Dataconomy

FEBRUARY 19, 2025

Traditional attention mechanismsthe core of how AI processes and remembers informationstruggle to scale efficiently, making models costly to train and run. Now, researchers from DeepSeek-AI and Peking University have introduced a game-changing approach called Natively Sparse Attention (NSA).

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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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AWS Machine Learning Blog

NOVEMBER 19, 2024

This year, generative AI and machine learning (ML) will again be in focus, with exciting keynote announcements and a variety of sessions showcasing insights from AWS experts, customer stories, and hands-on experiences with AWS services. Fifth, we’ll showcase various generative AI use cases across industries.

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AWS Machine Learning Blog

DECEMBER 4, 2024

Businesses are under pressure to show return on investment (ROI) from AI use cases, whether predictive machine learning (ML) or generative AI. Only 54% of ML prototypes make it to production, and only 5% of generative AI use cases make it to production. This post is cowritten with Isaac Cameron and Alex Gnibus from Tecton.

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ODSC - Open Data Science

JUNE 6, 2025

On June 12, 2025 at NVIDIA GTC Paris, learn more about cuML and clustering algorithms during the hands-on workshop, Accelerate Clustering Algorithms to Achieve the Highest Performance. It dramatically improves algorithm performance for data-intensive tasks involving tens to hundreds of millions of records.

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Flipboard

DECEMBER 6, 2023

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. Implementation includes the following steps: The first step is to break down the large document, such as a book, into smaller sections, or chunks.

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AWS Machine Learning Blog

DECEMBER 26, 2024

The report The economic potential of generative AI: The next productivity frontier , published by McKinsey & Company, estimates that generative AI could add an equivalent of $2.6 The potential for such large business value is galvanizing tens of thousands of enterprises to build their generative AI applications in AWS.

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AWS Machine Learning Blog

SEPTEMBER 8, 2023

For modern companies that deal with enormous volumes of documents such as contracts, invoices, resumes, and reports, efficiently processing and retrieving pertinent data is critical to maintaining a competitive edge. What if there was a way to process documents intelligently and make them searchable in with high accuracy?

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AWS Machine Learning Blog

MAY 13, 2025

Recognizing the transformative benefits of generative AI for enterprises, we at Hexagons Asset Lifecycle Intelligence division sought to enhance how users interact with our Enterprise Asset Management (EAM) products. This phase focused on establishing a secure and compliant foundation to enable the responsible adoption of generative AI.

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AWS Machine Learning Blog

AUGUST 9, 2024

Question and answering (Q&A) using documents is a commonly used application in various use cases like customer support chatbots, legal research assistants, and healthcare advisors. In this collaboration, the AWS GenAIIC team created a RAG-based solution for Deltek to enable Q&A on single and multiple government solicitation documents.

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AWS Machine Learning Blog

OCTOBER 23, 2024

The landscape of enterprise application development is undergoing a seismic shift with the advent of generative AI. This intuitive platform enables the rapid development of AI-powered solutions such as conversational interfaces, document summarization tools, and content generation apps through a drag-and-drop interface.

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AWS Machine Learning Blog

APRIL 2, 2025

At its core, Ray offers a unified programming model that allows developers to seamlessly scale their applications from a single machine to a distributed cluster. Combining the resiliency of SageMaker HyperPod and the efficiency of Ray provides a powerful framework to scale up your generative AI workloads.

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AWS Machine Learning Blog

SEPTEMBER 3, 2024

From deriving insights to powering generative artificial intelligence (AI) -driven applications, the ability to efficiently process and analyze large datasets is a vital capability. This same interface is also used for provisioning EMR clusters. The following diagram illustrates this solution.

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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

JULY 25, 2024

Solution overview The solution is based on the node problem detector and recovery DaemonSet, a powerful tool designed to automatically detect and report various node-level problems in a Kubernetes cluster. Choose Clusters in the navigation pane, open the trainium-inferentia cluster, choose Node groups, and locate your node group. #

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Flipboard

FEBRUARY 10, 2025

AI agents are rapidly becoming the next frontier in enterprise transformation, with 82% of organizations planning adoption within the next 3 years. According to a Capgemini survey of 1,100 executives at large enterprises, 10% of organizations already use AI agents, and more than half plan to use them in the next year.

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AWS Machine Learning Blog

APRIL 7, 2025

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies and AWS. For example, imagine a consulting firm that manages documentation for multiple healthcare providerseach customers sensitive patient records and operational documents must remain strictly separated.

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AWS Machine Learning Blog

JUNE 30, 2025

These diagrams serve as essential communication tools for stakeholders, documentation of compliance requirements, and blueprints for implementation teams. By using generative AI through natural language prompts, architects can now generate professional diagrams in minutes rather than hours, while adhering to AWS best practices.

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AWS Machine Learning Blog

MARCH 10, 2025

The traditional approach of manually sifting through countless research documents, industry reports, and financial statements is not only time-consuming but can also lead to missed opportunities and incomplete analysis. It became apparent that a cost-effective solution for our generative AI needs was required.

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AWS Machine Learning Blog

NOVEMBER 20, 2024

Whether it’s structured data in databases or unstructured content in document repositories, enterprises often struggle to efficiently query and use this wealth of information. Solution overview Amazon Q Business is a fully managed, generative AI-powered assistant that helps enterprises unlock the value of their data and knowledge.

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AWS Machine Learning Blog

NOVEMBER 22, 2024

Companies across various scales and industries are using large language models (LLMs) to develop generative AI applications that provide innovative experiences for customers and employees. By offloading the management and maintenance of the training cluster to SageMaker, we reduce both training time and our total cost of ownership (TCO).

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Dataconomy

JUNE 10, 2025

In a recent, deeply personal and inspiring address, Ruth Porat, President and Chief Investment Officer of Alphabet and Google, shared a powerful vision of how AI is set to revolutionize cancer research, detection, and treatment. Here, too, AI is making a dramatic impact. So, how is this partnership working in practice?

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Flipboard

NOVEMBER 27, 2024

Customers want to search through all of the data and applications across their organization, and they want to see the provenance information for all of the documents retrieved. For more details about RDF data format, refer to the W3C documentation. The following is an example of RDF triples in N-triples file format: "sales_qty_sold".

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Dataconomy

MARCH 26, 2025

Just two days ago, Chinese AI startup DeepSeek quietly dropped a bombshell on Hugging Face: a 685-billion-parameter large language model called DeepSeek-V3-0324. Just a massive set of model weights, an MIT license, and a few technical whispers that were enough to set the AI community ablaze. No splashy press briefings.

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ODSC - Open Data Science

FEBRUARY 23, 2023

5 Must-Know Pillars of a Data Science and AI Foundation A data science and AI foundation needs to be built up properly before diving in head-first. By knowing these core skills, like math and AI literacy, you’ll start off your career on a high note. Tesla’s Automated Driving Documents Have Been Requested by The U.S.

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AWS Machine Learning Blog

NOVEMBER 1, 2023

Organizations can search for PII using methods such as keyword searches, pattern matching, data loss prevention tools, machine learning (ML), metadata analysis, data classification software, optical character recognition (OCR), document fingerprinting, and encryption. This speeds up the PII detection process and also reduces the overall cost.

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AWS Machine Learning Blog

MARCH 20, 2025

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

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AWS Machine Learning Blog

APRIL 18, 2025

Retrieval Augmented Generation (RAG) enhances AI responses by combining the generative AI models capabilities with information from external data sources, rather than relying solely on the models built-in knowledge. Based on the quality and quantity of the data, the time to complete this process varied.

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Data Science Dojo

MARCH 13, 2024

You need the right tools to fully unleash the power of generative AI. A vector embedding model is one such tool that is a critical component of AI applications for creating realistic text, images, and more. The use case and outcomes of your generative AI application guide your choice of model. What are vector embedding models?

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Flipboard

JUNE 4, 2025

Climate tech startups are at the forefront of building impactful solutions to the climate crisis, and theyre using generative AI to build as quickly as possible. Trends among climate tech startups building with generative AI Climate tech startups adoption of generative AI is evolving rapidly.

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AWS Machine Learning Blog

MAY 1, 2024

This post presents a solution for developing a chatbot capable of answering queries from both documentation and databases, with straightforward deployment. For documentation retrieval, Retrieval Augmented Generation (RAG) stands out as a key tool. Virginia) AWS Region. The following diagram illustrates the solution architecture.

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AWS Machine Learning Blog

JULY 7, 2025

Software as a service (SaaS) companies managing multiple tenants face a critical challenge: efficiently extracting meaningful insights from vast document collections while controlling costs.

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IBM Journey to AI blog

SEPTEMBER 5, 2023

In the second blog of the series, we’re discussing best practices for upgrading your clusters to newer versions. You are responsible for applying these updates to the cluster master and worker nodes. Patch updates are automatically applied to cluster masters, but you are responsible for updating your cluster’s worker nodes.

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Towards AI

FEBRUARY 5, 2025

Last Updated on February 5, 2025 by Editorial Team Author(s): Michael Ryaboy Originally published on Towards AI. This article breaks down what Late Chunking is, why its essential for embedding larger or more intricate documents, and how to build it into your search pipeline using Chonkie and KDB.AI as the vector store.

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Towards AI

JANUARY 29, 2025

Author(s): Dwaipayan Bandyopadhyay Originally published on Towards AI. Source : Image by Author In todays AI World, where large amounts of structured and unstructured data are generated daily, accurately using knowledge has become the cornerstone of modern-day technology. What is MongoDB Atlas?

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phData

JANUARY 30, 2024

Snowpark ML is transforming the way that organizations implement AI solutions. Vector embeddings are a popular technique for working with unstructured data for Generative AI use cases. Document Vectors With the success of word embeddings , it’s understood that entire documents can be represented in a similar way.

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AWS Machine Learning Blog

OCTOBER 23, 2024

For instance, when developing a medical search engine, obtaining a large dataset of real user queries and relevant documents is often infeasible due to privacy concerns surrounding personal health information. These PDFs will serve as the source for generating document chunks.

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