November 24, 2019

250 words 2 mins read

From Africa with love

From Africa with love

Isaac Kamga discusses his contribution to the Ballistic Research LaboratoryComputer-Aided Design (BRL-CAD) community implementing a heart-shaped primitive and explains how this catapulted him into a role as a community organizer for Silicon Mountain, Africa's next tech hub.
Talk Title From Africa with love
Speakers Isaac Kamga (Google Developer Group Buea)
Conference O’Reilly Open Source Convention
Conf Tag Making Open Work
Location Austin, Texas
Date May 8-11, 2017
URL Talk Page
Slides Talk Slides
Video

Isaac Kamga discusses his contribution to the Ballistic Research Laboratory–Computer-Aided Design (BRL-CAD) community implementing a heart-shaped primitive and explains how this catapulted him into a role as a community organizer for Silicon Mountain, Africa’s next tech hub. The implementation was a demonstration of the engineering of a heart-shaped primitive within the BRL-CAD open source software package and its impact on the developer community in Cameroon. Using a case study approach, the team designed the heart-shaped primitive’s data structure, and necessary callback functions were written and tested with BRL-CAD’s testing infrastructure. (The Laguerre-based root solver is a sure-fire iterative method for finding roots of polynomials.) This work provided a guideline for the development of primitives within open source computer-aided design (CAD) software and showed that the BRL-CAD package primarily developed for the military sector could be used in nonmilitary locales for entertainment purposes. Isaac explains how he leveraged this experience to invite his entire developer community in Cameroon to contribute to open source software and how startups in Cameroon are leveraging open source software to build businesses.

guide open source infrastructure
comments powered by Disqus
Groovy, There's a Docker in My Application Pipeline [B]

Groovy, There's a Docker in My Application Pipeline [B]

November 23, 2019

In the era of Infrastructure as Code we strive to automate everything, this talk will discuss our experiences in automating the deployment of building of continuous delivery pipelines and solving test …
How can I contribute? A guide to making your first open source contribution

How can I contribute? A guide to making your first open source contribution

November 23, 2019

This talk is for youthe documentarians, developers, students, or community members wondering what you can contribute to open source and how to get started. Lucy Wyman discusses several ways open source projects need your help, what to look for in a project you're contributing to, and some first steps to making your first pull request.
Transforming telecommunications through open source software

Transforming telecommunications through open source software

November 19, 2019

The telecommunications industry's major network operators and vendors have not traditionally engaged with open source. Now, under pressure to transform their networks to support mobile devices and the demand for video, this is changing. William Snow tells the story of how Open Networking Laboratory has transformed the industry through open source and where the industry is headed using open source.
Why choose open infrastructure? (sponsored by IBM)

Why choose open infrastructure? (sponsored by IBM)

November 19, 2019

Open source isnt winning; its won. In the last decade, there's been an incredible explosion in open source software. Massive projects have been developed in the open, on open operating systems, using open languages and compilers. But, Christopher Aedo asks, was all the infrastructure open as well?
From rivulets to rivers: Elastic stream processing in Heron

From rivulets to rivers: Elastic stream processing in Heron

November 6, 2019

Twitter processes billions of events per day the instant the data is generated using Heron, an open source streaming engine tailored for large-scale environments. Bill Graham, Avrilia Floratau, and Ashvin Agrawal explore the techniques Heron uses to elastically scale resources in order to handle highly varying loads without sacrificing real-time performance or user experience.
Semantic natural language understanding at scale using Spark, machine-learned annotators, and deep-learned ontologies

Semantic natural language understanding at scale using Spark, machine-learned annotators, and deep-learned ontologies

November 2, 2019

David Talby and Claudiu Branzan offer a live demo of an end-to-end system that makes nontrivial clinical inferences from free-text patient records. Infrastructure components include Kafka, Spark Streaming, Spark, and Elasticsearch; data science components include spaCy, custom annotators, curated taxonomies, machine-learned dynamic ontologies, and real-time inferencing.