2014, AWS and Natural Language Processing

Anthropic Claude 3.5 Sonnet ranks number 1 for business and finance in S&P AI Benchmarks by Kensho

AWS Machine Learning Blog

JULY 9, 2024

Sonnet made key improvements in visual processing and understanding, writing and content generation, natural language processing, coding, and generating insights. Currently he helps customers in the financial service and insurance industry build machine learning solutions on AWS.

AWS

AWS AI AI Machine Learning

Personalize your generative AI applications with Amazon SageMaker Feature Store

AWS Machine Learning Blog

OCTOBER 6, 2023

Large language models (LLMs) are revolutionizing fields like search engines, natural language processing (NLP), healthcare, robotics, and code generation. Next, we recommend “Interstellar” (2014), a thought-provoking and visually stunning film that delves into the mysteries of time and space.

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AI AI Natural Language Processing ML

Top 6 Kubernetes use cases

IBM Journey to AI blog

NOVEMBER 13, 2023

Developed internally at Google and released to the public in 2014, Kubernetes has enabled organizations to move away from traditional IT infrastructure and toward the automation of operational tasks tied to the deployment, scaling and managing of containerized applications (or microservices ).

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Webinars

How to Achieve High-Accuracy Results When Using LLMs

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Top 5 Generative AI Integration Companies to drive Customer Support in 2023

Chatbots Life

MAY 16, 2023

Master of Code Global (MOCG) is a certified partner of Microsoft and AWS and has been recognized by LivePerson, Inc. Deeper Insights Year Founded : 2014 HQ : London, UK Team Size : 11–50 employees Clients : Smith and Nephew, Deloitte, Breast Cancer Now, IAC, Jones Lang-Lasalle, Revival Health. Elite Service Delivery partner of NVIDIA.

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Explain text classification model predictions using Amazon SageMaker Clarify

AWS Machine Learning Blog

JANUARY 25, 2023

Apart from supporting explanations for tabular data, Clarify also supports explainability for both computer vision (CV) and natural language processing (NLP) using the same SHAP algorithm. It is constructed by selecting 14 non-overlapping classes from DBpedia 2014.

Algorithm

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Foundational vision models and visual prompt engineering for autonomous driving applications

AWS Machine Learning Blog

NOVEMBER 15, 2023

As an example downstream application, the fine-tuned model can be used in pre-labeling workflows such as the one described in Auto-labeling module for deep learning-based Advanced Driver Assistance Systems on AWS. Start building the future with AWS today.

Machine Learning

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Must-Have Prompt Engineering Skills for 2024

ODSC - Open Data Science

JANUARY 29, 2024

GANs, introduced in 2014 paved the way for GenAI with models like Pix2pix and DiscoGAN. While AWS is usually the winner when it comes to data science and machine learning, it’s Microsoft Azure that’s taking the lead for prompt engineering job descriptions. NLP skills have long been essential for dealing with textual data.

Data Science

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How to Manage Unstructured Data in AI and Machine Learning Projects

DagsHub

OCTOBER 23, 2024

Large Language Models We engineer LLMs like Gemini and GPT-4 to process and understand unstructured text data. They can generate human-like text, summarize documents, and answer questions, making them essential for natural language processing and text analytics tasks. Our model achieves 28.4 after training for 3.5

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Accelerating large-scale neural network training on CPUs with ThirdAI and AWS Graviton

AWS Machine Learning Blog

FEBRUARY 29, 2024

In this post, we investigate of potential for the AWS Graviton3 processor to accelerate neural network training for ThirdAI’s unique CPU-based deep learning engine. As shown in our results, we observed a significant training speedup with AWS Graviton3 over the comparable Intel and NVIDIA instances on several representative modeling workloads.

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Mitigating risk: AWS backbone network traffic prediction using GraphStorm

Flipboard

JANUARY 15, 2025

The AWS global backbone network is the critical foundation enabling reliable and secure service delivery across AWS Regions. Specifically, we need to predict how changes to one part of the AWS global backbone network might affect traffic patterns and performance across the entire system.

AWS

AWS Machine Learning Machine Learning System Architecture

Luminaries and enterprise veterans to speak at Future of Data-centric AI

Snorkel AI

MAY 24, 2023

He leads corporate strategy for machine learning, natural language processing, information retrieval, and alternative data. He received the 2014 ACM Doctoral Dissertation Award and the 2019 Presidential Early Career Award for Scientists and Engineers for his research on large-scale computing.

Machine Learning

Machine Learning Machine Learning AI AI

Luminaries and enterprise veterans to speak at Future of Data-centric AI

Snorkel AI

MAY 24, 2023

He leads corporate strategy for machine learning, natural language processing, information retrieval, and alternative data. He received the 2014 ACM Doctoral Dissertation Award and the 2019 Presidential Early Career Award for Scientists and Engineers for his research on large-scale computing.

Machine Learning

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Fine-tune Meta Llama 3.2 text generation models for generative AI inference using Amazon SageMaker JumpStart

AWS Machine Learning Blog

NOVEMBER 11, 2024

Prerequisites To try out this solution using SageMaker JumpStart, you’ll need the following prerequisites: An AWS account that will contain all of your AWS resources. An AWS Identity and Access Management (IAM) role to access SageMaker. He is specialized in architecting AI/ML and generative AI services at AWS.

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AI AI ML ML

Perform batch transforms with Amazon SageMaker Jumpstart Text2Text Generation large language models

AWS Machine Learning Blog

MAY 24, 2023

Let’s set up the SageMaker execution role so it has permissions to run AWS services on your behalf: sagemaker_session = Session() aws_role = sagemaker_session.get_caller_identity_arn() aws_region = boto3.Session().region_name Rachna Chadha is a Principal Solutions Architect AI/ML in Strategic Accounts at AWS.

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Anthropic Claude 3.5 Sonnet ranks number 1 for business and finance in S&P AI Benchmarks by Kensho

Personalize your generative AI applications with Amazon SageMaker Feature Store

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Top 6 Kubernetes use cases

Webinars

Top 5 Generative AI Integration Companies to drive Customer Support in 2023

Explain text classification model predictions using Amazon SageMaker Clarify

Foundational vision models and visual prompt engineering for autonomous driving applications

Must-Have Prompt Engineering Skills for 2024

How to Manage Unstructured Data in AI and Machine Learning Projects

Accelerating large-scale neural network training on CPUs with ThirdAI and AWS Graviton

Mitigating risk: AWS backbone network traffic prediction using GraphStorm

Luminaries and enterprise veterans to speak at Future of Data-centric AI

Luminaries and enterprise veterans to speak at Future of Data-centric AI

Fine-tune Meta Llama 3.2 text generation models for generative AI inference using Amazon SageMaker JumpStart

Perform batch transforms with Amazon SageMaker Jumpstart Text2Text Generation large language models

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