AWS Machine Learning Blog

APRIL 4, 2025

They use real-time data and machine learning (ML) to offer customized loans that fuel sustainable growth and solve the challenges of accessing capital. These classified transactions then serve as critical inputs for downstream credit risk AI models, enabling more accurate assessments of a businesss creditworthiness.

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insideBIGDATA

MARCH 4, 2024

Hammerspace, the company orchestrating the Next Data Cycle, unveiled the high-performance NAS architecture needed to address the requirements of broad-based enterprise AI, machine learning and deep learning (AI/ML/DL) initiatives and the widespread rise of GPU computing both on-premises and in the cloud.

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AWS Machine Learning Blog

NOVEMBER 26, 2024

Solution overview The steps to implement the solution are as follows: Create the EKS cluster. Create the EKS cluster If you don’t have an existing EKS cluster, you can create one using eksctl. Adjust the following configuration to suit your needs, such as the Amazon EKS version, cluster name, and AWS Region.

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AWS Machine Learning Blog

DECEMBER 24, 2024

To reduce costs while continuing to use the power of AI , many companies have shifted to fine tuning LLMs on their domain-specific data using Parameter-Efficient Fine Tuning (PEFT). Manually managing such complexity can often be counter-productive and take away valuable resources from your businesses AI development.

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Smart Data Collective

AUGUST 29, 2022

This is why businesses are looking to leverage machine learning (ML). In this article, we will share some best practices for improving your analytics with ML. Top ML approaches to improve your analytics. Clustering. ?lustering They need a more comprehensive analytics strategy to achieve these business goals.

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Dataconomy

MARCH 3, 2025

Thanks to machine learning (ML) and artificial intelligence (AI), it is possible to predict cellular responses and extract meaningful insights without the need for exhaustive laboratory experiments. They introduce PERTURBQA , a benchmark designed to align AI-driven perturbation models with real biological decision-making.

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DataRobot Blog

DECEMBER 6, 2022

Other organizations are just discovering how to apply AI to accelerate experimentation time frames and find the best models to produce results. With a goal to help data science teams learn about the application of AI and ML, DataRobot shares helpful, educational blogs based on work with the world’s most strategic companies.

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Flipboard

DECEMBER 3, 2024

Syngenta and AWS collaborated to develop Cropwise AI , an innovative solution powered by Amazon Bedrock Agents , to accelerate their sales reps’ ability to place Syngenta seed products with growers across North America. Generative AI is reshaping businesses and unlocking new opportunities across various industries.

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AWS Machine Learning Blog

MARCH 3, 2025

Increasingly, organizations across industries are turning to generative AI foundation models (FMs) to enhance their applications. The launcher interfaces with underlying cluster management systems such as SageMaker HyperPod (Slurm or Kubernetes) or training jobs, which handle resource allocation and scheduling. recipes=recipe-name.

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Towards AI

SEPTEMBER 3, 2024

Last Updated on September 3, 2024 by Editorial Team Author(s): Surya Maddula Originally published on Towards AI. Let’s discuss two popular ML algorithms, KNNs and K-Means. We will discuss KNNs, also known as K-Nearest Neighbours and K-Means Clustering. They are both ML Algorithms, and we’ll explore them more in detail in a bit.

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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.

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Hacker News

OCTOBER 15, 2024

At the Open Compute Project (OCP) Global Summit 2024, we’re showcasing our latest open AI hardware designs with the OCP community. These innovations include a new AI platform, cutting-edge open rack designs, and advanced network fabrics and components. Prior to Llama, our largest AI jobs ran on 128 NVIDIA A100 GPUs.

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AWS Machine Learning Blog

NOVEMBER 14, 2024

We recently announced the general availability of cross-account sharing of Amazon SageMaker Model Registry using AWS Resource Access Manager (AWS RAM) , making it easier to securely share and discover machine learning (ML) models across your AWS accounts. Human oversight : Including human involvement in AI decision-making processes.

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AWS Machine Learning Blog

JULY 25, 2024

By accelerating the speed of issue detection and remediation, it increases the reliability of your ML training and reduces the wasted time and cost due to hardware failure. Choose Clusters in the navigation pane, open the trainium-inferentia cluster, choose Node groups, and locate your node group. # install.sh

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AWS Machine Learning Blog

JANUARY 30, 2025

The use of unsupervised learning methods on semi-structured data along with generative AI has been transformative in unlocking hidden insights. Amazon Bedrock is a fully managed service that provides access to high-performing foundation models (FMs) from leading AI startups and Amazon through a unified API.

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AWS Machine Learning Blog

APRIL 4, 2023

AWS provides various services catered to time series data that are low code/no code, which both machine learning (ML) and non-ML practitioners can use for building ML solutions. We use the Time Series Clustering using TSFresh + KMeans notebook, which is available on our GitHub repo.

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Flipboard

JANUARY 24, 2025

Overview of vector search and the OpenSearch Vector Engine Vector search is a technique that improves search quality by enabling similarity matching on content that has been encoded by machine learning (ML) models into vectors (numerical encodings). These benchmarks arent designed for evaluating ML models.

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Hacker News

JUNE 12, 2024

Meta is currently operating many data centers with GPU training clusters across the world. A year ago, however, as the industry reached a critical inflection point due to the rise of artificial intelligence (AI), we recognized that to lead in the generative AI space we’d need to transform our fleet.

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Dataconomy

MAY 22, 2023

TensorFlow provides high-level APIs, such as tf.distribute, to distribute training across multiple devices, machines, or clusters. PyTorch: PyTorch , developed by Facebook’s AI Research lab, is another popular distributed learning framework.

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AWS Machine Learning Blog

APRIL 22, 2024

Amazon SageMaker HyperPod is purpose-built to accelerate foundation model (FM) training, removing the undifferentiated heavy lifting involved in managing and optimizing a large training compute cluster. In this solution, HyperPod cluster instances use the LDAPS protocol to connect to the AWS Managed Microsoft AD via an NLB.

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AWS Machine Learning Blog

NOVEMBER 27, 2024

You can use these techniques together to train complex models that are orders of magnitude faster and rapidly iterate and deploy innovative AI solutions that drive business value. After they’re initiated, SageMaker training jobs spin up the cluster, provisioning the specified number and type of compute instances.

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Towards AI

FEBRUARY 21, 2024

Author(s): Alessandro Amenta Originally published on Towards AI. Image generated with DALL-E 3 In the fast-paced world of Machine Learning (ML) research, keeping up with the latest findings is crucial and exciting, but let’s be honest — it’s also a challenge. What’s the next big thing in ML?

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AWS Machine Learning Blog

JUNE 25, 2024

This solution simplifies the integration of advanced monitoring tools such as Prometheus and Grafana, enabling you to set up and manage your machine learning (ML) workflows with AWS AI Chips. By deploying the Neuron Monitor DaemonSet across EKS nodes, developers can collect and analyze performance metrics from ML workload pods.

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Hacker News

AUGUST 5, 2024

AI networks play an important role in interconnecting tens of thousands of GPUs together, forming the foundational infrastructure for training, enabling large models with hundreds of billions of parameters such as LLAMA 3.1 The growing prevalence of AI has introduced a new era of communication demands.

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Hacker News

MARCH 12, 2024

Marking a major investment in Meta’s AI future, we are announcing two 24k GPU clusters. We are sharing details on the hardware, network, storage, design, performance, and software that help us extract high throughput and reliability for various AI workloads. We use this cluster design for Llama 3 training.

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AWS Machine Learning Blog

FEBRUARY 12, 2024

Sharing in-house resources with other internal teams, the Ranking team machine learning (ML) scientists often encountered long wait times to access resources for model training and experimentation – challenging their ability to rapidly experiment and innovate. If it shows online improvement, it can be deployed to all the users.

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Hacker News

OCTOBER 15, 2024

At Open Compute Project Summit (OCP) 2024, we’re sharing details about our next-generation network fabric for our AI training clusters. Now, through OCP, we’re bringing new open advanced network technologies to our data centers, and the wider industry, for advanced AI applications.

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Flipboard

AUGUST 17, 2023

Many practitioners are extending these Redshift datasets at scale for machine learning (ML) using Amazon SageMaker , a fully managed ML service, with requirements to develop features offline in a code way or low-code/no-code way, store featured data from Amazon Redshift, and make this happen at scale in a production environment.

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Data Science Dojo

FEBRUARY 20, 2023

Machine learning (ML) is the technology that automates tasks and provides insights. It comes in many forms, with a range of tools and platforms designed to make working with ML more efficient. It provides a large cluster of clusters on a single machine. It is also useful for training models on smaller datasets.

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Smart Data Collective

NOVEMBER 1, 2020

Machines, artificial intelligence (AI), and unsupervised learning are reshaping the way businesses vie for a place under the sun. Unsupervised ML: The Basics. Unlike supervised ML, we do not manage the unsupervised model. Unsupervised ML uses algorithms that draw conclusions on unlabeled datasets.

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Towards AI

JULY 17, 2023

Last Updated on July 18, 2023 by Editorial Team Author(s): Muttineni Sai Rohith Originally published on Towards AI. Pyspark MLlib | Classification using Pyspark ML In the previous sections, we discussed about RDD, Dataframes, and Pyspark concepts. In this article, we will discuss about Pyspark MLlib and Spark ML.

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Hacker News

JANUARY 25, 2024

He writes about ML/AI/crypto/data, leadership, and building tech teams. Adam Drake is an advisor to scale-up tech companies.

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Data Science Dojo

JULY 17, 2023

In recent years, there has been a growing interest in the use of artificial intelligence (AI) for data analysis. AI tools can automate many of the tasks involved in data analysis, and they can also help businesses to discover new insights from their data. Top 10 AI tools for data analysis AI Tools for Data Analysis 1.

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Flipboard

APRIL 13, 2023

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of scalable compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are transforming their businesses.

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AWS Machine Learning Blog

AUGUST 15, 2024

With over 50 connectors, an intuitive Chat for data prep interface, and petabyte support, SageMaker Canvas provides a scalable, low-code/no-code (LCNC) ML solution for handling real-world, enterprise use cases. Afterward, you need to manage complex clusters to process and train your ML models over these large-scale datasets.

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AWS Machine Learning Blog

APRIL 19, 2024

Iambic Therapeutics is a drug discovery startup with a mission to create innovative AI-driven technologies to bring better medicines to cancer patients, faster. Our advanced generative and predictive artificial intelligence (AI) tools enable us to search the vast space of possible drug molecules faster and more effectively.

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AWS Machine Learning Blog

FEBRUARY 26, 2025

These experiences are made possible by our machine learning (ML) backend engine, with ML models built for video understanding, search, recommendation, advertising, and novel visual effects. By using sophisticated ML algorithms, the platform efficiently scans billions of videos each day.

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