AWS Machine Learning Blog

DECEMBER 13, 2023

Machine learning (ML) models do not operate in isolation. To deliver value, they must integrate into existing production systems and infrastructure, which necessitates considering the entire ML lifecycle during design and development. The SageMaker Model Registry centralizes model tracking, simplifying model deployment.

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IBM Journey to AI blog

FEBRUARY 2, 2023

They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights. In today’s world, data warehouses are a critical component of any organization’s technology ecosystem.

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AWS Machine Learning Blog

OCTOBER 30, 2023

Amazon Bedrock is a fully managed service provided by AWS that offers developers access to foundation models (FMs) and the tools to customize them for specific applications. It allows developers to build and scale generative AI applications using FMs through an API, without managing infrastructure.

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Towards AI

SEPTEMBER 28, 2023

Deployment & Serving: Exploring 6 Key MLOps Questions using AWS SageMaker This article is part of the AWS SageMaker series for exploration of ’31 Questions that Shape Fortune 500 ML Strategy’. Collaboration] How can multiple data scientists understand the impact of their version before releasing it? (A/B

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AWS Machine Learning Blog

DECEMBER 19, 2023

Artificial intelligence (AI) and machine learning (ML) are becoming an integral part of systems and processes, enabling decisions in real time, thereby driving top and bottom-line improvements across organizations. However, putting an ML model into production at scale is challenging and requires a set of best practices.

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AWS Machine Learning Blog

JANUARY 5, 2024

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models.

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IBM Journey to AI blog

APRIL 18, 2024

AGI, sometimes referred to as strong AI , is the science-fiction version of artificial intelligence (AI), where artificial machine intelligence achieves human-level learning, perception and cognitive flexibility. Some, like Goertzel and Pennachin , suggest that AGI would possess self-understanding and self-control.

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Google Research AI blog

APRIL 21, 2023

However, developing and iterating on these ML-based multimedia prototypes can be challenging and costly. However, developing and iterating on these ML-based multimedia prototypes can be challenging and costly. Visual Blocks for ML, formerly called Rapsai, provides a no-code graph building experience through its node-graph editor.

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AWS Machine Learning Blog

NOVEMBER 9, 2023

Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is essential for seamlessly bridging the gap between data science experimentation and deployment while meeting the requirements around model performance, security, and compliance.

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The MLOps Blog

MARCH 20, 2023

Long-term ML project involves developing and sustaining applications or systems that leverage machine learning models, algorithms, and techniques. An example of a long-term ML project will be a bank fraud detection system powered by ML models and algorithms for pattern recognition.

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AWS Machine Learning Blog

MARCH 13, 2024

Advancements in artificial intelligence (AI) and machine learning (ML) are revolutionizing the financial industry for use cases such as fraud detection, credit worthiness assessment, and trading strategy optimization. S3 Access Points simplifies the management of access permissions specific to each application accessing a shared dataset.

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AWS Machine Learning Blog

APRIL 11, 2023

Developing web interfaces to interact with a machine learning (ML) model is a tedious task. With Streamlit , developing demo applications for your ML solution is easy. Streamlit is an open-source Python library that makes it easy to create and share web apps for ML and data science. Create Studio using JupyterLab 3.0

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Heartbeat

OCTOBER 5, 2023

Unsurprisingly, Machine Learning (ML) has seen remarkable progress, revolutionizing industries and how we interact with technology. The emergence of Large Language Models (LLMs) like OpenAI's GPT , Meta's Llama , and Google's BERT has ushered in a new era in this field. Their mission?

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Marktechpost

AUGUST 6, 2023

To enable researchers and practitioners to train their models and advance state of the art, Meta has released the source code for its text-to-music generative AI, AudioCraft. MusicGen, AudioGen, and EnCodec are the three models that comprise the AudioCraft framework for development.

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AWS Machine Learning Blog

JANUARY 9, 2024

Foundation models (FMs) are often pre-trained on vast corpora of data with parameters ranging in scale of millions to billions and beyond. Large language models (LLMs) are a type of FM that generate text as a response of the user inference. Llama 2 models are autoregressive models with decoder only architecture.

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The MLOps Blog

MARCH 15, 2023

This includes the tools and techniques we used to streamline the ML model development and deployment processes, as well as the measures taken to monitor and maintain models in a production environment. CI/CD ensures that models are thoroughly tested and validated before they are deployed to a production environment.

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The MLOps Blog

JANUARY 23, 2023

Data versioning control is an important concept in machine learning, as it allows for the tracking and management of changes to data over time. However, data versioning control is frequently given little attention, leading to issues such as data inconsistencies and the inability to reproduce results.

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AWS Machine Learning Blog

FEBRUARY 20, 2024

In this post, we discuss deploying scalable machine learning (ML) models for diarizing media content using Amazon SageMaker , with a focus on the WhisperX model. The WhisperX model, based on OpenAI’s Whisper , performs transcriptions and diarization for media assets.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

Starting from the introduction of the Security Pillar and design principles, we then examine the solution design and implementation with four focus areas: access control, data protection, key and secret management, and workload configuration. This post focuses on the Security pillar of the IDP solution.

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Heartbeat

SEPTEMBER 18, 2023

Unleashing Innovation and Success: Comet — The Trusted ML Platform for Enterprise Environments Machine learning (ML) is a rapidly developing field, and businesses are increasingly depending on ML platforms to fuel innovation, improve efficiency, and mine data for insights.

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AWS Machine Learning Blog

FEBRUARY 16, 2024

Today, we are excited to announce that Code Llama foundation models, developed by Meta, are available for customers through Amazon SageMaker JumpStart to deploy with one click for running inference. In this post, we walk through how to discover and deploy the Code Llama model via SageMaker JumpStart.

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AWS Machine Learning Blog

APRIL 18, 2023

To improve this experience for its members, we at RallyPoint wanted to explore how machine learning (ML) could help. In his own words, “ RallyPoint is an online social and professional network for veterans, service members, family members, caregivers, and other civilian supporters of the US armed forces. It should be an easy process.

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AWS Machine Learning Blog

FEBRUARY 7, 2023

Amazon SageMaker has announced the support of three new completion criteria for Amazon SageMaker automatic model tuning , providing you with an additional set of levers to control the stopping criteria of the tuning job when finding the best hyperparameter configuration for your model. Let’s explore each of these criteria.

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AWS Machine Learning Blog

MAY 23, 2023

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

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AWS Machine Learning Blog

FEBRUARY 29, 2024

Amazon Bedrock provides a broad range of models from Amazon and third-party providers, including Anthropic, AI21, Meta, Cohere, and Stability AI, and covers a wide range of use cases, including text and image generation, embedding, chat, high-level agents with reasoning and orchestration, and more.

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AWS Machine Learning Blog

AUGUST 1, 2023

Advertising agencies can use generative AI and text-to-image foundation models to create innovative ad creatives and content. In this post, we demonstrate how you can generate new images from existing base images using Amazon SageMaker , a fully managed service to build, train, and deploy ML models for at scale.

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Google Research AI blog

MARCH 2, 2023

This allows the training of models on locally available signals without exposing raw data to servers, increasing user privacy. Since that launch, we have worked to improve the privacy guarantees of this technology by carefully combining secure aggregation (SecAgg) and a distributed version of differential privacy.

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AWS Machine Learning Blog

MAY 10, 2023

This smart mattress topper works like a thermostat for your bed and gives customers control of their sleep climate. In this post, we share how Sleepme used Amazon SageMaker to developed a machine learning (ML) model proof of concept that recommends temperatures to maximize your sleep score.

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AWS Machine Learning Blog

SEPTEMBER 1, 2023

Nowadays, the majority of our customers is excited about large language models (LLMs) and thinking how generative AI could transform their business. However, bringing such solutions and models to the business-as-usual operations is not an easy task. Our approach applies to both open-source and proprietary models equally.

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AWS Machine Learning Blog

MAY 19, 2023

Through the use of multiple AI/ML services, “Describe For Me” generates a caption of an input image and will read it back in a clear, natural-sounding voice in a variety of languages and dialects. In this blog post we walk you through the Solution Architecture behind “Describe For Me”, and the design considerations of our solution.

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TheSequence

MARCH 11, 2024

To successfully build an AI application, evaluating the performance of large language models (LLMs) is crucial. This post is a shortened version of Peter’s original blog, titled 'Evaluating LLM Applications '. Given the inherent novelty and complexities surrounding LLMs, this poses a unique challenge for most companies.

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AWS Machine Learning Blog

NOVEMBER 6, 2023

Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from scanned documents. Adapters are components that plug in to the Amazon Textract pre-trained deep learning model, customizing its output based on your annotated documents.

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AWS Machine Learning Blog

APRIL 19, 2023

In this post, the Sportradar team discusses the challenges they encountered and the solutions they created to build their model inference platform using the DJL. Since 2018, our team has been developing a variety of ML models to enable betting products for NFL and NCAA football. We recently developed four more new models.

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Heartbeat

AUGUST 10, 2023

Photo by Milad Fakurian on Unsplash Introduction With advanced models like Generative Pre-trained Transformer 3 (GPT-3), which provides human-like responses to user queries, AI is progressing toward generative tools to create realistic content, including text, videos, images, and audio. Learn more from Uber’s Olcay Cirit.

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AWS Machine Learning Blog

MARCH 23, 2023

Leidos has partnered with AWS to develop an approach to privacy-preserving, confidential machine learning (ML) modeling where you build cloud-enabled, encrypted pipelines. In this post, we show how to activate privacy-preserving ML predictions for the most highly regulated environments.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

Amazon Personalize allows you to add sophisticated personalization capabilities to your applications by using the same machine learning (ML) technology used on Amazon.com for over 20 years. No ML expertise is required. After the model is trained, you can generate real-time personalized recommendations for your users.

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Heartbeat

JUNE 5, 2023

However, managing machine learning projects can be challenging, especially as the size and complexity of the data and models increase. Without proper tracking, optimization, and collaboration tools, ML practitioners can quickly become overwhelmed and lose track of their progress. This is where Comet comes in. Hugging Face ?

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