returning more accurate results. A multimodal embeddings model is designed to learn joint representations of different modalities like text, images, and audio.

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IBM Journey to AI blog

APRIL 9, 2024

Now, whether they’re lining the fairways or watching from home, fans can more fully appreciate the performance of the world’s best golfers at the sport’s most prestigious tournament. In a continuous design thinking process, teams from IBM Consulting and the club collaborate to improve the fan experience year after year.

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AWS Machine Learning Blog

DECEMBER 1, 2023

Launched in 2019, Amazon SageMaker Studio provides one place for all end-to-end machine learning (ML) workflows, from data preparation, building and experimentation, training, hosting, and monitoring. As a web application, SageMaker Studio has improved load time, faster IDE and kernel start up times, and automatic upgrades.

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Google Research AI blog

MARCH 30, 2023

Posted by Peter Mattson, Senior Staff Engineer, ML Performance, and Praveen Paritosh, Senior Research Scientist, Google Research, Brain Team Machine learning (ML) offers tremendous potential, from diagnosing cancer to engineering safe self-driving cars to amplifying human productivity. Each step can introduce issues and biases.

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AWS Machine Learning Blog

MAY 2, 2024

Amazon Personalize makes it straightforward to personalize your website, app, emails, and more, using the same machine learning (ML) technology used by Amazon, without requiring ML expertise. Benefits of new recipes The new recipes offer enhancements in scalability, latency, model performance, and functionality.

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AWS Machine Learning Blog

NOVEMBER 16, 2023

This is a joint blog with AWS and Philips. Philips is a health technology company focused on improving people’s lives through meaningful innovation. Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle.

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AWS Machine Learning Blog

FEBRUARY 6, 2024

To support overarching pharmacovigilance activities, our pharmaceutical customers want to use the power of machine learning (ML) to automate the adverse event detection from various data sources, such as social media feeds, phone calls, emails, and handwritten notes, and trigger appropriate actions.

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AWS Machine Learning Blog

NOVEMBER 29, 2023

Data preparation is a crucial step in any machine learning (ML) workflow, yet it often involves tedious and time-consuming tasks. With this integration, SageMaker Canvas provides customers with an end-to-end no-code workspace to prepare data, build and use ML and foundations models to accelerate time from data to business insights.

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Towards AI

FEBRUARY 20, 2024

Beginner’s Guide to ML-001: Introducing the Wonderful World of Machine Learning: An Introduction Everyone is using mobile or web applications which are based on one or other machine learning algorithms. Machine learning(ML) is evolving at a very fast pace. Similarly, you give a Machine learning model many pictures, videos, Sounds, etc.,

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AWS Machine Learning Blog

APRIL 24, 2024

In this post, we share how we analyzed the feedback data and identified limitations of accuracy and hallucinations RAG provided, and used the human evaluation score to train the model through reinforcement learning. This method addressed the RAG limitation and further improved the bot response quality. pdf – page: 10 * ARS GEN 10.0/05.01.02.

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AWS Machine Learning Blog

APRIL 16, 2024

Customers are building generative AI applications using large language models (LLMs) and other foundation models (FMs), which enhance customer experiences, transform operations, improve employee productivity, and create new revenue channels.

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Heartbeat

FEBRUARY 1, 2023

Machine learning has become an essential part of our lives because we interact with various applications of ML models, whether consciously or unconsciously. Machine Learning Operations (MLOps) are the aspects of ML that deal with the creation and advancement of these models. What is MLOps?

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Defined.ai blog

JANUARY 12, 2023

Machine learning (ML) can be used in manufacturing in a variety of ways to optimize production processes and improve product quality. Common applications include: Predictive maintenance: ML models can be trained to analyze sensor data from equipment to predict fault timelines and when maintenance will be needed.

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AWS Machine Learning Blog

FEBRUARY 21, 2023

We’re thrilled to announce an expanded collaboration between AWS and Hugging Face to accelerate the training, fine-tuning, and deployment of large language and vision models used to create generative AI applications. The benefits are: faster training and scaling low-latency and high-throughput inference. Or they can self-manage on Amazon EC2.

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AWS Machine Learning Blog

MAY 16, 2024

To enhance the shopping experience of LotteON’s customers, the recommendation service development team is continuously improving the recommendation service to provide customers with the products they are looking for or may be interested in at the right time. The EMR preprocessing batch runs through Airflow according to the specified schedule.

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Snorkel AI

OCTOBER 23, 2023

Wayfair relies on machine learning (ML) and product tagging to ensure customer searches result in relevant products. With Snorkel Flow, Wayfair built a data-centric AI development workflow to help improve automated catalog tagging across their products. To ensure that relevant products appear in customer searches (e.g.

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AWS Machine Learning Blog

OCTOBER 19, 2023

By using Amazon Rekognition for image and video moderation, human moderators have to review a much smaller set of content, typically 1–5% of the total volume, already flagged by the content moderation model. These adapters extend the capabilities of the moderation model to detect images used for training with higher accuracy.

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AWS Machine Learning Blog

MAY 10, 2023

Amazon SageMaker provides a broad selection of machine learning (ML) infrastructure and model deployment options to help meet your ML inference needs. New generations of CPUs offer a significant performance improvement in ML inference due to specialized built-in instructions. 4xlarge instances. 4xlarge.

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Iguazio

AUGUST 14, 2023

As ML models become increasingly complex and integral to critical decision-making processes, ensuring their optimal performance and reliability has become a paramount concern for technology leaders. What is Model Monitoring? What is Observability in ML?

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Iguazio

JULY 31, 2023

MLOps accelerates the ML model deployment process to make it more efficient and scalable. Looking to improve your MLOps knowledge and processes? In this blog post, we detail the steps you need to take to build and run a successful MLOps pipeline. An extension of DevOps, MLOps streamlines and monitors ML workflows.

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Heartbeat

MARCH 14, 2024

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionary technologies with the potential to transform the field of engineering. The synergy between engineering and AI/ML creates unprecedented opportunities for efficiency, cost reduction, and innovation. Indium Software Why AI and ML in Engineering?

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