Hugging Face gets an Amazon treatment

AWS Hugging Face

To amplify the process of embracing natural language processing models via the power of AI, Amazon Web Service (AWS) chose to collaborate with Hugging Face, who are pursuing various ways to make this process elementary.

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[Paper Summary] Researchers at the University Of Genoa and AWS analyze techniques to Make Machine Learning (ML) Models fairer

AI fair or unfair

This research on algorithmic fairness provides three main approaches, i.e., pre-processing data, post-processing an already learned ML model, and in-processing, which consists of enforcing fairness notions by imposing specific statistical constraints on the learning phase of the model.

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Amazon launches Lookout for Metrics, an AWS service to monitor business performance


Amazon today announced the general availability of Lookout for Metrics, a fully managed service that uses machine learning to monitor key factors impacting the health of enterprises. Launched at re: Invent 2020 last December in preview, Lookout for Metrics can now be accessed by most Amazon Web Services (AWS) customers via the AWS console and through supporting partners.

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Vonage Contact Center Intelligence receives AWS Machine Learning competency status in Applied AI

Robot Vonage

In years past, the march toward innovation in the contact center could be described more as a steady trek than a sprint. Moving from a core function that had been viewed mainly as a cost center to one focused on customer satisfaction and a means of delivering personalized customer experiences has its roots prior to 2020 but has accelerated tremendously over the past year.

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Amazon launches computer vision service to detect defects in manufactured products


Amazon announced the general availability of Amazon Lookout for Vision, a cloud service that analyzes images using computer vision and AI to spot product or process defects and anomalies in manufactured products. Amazon says Lookout for Vision, which is available in select Amazon Web Services (AWS) regions via the AWS console and suppo

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Architect and build the full machine learning lifecycle with AWS: An end-to-end Amazon SageMaker demo

ML Lifecycle

In this tutorial, we will walk through the entire machine learning (ML) lifecycle and show you how to architect and build an ML use case end to end using Amazon SageMaker. Amazon SageMaker provides a rich set of capabilities that enable data scientists, machine learning engineers, and developers to prepare, build, train, and deploy ML models rapidly and with ease. For our use case, we have chosen an automobile claims fraud detection example.

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What Andy Jassy’s ascension to CEO means for Amazon’s AI initiatives

This week, Jeff Bezos announced that he’ll step down as CEO at Amazon and transition to an executive chair role during the third quarter of this year. Amazon Web Services (AWS) CEO Andy Jassy will take his place, heading up a company currently valued at around $1.6 trillion. Jassy, who joined Amazon in 1997 and has led AWS since its inception in 2003, believes Amazon’s decision to double down on AI early differentiated it from the competition.

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Retraining Machine Learning Model approaches

Typewriter and items

Generally machine learning models will be trained by some learning between set of input features and dependent feature or target variable. The aim of the model is to minimize the prediction error by applying or optimizing cost functions, and when we found some optimized models, we will deploy into the production and the aim is that model will generate accurate predictions on future unseen data as well so the goal is that model will predict the future unseen data as accurately as data used during the training period.

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How I built this: Machine learning with Amazon Personalize and a Customer Data Platform

By making off-the-rack machine learning models accessible for anyone to use, cloud ML services like Amazon Personalize help make ML-driven customer experiences available to teams at any scale. You no longer need in-house data science and machine learning experts to get the benefit of propensity scoring or product recommendations.

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The evolution of Big Data compute platforms  – past, now and later

A journey into the evolution of Big Data Compute Platforms like Hadoop and Spark. Sharing my perspective on where we were, where we are and where we are headed. Over the past few years I have been part of a large number of Hadoop projects. Back in 2012–2016 the majority of our work was done using on-premises Hadoop infrastructure.

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Nvidia moves its Software closer to cloud customers through an AWS Storefront

Nvidia is making it easier for AWS cloud customers to find and integrate Nvidia software applications into their AI and deep learning projects through an all-new, all-in-one “storefront” in the AWS Marketplace.

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AWS expands on SageMaker capabilities with end-to-end features for machine learning

Nearly three years after it was first launched, Amazon Web Services’ SageMaker platform has gotten a significant upgrade in the form of new features, making it easier for developers to automate and scale each step of the process to build new automation and machine learning capabilities, the company said.

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Amazon launches new AI services for DevOps and business intelligence applications

Amazon today launched SageMaker Data Wrangler, a new AWS service designed to speed up data prep for machine learning and AI applications. Alongside it, the company took the wraps off of SageMaker Feature Store, a purpose-built product for naming, organizing, finding, and sharing features, or the individual independent variables that act as inputs in a machine learning system. Beyond this, Amazon unveiled SageMaker Pipelines, which CEO Andy Jassy described as a CI/CD service for AI.

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TravoBOT – “Move freely in the pandemic” (AWS Serverless Chatbot)

Of all the things that this pandemic has taught us, one of the primary concern that many people are still facing is the uncertainty in planning their travel – either in case of emergency or for leisure. And this resulted in TravoBOT – A chatbot that helps the user by collating information from different data sources and provide user with a travel recommendation to a particular destination.

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Algorithmia 2020 state of enterprise Machine Learning

The main takeaway from the 2020 State of Enterprise Machine Learning survey is that a growing number of companies are entering the early stages of ML development, but challenges in deployment, scaling, versioning, and other sophistication efforts still hinder teams from extracting value from their ML investments.

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AWS Machine Learning – Helping small businesses deliver personalized experiences with the Amazon Personalize extension for Magento

This is a guest post by Jeff Finkelstein, founder of Customer Paradigm, a full-service interactive media firm and Magento solutions partner. Many small retailers use Magento, an open-source ecommerce platform, to create websites or mobile applications to sell their products online.

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NVIDIA chucks its MLPerf-leading A100 GPU into Amazon’s cloud

NVIDIA’s A100 set a new record in the MLPerf benchmark last month and now it’s accessible through Amazon’s cloud. Amazon Web Services (AWS) first launched a GPU instance 10 years ago with the NVIDIA M2050. It’s rather poetic that, a decade on, NVIDIA is now providing AWS with the hardware to power the next generation…

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