IBM Journey to AI blog

AUGUST 11, 2023

How to use ML to automate the refining process into a cyclical ML process. Initiate updates and optimization—Here, ML engineers will begin “retraining” the ML model method by updating how the decision process comes to the final decision, aiming to get closer to the ideal outcome.

Data Science 170

Data Science DevOps Machine Learning Data Scientist 170

AWS Machine Learning Blog

JUNE 24, 2024

Their skilled workforce and streamlined workflows allowed us to rapidly label the massive datasets required to train our innovative text-to-animation AI models. Ketaki Shriram, Co-Founder and CTO of Krikey AI. About Krikey AI Krikey AI Animation tools empower anyone to animate a 3D character in minutes.

AI Developer 113

AI Developer AI Development Generative AI AI 113

AWS Machine Learning Blog

FEBRUARY 19, 2025

At AWS re:Invent 2024, we launched a new innovation in Amazon SageMaker HyperPod on Amazon Elastic Kubernetes Service (Amazon EKS) that enables you to run generative AI development tasks on shared accelerated compute resources efficiently and reduce costs by up to 40%. HyperPod CLI v2.0.0

Data Scientist 76

Data Scientist Data Science ML Engineer Generative AI 76

AWS Machine Learning Blog

SEPTEMBER 12, 2024

As generative AI moves from proofs of concept (POCs) to production, we’re seeing a massive shift in how businesses and consumers interact with data, information—and each other. While these layers provide different points of entry, the fundamental truth is that every generative AI journey starts at the foundational bottom layer.

Generative AI 95

Generative AI AI AI ML 95

AWS Machine Learning Blog

JULY 8, 2024

TWCo data scientists and ML engineers took advantage of automation, detailed experiment tracking, integrated training, and deployment pipelines to help scale MLOps effectively. ML model experimentation is one of the sub-components of the MLOps architecture. Anila Joshi has more than a decade of experience building AI solutions.

Data Scientist 118

Data Scientist ML Engineer Machine Learning Data Science 118

Flipboard

JUNE 20, 2023

Machine learning (ML) engineers have traditionally focused on striking a balance between model training and deployment cost vs. performance. This is important because training ML models and then using the trained models to make predictions (inference) can be highly energy-intensive tasks.

Machine Learning 123

Machine Learning BERT Deep Learning ML Engineer 123

AWS Machine Learning Blog

NOVEMBER 14, 2024

It also helps achieve data, project, and team isolation while supporting software development lifecycle best practices. Furthermore, sharing model resources directly across multiple accounts helps improve ML model approval, deployment, and auditing. Siamak Nariman is a Senior Product Manager at AWS. Madhubalasri B.

ML 96

ML Machine Learning Auto-complete Auto-classification 96

AWS Machine Learning Blog

APRIL 7, 2025

Search for the embedding and text generation endpoints. Conclusion In this post, we explored how SageMaker JumpStart empowers data scientists and ML engineers to discover, access, and deploy a wide range of pre-trained FMs for inference, including Metas most advanced and capable models to date. Choose Delete again to confirm.

Machine Learning 86

Machine Learning Large Language Models Python Automation 86

AWS Machine Learning Blog

JUNE 8, 2023

However, businesses can meet this challenge while providing personalized and efficient customer service with the advancements in generative artificial intelligence (generative AI) powered by large language models (LLMs). Generative AI chatbots have gained notoriety for their ability to imitate human intellect.

Generative AI 89

Generative AI LLM Machine Learning Large Language Models 89

AWS Machine Learning Blog

SEPTEMBER 25, 2024

models help you build and deploy cutting-edge generative AI models to ignite new innovations like image reasoning and are also more accessible for on-edge applications. Search for the embedding and text generation endpoints. With a focus on responsible innovation and system-level safety, Llama 3.2 Choose Delete again to confirm.

Software Engineer 129

Software Engineer Software Development ML Python 129

AWS Machine Learning Blog

AUGUST 1, 2024

Amazon Bedrock also provides a broad set of capabilities needed to build generative AI applications with security, privacy, and responsible AI practices. However, deploying customized FMs to support generative AI applications in a secure and scalable manner isn’t a trivial task.

Generative AI 125

Generative AI Machine Learning Artificial Intelligence Artificial Intelligence 125

AWS Machine Learning Blog

JANUARY 10, 2024

Specialist Data Engineering at Merck, and Prabakaran Mathaiyan, Sr. ML Engineer at Tiger Analytics. The large machine learning (ML) model development lifecycle requires a scalable model release process similar to that of software development. This post is co-written with Jayadeep Pabbisetty, Sr.

ML 126

ML Machine Learning Data Scientist ETL 126

AWS Machine Learning Blog

FEBRUARY 11, 2025

Conclusion In this post, we explored how SageMaker JumpStart empowers data scientists and ML engineers to discover, access, and deploy a wide range of pre-trained FMs for inference, including Metas most advanced and capable models to date. On the endpoint details page, choose Delete. Choose Delete again to confirm. models today.

Computer Vision 84

Computer Vision ML Python Automation 84

AWS Machine Learning Blog

NOVEMBER 16, 2023

Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. In this post, we describe how Philips partnered with AWS to develop AI ToolSuite—a scalable, secure, and compliant ML platform on SageMaker.

Data Scientist 115

Data Scientist ML Data Science Machine Learning 115

AWS Machine Learning Blog

SEPTEMBER 23, 2024

Fortunately, generative AI-powered developer assistants like Amazon Q Developer have emerged to help data scientists streamline their workflows and fast-track ML projects, allowing them to save time and focus on strategic initiatives and innovation. For pricing information, see Amazon Q Developer pricing.

ML 86

ML Computer Vision Data Scientist Machine Learning 86

AWS Machine Learning Blog

OCTOBER 15, 2024

Fast Bria AI offers a family of high-quality visual content models. Fast in SageMaker JumpStart and AWS Marketplace, enterprises can now use advanced generative AI capabilities to enhance their visual content creation processes. About the Authors Bar Fingerman is the Head of AI/ML Engineering at Bria.

Generative AI 84

Generative AI ML Python Responsible AI 84

AWS Machine Learning Blog

JUNE 25, 2024

His area of focus is generative AI and AWS AI Accelerators. Niithiyn works closely with the Generative AI GTM team to enable AWS customers on multiple fronts and accelerate their adoption of generative AI. Ziwen Ning is a software development engineer at AWS.

ML 92

ML Metadata Software Development Generative AI 92

AWS Machine Learning Blog

APRIL 29, 2024

Metaflow overview Metaflow was originally developed at Netflix to enable data scientists and ML engineers to build ML/AI systems quickly and deploy them on production-grade infrastructure. How Metaflow integrates with Trainium From a Metaflow developer perspective, using Trainium is similar to other accelerators.

ML 125

ML Python Data Scientist Machine Learning 125

AWS Machine Learning Blog

JULY 23, 2024

collection of multilingual large language models (LLMs), which includes pre-trained and instruction tuned generative AI models in 8B, 70B, and 405B sizes, is available through Amazon SageMaker JumpStart to deploy for inference. Christopher Whitten is a software developer on the JumpStart team.

Machine Learning 125

Machine Learning Computer Vision Python ML 125

AWS Machine Learning Blog

NOVEMBER 21, 2023

Prior to working at Amazon Music, Siddharth was working at companies like Meta, Walmart Labs, Rakuten on E-Commerce centric ML Problems. Tarun Sharma is a Software Development Manager leading Amazon Music Search Relevance. Siddharth spent early part of his career working with bay area ad-tech startups.

ML 109

ML Deep Learning Machine Learning DevOps 109

Snorkel AI

MAY 4, 2023

The free virtual conference is the largest annual gathering of the data-centric AI community. The sessions at this year’s conference will focus on the following: Data development techniques: programmatic labeling, synthetic data, active learning, weak supervision, data cleaning, and augmentation.

Computer Vision 52

Computer Vision Large Language Models Natural Language Processing AI 52

Snorkel AI

MAY 4, 2023

The free virtual conference is the largest annual gathering of the data-centric AI community. The sessions at this year’s conference will focus on the following: Data development techniques: programmatic labeling, synthetic data, active learning, weak supervision, data cleaning, and augmentation.

Computer Vision 52

Computer Vision Large Language Models Natural Language Processing AI 52

ODSC - Open Data Science

JANUARY 10, 2024

The AI Paradigm Shift: Under the Hood of a Large Language Models Valentina Alto | Azure Specialist — Data and Artificial Intelligence | Microsoft Develop an understanding of Generative AI and Large Language Models, including the architecture behind them, their functioning, and how to leverage their unique conversational capabilities.

Large Language Models 52

Large Language Models Deep Learning Data Science LLM 52

AWS Machine Learning Blog

APRIL 25, 2023

This allows ML engineers and admins to configure these environment variables so data scientists can focus on ML model building and iterate faster. About the Authors Dipankar Patro is a Software Development Engineer at AWS SageMaker, innovating and building MLOps solutions to help customers adopt AI/ML solutions at scale.

Machine Learning 96

Machine Learning Data Scientist Python ML 96

AWS Machine Learning Blog

JANUARY 26, 2024

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. This post provides three guided steps to architect risk management strategies while developing generative AI applications using LLMs.

Generative AI 139

Generative AI ML LLM AI 139

AWS Machine Learning Blog

DECEMBER 4, 2024

Organizations of every size and across every industry are looking to use generative AI to fundamentally transform the business landscape with reimagined customer experiences, increased employee productivity, new levels of creativity, and optimized business processes.

ML 137

ML Generative AI Data Scientist ML Engineer 137

AWS Machine Learning Blog

DECEMBER 2, 2024

The generative AI landscape has been rapidly evolving, with large language models (LLMs) at the forefront of this transformation. As LLMs continue to expand, AI engineers face increasing challenges in deploying and scaling these models efficiently for inference. The following table summarizes our setup.

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Large Language Models Auto-complete Machine Learning LLM 107

Marktechpost

APRIL 10, 2025

Bio: Hamza Tahir is a software developer turned ML engineer. Based on his learnings from deploying ML in production for predictive maintenance use-cases in his previous startup, he co-created ZenML , an open-source MLOps framework for creating production grade ML pipelines on any infrastructure stack.

Software Engineer 48

Software Engineer LLM ML Prompt Engineer 48