Dataconomy

MARCH 13, 2023

How to create an artificial intelligence? The creation of artificial intelligence (AI) has long been a dream of scientists, engineers, and innovators. With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless.

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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. In this post, we seek to separate a time series dataset into individual clusters that exhibit a higher degree of similarity between its data points and reduce noise.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

We believe generative AI has the potential over time to transform virtually every customer experience we know. Innovative startups like Perplexity AI are going all in on AWS for generative AI. And at the top layer, we’ve been investing in game-changing applications in key areas like generative AI-based coding.

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AWS Machine Learning Blog

MAY 23, 2023

Just recently, generative AI applications have captured everyone’s attention and imagination. We are truly at an exciting inflection point in the widespread adoption of ML, and we believe every customer experience and application will be reinvented with generative AI.

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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

NOVEMBER 30, 2023

Building foundation models (FMs) requires building, maintaining, and optimizing large clusters to train models with tens to hundreds of billions of parameters on vast amounts of data. Customers such as Stability AI use SageMaker HyperPod to train their foundation models, including Stable Diffusion. “As

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AWS Machine Learning Blog

OCTOBER 5, 2023

In this post, we walk through how to fine-tune Llama 2 on AWS Trainium , a purpose-built accelerator for LLM training, to reduce training times and costs. We review the fine-tuning scripts provided by the AWS Neuron SDK (using NeMo Megatron-LM), the various configurations we used, and the throughput results we saw.

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AWS Machine Learning Blog

DECEMBER 12, 2023

In this post, we’ll summarize training procedure of GPT NeoX on AWS Trainium , a purpose-built machine learning (ML) accelerator optimized for deep learning training. M tokens/$) trained such models with AWS Trainium without losing any model quality. We’ll outline how we cost-effectively (3.2 billion in Pythia. billion in Pythia.

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IBM Journey to AI blog

AUGUST 30, 2023

IBM Maximo Application Suite (MAS), the next generation of IBM Maximo, delivers a better user experience, faster integration, robust AI analytics and a broad range of cloud deployment options. Why ROSA for Maximo in AWS? Red Hat OpenShift Service on AWS is jointly developed and jointly supported by AWS and Red Hat.

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IBM Journey to AI blog

JANUARY 16, 2024

Businesses are increasingly embracing data-intensive workloads, including high-performance computing, artificial intelligence (AI) and machine learning (ML). To aid in building more sustainable IT estates, IBM has partnered up with Amazon Web Services (AWS) to facilitate sustainable cloud modernization journeys.

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Data Science Dojo

FEBRUARY 20, 2023

It is used by businesses across industries for a wide range of applications, including fraud prevention, marketing automation, customer service, artificial intelligence (AI), chatbots, virtual assistants, and recommendations. It provides a large cluster of clusters on a single machine.

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AWS Machine Learning Blog

JANUARY 17, 2024

Today, we’re excited to announce the availability of Llama 2 inference and fine-tuning support on AWS Trainium and AWS Inferentia instances in Amazon SageMaker JumpStart. In this post, we demonstrate how to deploy and fine-tune Llama 2 on Trainium and AWS Inferentia instances in SageMaker JumpStart.

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Mlearning.ai

APRIL 16, 2023

Harnessing the Power of fine tuned Foundation Models for adding Generative AI capabilities to your application The field of artificial intelligence (AI) has been making waves across various industries, and customers are rushing to incorporate Generative AI capabilities in their application.

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Smart Data Collective

FEBRUARY 20, 2022

AWS (Amazon Web Services), the comprehensive and evolving cloud computing platform provided by Amazon, is comprised of infrastructure as a service (IaaS), platform as a service (PaaS) and packaged software as a service (SaaS). With its wide array of tools and convenience, AWS has already become a popular choice for many SaaS companies.

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AWS Machine Learning Blog

AUGUST 21, 2023

Data is frequently kept in data lakes that can be managed by AWS Lake Formation , giving you the ability to implement fine-grained access control using a straightforward grant or revoke procedure. You can use the provided AWS CloudFormation stack to set up the architectural components for this solution.

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Data Science Dojo

DECEMBER 31, 2023

The year 2023 proved to be a game-changer in the progress of generative AI. We saw companies like Microsoft, Apple, Google, and more fueling this AI race. Moreover, there was also a rise in the number of startups creating generative AI tools and building on to the technology around it. What followed was unexpected.

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Flipboard

NOVEMBER 17, 2023

Generative AI models have the potential to revolutionize enterprise operations, but businesses must carefully consider how to harness their power while overcoming challenges such as safeguarding data and ensuring the quality of AI-generated content. This type of data is often used in ML and artificial intelligence applications.

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AWS Machine Learning Blog

APRIL 24, 2024

Conversational artificial intelligence (AI) assistants are engineered to provide precise, real-time responses through intelligent routing of queries to the most suitable AI functions. What is an AI assistant?

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AWS Machine Learning Blog

MARCH 15, 2023

Tens of thousands of AWS customers use AWS machine learning (ML) services to accelerate their ML development with fully managed infrastructure and tools. The data scientist is responsible for moving the code into SageMaker, either manually or by cloning it from a code repository such as AWS CodeCommit.

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AWS Machine Learning Blog

MAY 23, 2024

By distributing experts across workers, expert parallelism addresses the high memory requirements of loading all experts on a single device and enables MoE training on a larger cluster. The following figure offers a simplified look at how expert parallelism works on a multi-GPU cluster.

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Flipboard

FEBRUARY 16, 2023

Modern model pre-training often calls for larger cluster deployment to reduce time and cost. In October 2022, we launched Amazon EC2 Trn1 Instances , powered by AWS Trainium , which is the second generation machine learning accelerator designed by AWS. The following diagram shows an example.

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AWS Machine Learning Blog

APRIL 19, 2024

We are excited to announce a new version of the Amazon SageMaker Operators for Kubernetes using the AWS Controllers for Kubernetes (ACK). ACK is a framework for building Kubernetes custom controllers, where each controller communicates with an AWS service API. They are also supported by AWS CloudFormation. Release v1.2.9

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AWS Machine Learning Blog

NOVEMBER 16, 2023

This is a joint blog with AWS and Philips. Since 2014, the company has been offering customers its Philips HealthSuite Platform, which orchestrates dozens of AWS services that healthcare and life sciences companies use to improve patient care.

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ODSC - Open Data Science

APRIL 24, 2023

Botnet Detection at Scale — Lessons Learned From Clustering Billions of Web Attacks Into Botnets Editor’s note: Ori Nakar is a speaker for ODSC Europe this June. Be sure to check out his talk, “ Botnet detection at scale — Lesson learned from clustering billions of web attacks into botnets ,” there!

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AWS Machine Learning Blog

MARCH 30, 2023

Metadata of the match is processed within the AWS Lambda function MetaDataIngestion , while positional data is ingested using the AWS Fargate container called MatchLink. Additionally, the ball recovery times are sent to a specific topic in the MSK cluster, where they can be accessed by other Bundesliga Match Facts.

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AWS Machine Learning Blog

SEPTEMBER 14, 2023

Today, generative AI models cover a variety of tasks from text summarization, Q&A, and image and video generation. Fine-tuning allows you to adjust these generative AI models to achieve improved performance on your domain-specific tasks. For details, refer to Creating an AWS account. image and a ml.t3.medium

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AWS Machine Learning Blog

JANUARY 17, 2024

We then discuss the various use cases and explore how you can use AWS services to clean the data, how machine learning (ML) can aid in this effort, and how you can make ethical use of the data in generating visuals and insights. For more information, refer to Common techniques to detect PHI and PII data using AWS Services.

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AWS Machine Learning Blog

APRIL 19, 2024

We used AWS services including Amazon Bedrock , Amazon SageMaker , and Amazon OpenSearch Serverless in this solution. In this series, we use the slide deck Train and deploy Stable Diffusion using AWS Trainium & AWS Inferentia from the AWS Summit in Toronto, June 2023 to demonstrate the solution.

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AWS Machine Learning Blog

APRIL 5, 2024

SageMaker Processing enables the flexible scaling of compute clusters to accommodate tasks of varying sizes, from processing a single city block to managing planetary-scale workloads. Now, with the specialized geospatial container in SageMaker, managing and running clusters for geospatial processing has become more straightforward.

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AWS Machine Learning Blog

APRIL 16, 2024

IAM role – SageMaker requires an AWS Identity and Access Management (IAM) role to be assigned to a SageMaker Studio domain or user profile to manage permissions effectively. To learn more about SageMaker Studio JupyterLab Spaces, refer to Boost productivity on Amazon SageMaker Studio: Introducing JupyterLab Spaces and generative AI tools.

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AWS Machine Learning Blog

DECEMBER 18, 2023

Make sure you have the following prerequisites: Create an S3 bucket Configure MongoDB Atlas cluster Create a free MongoDB Atlas cluster by following the instructions in Create a Cluster. In his role Igor is working with strategic partners helping them build complex, AWS-optimized architectures. Note we have two folders.

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Flipboard

DECEMBER 6, 2023

Click here to open the AWS console and follow along. The model then uses a clustering algorithm to group the sentences into clusters. The sentences that are closest to the center of each cluster are selected to form the summary. To use one of these models, AWS offers the fully managed service Amazon Bedrock.

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AWS Machine Learning Blog

APRIL 18, 2024

It’s straightforward to deploy in your AWS account. Prerequisites You need to have an AWS account and an AWS Identity and Access Management (IAM) role and user with permissions to create and manage the necessary resources and components for this application. Everything you need is provided as open source in our GitHub repo.

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Flipboard

NOVEMBER 24, 2023

Many customers are building generative AI apps on Amazon Bedrock and Amazon CodeWhisperer to create code artifacts based on natural language. In this post, we show you how SnapLogic , an AWS customer, used Amazon Bedrock to power their SnapGPT product through automated creation of these complex DSL artifacts from human language.

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AWS Machine Learning Blog

JULY 6, 2023

A number of AWS independent software vendor (ISV) partners have already built integrations for users of their software as a service (SaaS) platforms to utilize SageMaker and its various features, including training, deployment, and the model registry. In some cases, an ISV may deploy their software in the customer AWS account.

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AWS Machine Learning Blog

DECEMBER 15, 2023

We are excited to announce the launch of Amazon DocumentDB (with MongoDB compatibility) integration with Amazon SageMaker Canvas , allowing Amazon DocumentDB customers to build and use generative AI and machine learning (ML) solutions without writing code. Analyze data using generative AI. Prepare data for machine learning.

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AWS Machine Learning Blog

MAY 7, 2024

Veritone is an artificial intelligence (AI) company based in Irvine, California. Founded in 2014, Veritone empowers people with AI-powered software and solutions for various applications, including media processing, analytics, advertising, and more.

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