Remove de platforms packaging-and-infrastructure
article thumbnail

Accelerate machine learning time to value with Amazon SageMaker JumpStart and PwC’s MLOps accelerator

AWS Machine Learning

This is a guest blog post co-written with Vik Pant and Kyle Bassett from PwC. With organizations increasingly investing in machine learning (ML), ML adoption has become an integral part of business transformation strategies. Central to this paradigm is a pipeline-centric viewpoint for developing and operating industrial-strength ML systems.

article thumbnail

Build financial search applications using the Amazon Bedrock Cohere multilingual embedding model

AWS Machine Learning

Cohere’s multilingual embedding model Cohere is a leading enterprise AI platform that builds world-class large language models (LLMs) and LLM-powered solutions that allow computers to search, capture meaning, and converse in text. They provide ease of use and strong security and privacy controls.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Customer Data Analytics: How to Select the Best Tool for Your Needs

Pointillist

In this post, I’ll review the pros and cons of six major categories: customer data platforms, business intelligence software, customer analytics tools, digital experience platforms, journey mapping tools, and customer journey analytics software. What are Customer Data Platforms?

article thumbnail

Fine-tune and deploy Llama 2 models cost-effectively in Amazon SageMaker JumpStart with AWS Inferentia and AWS Trainium

AWS Machine Learning

Today, we’re excited to announce the availability of Llama 2 inference and fine-tuning support on AWS Trainium and AWS Inferentia instances in Amazon SageMaker JumpStart. Fine-tuning and deploying LLMs, like Llama 2, can become costly or challenging to meet real time performance to deliver good customer experience.

article thumbnail

Announcing new Jupyter contributions by AWS to democratize generative AI and scale ML workloads

AWS Machine Learning

The Jupyter Notebook, first released in 2011, has become a de facto standard tool used by millions of users worldwide across every possible academic, research, and industry sector. Our goal is to work in the open-source community to help Jupyter to be the best possible notebook platform for data science and ML.

APIs 86
article thumbnail

Five Consumer Forces Shaping Move

C Space

Five Consumer Forces Shaping Move. In March of 2020, we launched an exploration to understand how people’s lives are changing amidst the new realities thrust upon us by the pandemic, social unrest and evolving technologies. The “inward“ part of the cycle will be with us for some time. We believe that’s the wrong question. To make better choices.