IBM Journey to AI blog

MAY 15, 2024

Business leaders risk compromising their competitive edge if they do not proactively implement generative AI (gen AI). However, businesses scaling AI face entry barriers. This situation will exacerbate data silos, increase costs and complicate the governance of AI and data workloads.

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AWS Machine Learning Blog

FEBRUARY 1, 2024

Resilience plays a pivotal role in the development of any workload, and generative AI workloads are no different. There are unique considerations when engineering generative AI workloads through a resilience lens. In this post, we discuss the different stacks of a generative AI workload and what those considerations should be.

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Flipboard

NOVEMBER 24, 2023

To pave the way for the growth of AI, BMW Group needed to make a leap regarding scalability and elasticity while reducing operational overhead, software licensing, and hardware management. These platforms were too limited regarding CPU, GPU, and memory to allow the scalability of AI at BMW Group.

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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. AWS SageMaker also has a CLI for model creation and management.

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AWS Machine Learning Blog

MARCH 1, 2023

In this post, we share how Kakao Games and the Amazon Machine Learning Solutions Lab teamed up to build a scalable and reliable LTV prediction solution by using AWS data and ML services such as AWS Glue and Amazon SageMaker. The ETL pipeline, MLOps pipeline, and ML inference should be rebuilt in a different AWS account.

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AWS Machine Learning Blog

JUNE 18, 2024

On December 6 th -8 th 2023, the non-profit organization, Tech to the Rescue , in collaboration with AWS, organized the world’s largest Air Quality Hackathon – aimed at tackling one of the world’s most pressing health and environmental challenges, air pollution. As always, AWS welcomes your feedback.

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Pickl AI

DECEMBER 26, 2024

AI, serverless computing, and edge technologies redefine cloud-based Data Science workflows. Major Cloud Platforms for Data Science Amazon Web Services ( AWS ), Microsoft Azure, and Google Cloud Platform (GCP) dominate the cloud market with their comprehensive offerings. Below are key strategies for achieving this.

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AWS Machine Learning Blog

FEBRUARY 23, 2023

For more information about distributed training with SageMaker, refer to the AWS re:Invent 2020 video Fast training and near-linear scaling with DataParallel in Amazon SageMaker and The science behind Amazon SageMaker’s distributed-training engines. In a later post, we will do a deep dive into the DNNs used by ADAS systems.

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AWS Machine Learning Blog

MARCH 14, 2024

Generative artificial intelligence (generative AI) has enabled new possibilities for building intelligent systems. Recent improvements in Generative AI based large language models (LLMs) have enabled their use in a variety of applications surrounding information retrieval. In the following figure we demonstrate our end-to-end pipeline.

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Precisely

APRIL 11, 2024

In an era where cloud technology is not just an option but a necessity for competitive business operations, the collaboration between Precisely and Amazon Web Services (AWS) has set a new benchmark for mainframe and IBM i modernization. Solution page Precisely on Amazon Web Services (AWS) Precisely brings data integrity to the AWS cloud.

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AWS Machine Learning Blog

FEBRUARY 1, 2024

Data is the foundation to capturing the maximum value from AI technology and solving business problems quickly. To unlock the potential of generative AI technologies, however, there’s a key prerequisite: your data needs to be appropriately prepared. Prerequisites Before starting, you need an AWS account.

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AWS Machine Learning Blog

FEBRUARY 24, 2023

AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers for these types of use cases. In the following sections, we dive into each pipeline in more detail.

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AWS Machine Learning Blog

DECEMBER 5, 2023

This post is written in collaboration with Balaji Chandrasekaran, Jennifer Cwagenberg and Andrew Sansom and Eiman Ebrahimi from Protopia AI. AWS is especially well suited to provide enterprises the tools necessary for deploying LLMs at scale to enable critical decision-making.

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AWS Machine Learning Blog

FEBRUARY 5, 2025

The following diagram illustrates the data pipeline for indexing and query in the foundational search architecture. The listing indexer AWS Lambda function continuously polls the queue and processes incoming listing updates. He has specialization in data strategy, machine learning and Generative AI.

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AWS Machine Learning Blog

AUGUST 22, 2024

Building a deployment pipeline for generative artificial intelligence (AI) applications at scale is a formidable challenge because of the complexities and unique requirements of these systems. Generative AI models are constantly evolving, with new versions and updates released frequently.

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Precisely

OCTOBER 3, 2024

In reviewing best practices for your AWS cloud migration, it’s crucial to define your business case first, and work from there. Migrating to AWS can unlock incredible value for your business, but it requires careful planning, risk management, and the right technical and organizational strategies.

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AWS Machine Learning Blog

OCTOBER 7, 2024

A generative AI Slack chat assistant can help address these challenges by providing a readily available, intelligent interface for users to interact with and obtain the information they need. See Data source connectors for a list of supported data source connectors for Amazon Kendra. through the Slack app.

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O'Reilly Media

SEPTEMBER 15, 2021

In June 2021, we asked the recipients of our Data & AI Newsletter to respond to a survey about compensation. The average salary for data and AI professionals who responded to the survey was $146,000. Cloud certifications, specifically in AWS and Microsoft Azure, were most strongly associated with salary increases.

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Towards AI

MAY 30, 2024

Last Updated on June 3, 2024 by Editorial Team Author(s): Towards AI Editorial Team Originally published on Towards AI. If you’ve enjoyed the list of courses at Gen AI 360, wait for this… Today, I am super excited to finally announce that we at towards_AI have released our first book: Building LLMs for Production.

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Flipboard

AUGUST 17, 2023

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. To do this, we provide an AWS CloudFormation template to create a stack that contains the resources.

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AWS Machine Learning Blog

FEBRUARY 13, 2024

SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts. With this launch, account owners can grant access to select feature groups by other accounts using AWS Resource Access Manager (AWS RAM). Their task is to construct and oversee efficient data pipelines.

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AWS Machine Learning Blog

AUGUST 8, 2024

As one of the largest AWS customers, Twilio engages with data, artificial intelligence (AI), and machine learning (ML) services to run their daily workloads. Data is the foundational layer for all generative AI and ML applications. Access to Amazon Bedrock FMs isn’t granted by default.

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Towards AI

OCTOBER 4, 2023

Mike Shakhomirov Originally published on Towards AI. Advanced-Data Engineering and ML Ops with Infrastructure as Code This member-only story is on us. Photo by Markus Winkler on Unsplash This story explains how to create and orchestrate machine learning pipelines with AWS Step Functions and deploy them using Infrastructure as Code.

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AWS Machine Learning Blog

AUGUST 21, 2024

By walking through this specific implementation, we aim to showcase how you can adapt batch inference to suit various data processing needs, regardless of the data source or nature. Prerequisites To use the batch inference feature, make sure you have satisfied the following requirements: An active 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

MARCH 15, 2024

This approach can help heart stroke patients, doctors, and researchers with faster diagnosis, enriched decision-making, and more informed, inclusive research work on stroke-related health issues, using a cloud-native approach with AWS services for lightweight lift and straightforward adoption. Stroke victims can lose around 1.9

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AWS Machine Learning Blog

APRIL 12, 2023

In this post, we describe how AWS Partner Airis Solutions used Amazon Lookout for Equipment , AWS Internet of Things (IoT) services, and CloudRail sensor technologies to provide a state-of-the-art solution to address these challenges. It’s an easy way to run analytics on IoT data to gain accurate insights.

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ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. Companies are finding NLP to be one of the best applications of AI regardless of industry.

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AWS Machine Learning Blog

DECEMBER 6, 2023

Conversational AI has come a long way in recent years thanks to the rapid developments in generative AI, especially the performance improvements of large language models (LLMs) introduced by training techniques such as instruction fine-tuning and reinforcement learning from human feedback. Run npm install to install the dependencies.

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AWS Machine Learning Blog

SEPTEMBER 28, 2023

This process significantly benefits from the MLOps features of SageMaker, which streamline the data science workflow by harnessing the powerful cloud infrastructure of AWS. The following diagram illustrates the inference pipeline. Click here to open the AWS console and follow along.

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AWS Machine Learning Blog

SEPTEMBER 18, 2023

Ray AI Runtime (AIR) reduces friction of going from development to production. The full code can be found on the aws-samples-for-ray GitHub repository. It integrates smoothly with other data processing libraries like Spark, Pandas, NumPy, and more, as well as ML frameworks like TensorFlow and PyTorch.

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IBM Journey to AI blog

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise.

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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.

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Towards AI

APRIL 4, 2023

SAN JOSE, CA (April 4, 2023) — Edge Impulse, the leading edge AI platform, today announced Bring Your Own Model (BYOM), allowing AI teams to leverage their own bespoke ML models and optimize them for any edge device. Teams can now access the power of Edge Impulse in minutes, with unprecedented ease.

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Pickl AI

DECEMBER 25, 2024

It integrates diverse, high-quality content from 22 sources, enabling robust AI research and development. Its accessibility and scalability make it essential for applications like text generation, summarisation, and domain-specific AI solutions. Its diverse content includes academic papers, web data, books, and code.

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Precisely

MARCH 4, 2024

What if every decision, recommendation, and prediction made by artificial intelligence (AI) was as reliable as your most trusted team members? This isn’t a distant dream – it’s a tangible reality with trusted AI. But how can you make sure your AI can be trusted? Remember some of the newsworthy AI mishaps of 2023?

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The MLOps Blog

JUNE 27, 2023

For example, if you use AWS, you may prefer Amazon SageMaker as an MLOps platform that integrates with other AWS services. SageMaker Studio offers built-in algorithms, automated model tuning, and seamless integration with AWS services, making it a powerful platform for developing and deploying machine learning solutions at scale.

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