Category: FAANG

Every data ecosystem requires data integration, and the first step is establishing secure, timely, and reliable data connections to source systems Editor’s note: This is the second post in the Palantir RFx Blog Series, which explores how organizations can better craft RFIs and RFPs to evaluate digital transformation software. Each post focuses on one key capability …

Read more “Data Connection: The first step in data integration (Palantir RFx Blog Series, #2)”

Machine learning (ML) teams need the flexibility to choose their integrated development environment (IDE) when working on a project. It allows you to have a productive developer experience and innovate at speed. You may even use multiple IDEs within a project. Amazon SageMaker lets ML teams choose to work from fully managed, cloud-based environments within …

Read more “Host code-server on Amazon SageMaker”

Founded more than 91 years ago in Seattle, John L. Scott Real Estate’s core value is Living Life as a Contribution®. The firm helps homebuyers find and buy the home of their dreams, while also helping sellers move into the next chapter of their home ownership journey. John L. Scott currently operates over 100 offices …

Read more “Real estate brokerage firm John L. Scott uses Amazon Textract to strike racially restrictive language from property deeds for homeowners”

As a civil engineer, Scott Ashford used explosives to make the ground under Japan’s Sendai airport safer in an earthquake. Now, as the dean of the engineering college at Oregon State University, he’s at ground zero of another seismic event. In its biggest fundraising celebration in nearly a decade, Oregon State announced plans today for …

Read more “AI Supercomputer to Power $200 Million Oregon State University Innovation Complex”

Posted by Yi Tay and Mostafa Dehghani, Research Scientists, Google Research, Brain Team Building models that understand and generate natural language well is one the grand goals of machine learning (ML) research and has a direct impact on building smart systems for everyday applications. Improving the quality of language models is a key target for …

Read more “UL2 20B: An Open Source Unified Language Learner”

Amazon SageMaker multi-model endpoint (MME) enables you to cost-effectively deploy and host multiple models in a single endpoint and then horizontally scale the endpoint to achieve scale. As illustrated in the following figure, this is an effective technique to implement multi-tenancy of models within your machine learning (ML) infrastructure. We have seen software as a …

Read more “Run and optimize multi-model inference with Amazon SageMaker multi-model endpoints”

This post was co-written with Tobias Wenzel, Software Engineering Manager for the Intuit Machine Learning Platform. We all appreciate the importance of a high-quality and reliable machine learning (ML) model when using autonomous driving or interacting with Alexa, for examples. ML models also play an important role in less obvious ways—they’re used by business applications, …

Read more “Testing approaches for Amazon SageMaker ML models”

Amazon Neptune ML is a machine learning (ML) capability of Amazon Neptune that helps you make accurate and fast predictions on your graph data. Under the hood, Neptune ML uses Graph Neural Networks (GNNs) to simultaneously take advantage of graph structure and node/edge properties to solve the task at hand. Traditional methods either only use …

Read more “Encode multi-lingual text properties in Amazon Neptune to train predictive models”

Editor’s Note: This is the second post in our three part blog series about building a customer centric bank. You can read Part 1 here. Banking executives have a lot on their to-do list. Adopt AI and machine learning. Personalize service. Govern responsibly. Embrace new business models. It’s clear that digital transformation and customer-centricity rank high …

Read more “Customer-centric Transformation at a European Bank”