TechCrunch

NOVEMBER 4, 2022

Called OpenBioML , the endeavor’s first projects will focus on machine learning-based approaches to DNA sequencing, protein folding and computational biochemistry. Stability AI’s ethically questionable decisions to date aside, machine learning in medicine is a minefield. ” Generating DNA sequences.

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AWS Machine Learning - AI

NOVEMBER 14, 2024

Architecture The following figure shows the architecture of the solution. Through natural language processing algorithms and machine learning techniques, the large language model (LLM) analyzes the user’s queries in real time, extracting relevant context and intent to deliver tailored responses.

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AWS Machine Learning - AI

APRIL 23, 2025

National Laboratory has implemented an AI-driven document processing platform that integrates named entity recognition (NER) and large language models (LLMs) on Amazon SageMaker AI. In this post, we discuss how you can build an AI-powered document processing platform with open source NER and LLMs on SageMaker.

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CIO

MAY 19, 2025

The concept derives from a model of concurrent computation in the 1970s. With the advent of artificial intelligence, agents also exhibit additional properties such as basic reasoning, autonomy and collaboration. Foundation models, multi-agent frameworks and observability layers. Orchestration layers. Data services.

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CIO

APRIL 16, 2025

Digital tools are the lifeblood of todays enterprises, but the complexity of hybrid cloud architectures, involving thousands of containers, microservices and applications, frustratesoperational leaders trying to optimize business outcomes. Artificial intelligence has contributed to complexity.

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AWS Machine Learning - AI

MARCH 13, 2025

DeepSeek-R1 , developed by AI startup DeepSeek AI , is an advanced large language model (LLM) distinguished by its innovative, multi-stage training process. Instead of relying solely on traditional pre-training and fine-tuning, DeepSeek-R1 integrates reinforcement learning to achieve more refined outputs.

Artificial Inteligence 104

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AWS Machine Learning - AI

APRIL 16, 2025

Out-of-the-box models often lack the specific knowledge required for certain domains or organizational terminologies. To address this, businesses are turning to custom fine-tuned models, also known as domain-specific large language models (LLMs). The following diagram is the solution architecture.

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AWS Machine Learning - AI

NOVEMBER 27, 2024

Large language models (LLMs) have witnessed an unprecedented surge in popularity, with customers increasingly using publicly available models such as Llama, Stable Diffusion, and Mistral. With activations being partitioned along the sequence dimension, we need to consider how our model’s computations are affected.

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AWS Machine Learning - AI

APRIL 10, 2025

The introduction of Amazon Nova models represent a significant advancement in the field of AI, offering new opportunities for large language model (LLM) optimization. In this post, we demonstrate how to effectively perform model customization and RAG with Amazon Nova models as a baseline.

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AWS Machine Learning - AI

OCTOBER 29, 2024

This engine uses artificial intelligence (AI) and machine learning (ML) services and generative AI on AWS to extract transcripts, produce a summary, and provide a sentiment for the call. He helps support large enterprise customers at AWS and is part of the Machine Learning TFC.

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CIO

OCTOBER 4, 2022

From delightful consumer experiences to attacking fuel costs and carbon emissions in the global supply chain, real-time data and machine learning (ML) work together to power apps that change industries. Data architecture coherence. more machine learning use casesacross the company.

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Infinidat

MAY 22, 2025

(GUEST BLOG) Adriana Andronescu Thu, 05/22/2025 - 09:55 In the dynamic world of AI, businesses often face a critical decision: optimize large language models (LLMs) with fine-tuning or enhance them using Retrieval-Augmented Generation (RAG). Both strategies tailor LLMs to meet specific needs but differ in approach.

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AWS Machine Learning - AI

MARCH 18, 2025

This is where the integration of cutting-edge technologies, such as audio-to-text translation and large language models (LLMs), holds the potential to revolutionize the way patients receive, process, and act on vital medical information. These insights can include: Potential adverse event detection and reporting.

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AWS Machine Learning - AI

APRIL 30, 2025

With advancement in AI technology, the time is right to address such complexities with large language models (LLMs). Amazon Bedrock has helped democratize access to LLMs, which have been challenging to host and manage. The following diagram illustrates the architecture using AWS services.

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AWS Machine Learning - AI

JANUARY 29, 2025

Their DeepSeek-R1 models represent a family of large language models (LLMs) designed to handle a wide range of tasks, from code generation to general reasoning, while maintaining competitive performance and efficiency. The resulting distilled models, such as DeepSeek-R1-Distill-Llama-8B (from base model Llama-3.1-8B

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AWS Machine Learning - AI

OCTOBER 17, 2024

With the advent of generative AI and machine learning, new opportunities for enhancement became available for different industries and processes. It doesn’t retain audio or output text, and users have control over data storage with encryption in transit and at rest. This can lead to more personalized and effective care.

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AWS Machine Learning - AI

MARCH 4, 2025

To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. The solution incorporates the following key features: Using a Retrieval Augmented Generation (RAG) architecture, the system generates a context-aware detailed assessment.

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CIO

MARCH 4, 2025

There are organizations who spend $1 million plus per year on LLM calls, Ricky wrote. Agent ops is a critical capability think Python SDKs for agent monitoring, LLM cost tracking, benchmarking, to gain visibility into API calls, real-time cost management, and reliability scores for agents in production.

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AWS Machine Learning - AI

NOVEMBER 7, 2024

You can also bring your own customized models and deploy them to Amazon Bedrock for supported architectures. Prompt catalog – Crafting effective prompts is important for guiding large language models (LLMs) to generate the desired outputs. It’s serverless so you don’t have to manage the infrastructure.

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AWS Machine Learning - AI

MARCH 18, 2025

This application allows users to ask questions in natural language and then generates a SQL query for the users request. Large language models (LLMs) are trained to generate accurate SQL queries for natural language instructions. However, off-the-shelf LLMs cant be used without some modification.

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AWS Machine Learning - AI

MAY 15, 2025

By automating repetitive tasks, SuperAcc enhances both operational efficiency and accuracy, using Apoideas self-trained machine learning (ML) models to deliver consistent, high-accuracy results in live production environments. The model architecture is illustrated in the following diagram.

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AWS Machine Learning - AI

MARCH 3, 2025

This need for customization has become even more pronounced with the emergence of new models, such as those released by DeepSeek. However, customizing DeepSeek models effectively while managing computational resources remains a significant challenge. You can run these recipes using SageMaker HyperPod or as SageMaker training jobs.

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Perficient

NOVEMBER 20, 2024

Introduction to Multiclass Text Classification with LLMs Multiclass text classification (MTC) is a natural language processing (NLP) task where text is categorized into multiple predefined categories or classes. Traditional approaches rely on training machine learning models, requiring labeled data and iterative fine-tuning.

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AWS Machine Learning - AI

OCTOBER 31, 2024

The solution integrates large language models (LLMs) with your organization’s data and provides an intelligent chat assistant that understands conversation context and provides relevant, interactive responses directly within the Google Chat interface. It can be a local machine or a cloud instance.

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CIO

JANUARY 7, 2025

It prevents vendor lock-in, gives a lever for strong negotiation, enables business flexibility in strategy execution owing to complicated architecture or regional limitations in terms of security and legal compliance if and when they rise and promotes portability from an application architecture perspective.

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AWS Machine Learning - AI

DECEMBER 5, 2023

New and powerful large language models (LLMs) are changing businesses rapidly, improving efficiency and effectiveness for a variety of enterprise use cases. Speed is of the essence, and adoption of LLM technologies can make or break a business’s competitive advantage.

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AWS Machine Learning - AI

JULY 24, 2024

Large language models (LLMs) have achieved remarkable success in various natural language processing (NLP) tasks, but they may not always generalize well to specific domains or tasks. You may need to customize an LLM to adapt to your unique use case, improving its performance on your specific dataset or task.

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CIO

DECEMBER 5, 2024

Consolidating data and improving accessibility through tenanted access controls can typically deliver a 25-30% reduction in data storage expenses while driving more informed decisions. When evaluating options, prioritize platforms that facilitate data democratization through low-code or no-code architectures.

Enterprise 158

Enterprise Data Insurance Business Intelligence 158

TechCrunch

SEPTEMBER 27, 2021

As more enterprises migrate to cloud-based architectures, they are also taking on more applications (because they can) and, as a result of that, more complex workloads and storage needs. Machine learning and other artificial intelligence applications add even more complexity.

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AWS Machine Learning - AI

DECEMBER 24, 2024

Training large language models (LLMs) models has become a significant expense for businesses. For many use cases, companies are looking to use LLM foundation models (FM) with their domain-specific data. architectures/5.sagemaker-hyperpod/LifecycleScripts/base-config/

AWS 106

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AWS Machine Learning - AI

MARCH 20, 2025

Traditionally, transforming raw data into actionable intelligence has demanded significant engineering effort. It often requires managing multiple machine learning (ML) models, designing complex workflows, and integrating diverse data sources into production-ready formats.

Data 118

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CIO

APRIL 9, 2025

CEOs and boards of directors are tasking their CIOs to enable artificial intelligence (AI) within the organization as rapidly as possible. The networking, compute, and storage needs not to mention power and cooling are significant, and market pressures require the assembly to happen quickly.

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AWS Machine Learning - AI

MARCH 11, 2025

DeepSeek-R1 is a large language model (LLM) developed by DeepSeek AI that uses reinforcement learning to enhance reasoning capabilities through a multi-stage training process from a DeepSeek-V3-Base foundation. DeepSeek-R1 uses a Mixture of Experts (MoE) architecture and is 671 billion parameters in size.

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Xebia

FEBRUARY 23, 2025

Data governance is rapidly rising on the priority lists of large companies that want to work with AI in a data-driven manner. In many companies, data is spread across different storage locations and platforms, thus, ensuring effective connections and governance is crucial. Poor data quality automatically results in poor decisions.

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AWS Machine Learning - AI

NOVEMBER 15, 2024

The flexible, scalable nature of AWS services makes it straightforward to continually refine the platform through improvements to the machine learning models and addition of new features. The following diagram illustrates the Principal generative AI chatbot architecture with AWS services.

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CIO

OCTOBER 3, 2024

Rather than pull away from big iron in the AI era, Big Blue is leaning into it, with plans in 2025 to release its next-generation Z mainframe , with a Telum II processor and Spyre AI Accelerator Card, positioned to run large language models (LLMs) and machine learning models for fraud detection and other use cases.

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AWS Machine Learning - AI

MARCH 5, 2025

These assistants can be powered by various backend architectures including Retrieval Augmented Generation (RAG), agentic workflows, fine-tuned large language models (LLMs), or a combination of these techniques. To learn more about FMEval, see Evaluate large language models for quality and responsibility of LLMs.

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