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Architecture & Design

Key Takeaway Points and Lessons Learned from QCon London 2020

QCon returned to London this past March for its fourteenth year in the city, attracting over 1,600 senior developers, architects, data engineers, team leads, and CTOs. This article provides a summary of the key takeaways.

Abel Avram
on Apr 07, 2020
Java

Spring Boot Tutorial: Building Microservices Deployed to Google Cloud

In this tutorial, the reader will get a chance to create a small Spring Boot application, containerize it and deploy it to Google Kubernetes Engine using Skaffold and the Cloud Code IntelliJ plugin.

Sergio Felix
on Mar 26, 2020
Culture & Methods

Q&A on the Book AI Crash Course

The book AI Crash Course by Hadelin de Ponteves contains a toolkit of four different AI models: Thompson Sampling, Q-Learning, Deep Q-Learning and Deep Convolutional Q-learning. It teaches the theory of these AI models and provides coding examples for solving industry cases based on these models.

Ben Linders Hadelin de Ponteves
on Mar 19, 2020
Cloud

Has an AI Cyber Attack Happened Yet?

AI cyber attacks have happened and are happening, with increasing regularity. This article looks at recent attacks, the role of bots, and defense strategies you can employ.

Sam Bocetta
on Mar 10, 2020
AI, ML & Data Engineering

The Kongo Problem: Building a Scalable IoT Application with Apache Kafka

In this article, author Paul Brebner discusses the best practices for developing IoT projects using Apache Kafka and Kafka Streams technologies and how to maximize Kafka scalability.

Paul Brebner
on Feb 15, 2020
Culture & Methods

Q&A on the Book Agile Machine Learning

The book Agile Machine Learning by Eric Carter and Matthew Hurst describes how the guiding principles of the Agile Manifesto have been used by machine learning teams in data projects. It explores how to apply agile practices for dealing with the unknowns of data and inferencing systems, using metrics as the customer.

Ben Linders Matthew Hurst
on Feb 12, 2020
AI, ML & Data Engineering

The Road to Artificial Intelligence: An Ethical Minefield

Increasingly-rapid developments in the field of AI have offered society profound benefits, but have also produced complex ethical dilemmas. Many of the most nefarious issues are often overlooked, even in the engineering community. There also exists the meta-ethical question of who ought to be the ones making decisions concerning the encoding of values into autonomous systems.

Lloyd Danzig
on Jan 26, 2020
Web Development

Why Visual AI Beats Pixel and DOM Diffs for Web App Testing

Visual AI breaks regions of pixels into rendered elements for comparison purposes, similar to how humans view web pages. As a result, Visual AI can compare any kinds of images on a page, providing a more effective mechanism for automated visual testing when compared to pixel and DOM diffing.

Michael Battat
on Jan 23, 2020
Culture & Methods

How King uses AI to test Candy Crush Saga

To be able to improve features in games which are constantly evolving, the challenge will be to scale tests to be on a par with new feature development. Automated tests are vital for King to keep up testing Candy Crush, therefore they are constantly looking for new improved ways to test.

Alexander Andelkovic
on Dec 30, 2019
Java

Getting to Know Deep Java Library (DJL)

Amazon has announced DJL, an open source library to develop Deep Learning models in Java. This article details how to get started with the toolkit. The library aims to reduce number of software dependencies by enabling end-end Deep learning development in Java, rather than having to use additional technologies such as Python or R.

Kesha Williams
on Dec 19, 2019
Development

InfoQ Editors' Recommended Talks from 2019

As part of the 2019 end-of-year-summary content, this article collects together a list of recommended presentation recordings from the InfoQ editorial team.

Charles Humble Ben Linders Arthur Casals Manuel Pais Erik Costlow Shane Hastie Shaaron A Alvares Srini Penchikala Michael Redlich Steef-Jan Wiggers Daniel Bryant
on Dec 06, 2019
Development

InfoQ's 2019, and Software Predictions for 2020

We take a look back at what we saw on InfoQ in 2019, and think about what the next year might bring.

Charles Humble Erik Costlow Arthur Casals Daniel Bryant Bruno Couriol Ben Linders Shane Hastie
on Dec 06, 2019

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