T-Mobile US, Inc. uses artificial intelligence through Amazon Transcribe and Amazon Translate to deliver voicemail in the language of their customers’ choice

By Admin 24/10/2023

AWS Machine Learning Blog This post is co-authored by Dhurjati Brahma, Senior Systems Architect at T-Mobile US, Inc and Jim Chao, Principal Engineer/Architect at T-Mobile US, Inc and Nicholas Zellerhoff Associate Systems Architect at T-Mobile US, Inc. T-Mobile US, Inc. provides a Voicemail to Text service to its customers, which allows customers to quickly read […]Continue reading

From text to dream job: Building an NLP-based job recommender at Talent.com with Amazon SageMaker

By Admin 24/10/2023

AWS Machine Learning Blog This post is co-authored by Anatoly Khomenko, Machine Learning Engineer, and Abdenour Bezzouh, Chief Technology Officer at Talent.com. Founded in 2011, Talent.com is one of the world’s largest sources of employment. The company combines paid job listings from their clients with public job listings into a single searchable platform. With over […]Continue reading

Use the Amazon SageMaker and Salesforce Data Cloud integration to power your Salesforce apps with AI/ML

By Admin 04/08/2023

AWS Machine Learning Blog This post is co-authored by Daryl Martis, Director of Product, Salesforce Einstein AI. This is the second post in a series discussing the integration of Salesforce Data Cloud and Amazon SageMaker. In Part 1, we show how the Salesforce Data Cloud and Einstein Studio integration with SageMaker allows businesses to access […]Continue reading

Bring your own AI using Amazon SageMaker with Salesforce Data Cloud

By Admin 04/08/2023

AWS Machine Learning Blog This post is co-authored by Daryl Martis, Director of Product, Salesforce Einstein AI. We’re excited to announce Amazon SageMaker and Salesforce Data Cloud integration. With this capability, businesses can access their Salesforce data securely with a zero-copy approach using SageMaker and use SageMaker tools to build, train, and deploy AI models. […]Continue reading

How Patsnap used GPT-2 inference on Amazon SageMaker with low latency and cost

By Admin 25/07/2023

AWS Machine Learning Blog This blog post was co-authored, and includes an introduction, by Zilong Bai, senior natural language processing engineer at Patsnap. You’re likely familiar with the autocomplete suggestion feature when you search for something on Google or Amazon. Although the search terms in these scenarios are pretty common keywords or expressions that we […]Continue reading

How OCX Cognition reduced ML model development time from weeks to days and model update time from days to real time using AWS Step Functions and Amazon SageMaker

By Admin 25/05/2023

AWS Machine Learning Blog This post was co-authored by Brian Curry (Founder and Head of Products at OCX Cognition) and Sandhya MN (Data Science Lead at InfoGain) OCX Cognition is a San Francisco Bay Area-based startup, offering a commercial B2B software as a service (SaaS) product called Spectrum AI. Spectrum AI is a predictive (generative) […]Continue reading

Demand forecasting at Getir built with Amazon Forecast

By Admin 15/05/2023

AWS Machine Learning Blog This is a guest post co-authored by Nafi Ahmet Turgut, Mutlu Polatcan, Pınar Baki, Mehmet İkbal Özmen, Hasan Burak Yel, and Hamza Akyıldız from Getir. Getir is the pioneer of ultrafast grocery delivery. The tech company has revolutionized last-mile delivery with its “groceries in minutes” delivery proposition. Getir was founded in […]Continue reading