[TALK]@Telematika

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Peering Coordination Forum

February 13, 2020

The forum provides time for attendees to meet and network with others in the peering community present at NANOG. Peering Representatives, who completed and submitt …

Lightning Talk: Identifying DNS Open Resolvers in IPv6

February 10, 2020

Introduction As all of you know, having DNS servers considered Open Resolvers is very negative, both for those who leave the service open, for the Internet and for …

CNCF: Making Standards without Standards

February 8, 2020

In the not too distant past interoperability was driven by Standards produced by SDOs such as W3C and OASIS. Paper Standards first, followed by code to prove the Standard. Since then weve flipped thi …

The State of Traffic Engineering - an ISP's Perspective

February 6, 2020

This talk will go over the current state of the major Traffic Engineering solutions (starting with basic static routing and working through IGP as MED, AIGP, RSVP- …

How CLEVER is your neural network? Robustness evaluation against adversarial examples

February 3, 2020

Neural networks are particularly vulnerable to adversarial inputs. Carefully designed perturbations can lead a well-trained model to misbehave, raising new concerns about safety-critical and security-critical applications. Pin-Yu Chen offers an overview of CLEVER, a comprehensive robustness measure that can be used to assess the robustness of any neural network classifiers.

KRACK Simplified

February 3, 2020

WiFi devices have been using a security protocol called WPA2 without any known issues for over a decade. But in October 2017, two security researchers from Univers …

TL;DR NIST Container Security Standards

February 3, 2020

In September 2017, the National Institute of Standards and Technology issued a 63 page paper detailing their recommendations for container security. While its chock-full of recommendations all cloud …

Pat Helland and me: How to build stateful distributed applications that can scale almost infinitely

January 29, 2020

In 2007, Pat Helland published "Life Beyond Distributed Transactions: An Apostates Opinion," in which he conducts a thought experiment on how to design a distributed database that can scale almost infinitely. While the paper explicitly addresses distributed database design, Sean Allen shows that the ideas are far more widely applicable, particularly in scaling stateful applications.

Evaluate deep Q-learning for sequential targeted marketing with 10-fold cross-validation

January 13, 2020

Jian Wu discusses an end-to-end engineering project to train and evaluate deep Q-learning models for targeting sequential marketing campaigns using the 10-fold cross-validation method. Jian also explains how to evaluate trained DQN models with neural network-based baseline models and shows that trained deep Q-learning models generally produce better-optimized long-term rewards.

How Captricity built a human-level handwriting recognition engine using data-driven AI

January 11, 2020

Captricity has deployed a machine learning pipeline that can read handwriting at human-level accuracy. Ramesh Sridharan discusses the big ideas the company learned building and deploying this system, using data to identify specific problems to solve using AI and to evaluate and validate the algorithm itself and the overall system once deployed.

Neural Network Distiller: A PyTorch environment for neural network compression

January 11, 2020

Neta Zmora offers an overview of Distiller, an open source Python package for neural network compression research. Neta discusses the motivation for compressing DNNs, outlines compression approaches, and explores Distiller's design and tools, supported algorithms, and code and documentation. Neta concludes with an example implementation of a compression research paper.

All the cool kids are doing it; maybe we should too? Jupyter, gravitational waves, and the LIGO and Virgo Scientific Collaborations

January 9, 2020

Will Farr shares examples of Jupyter use within the LIGO and Virgo Scientific Collaborations and offers lessons about the (many) advantages and (few) disadvantages of Jupyter for large, global scientific collaborations. Along the way, Will speculates on Jupyter's future role in gravitational wave astronomy.

Scheduled notebooks: A means for manageable and traceable code execution

January 6, 2020

Using an nteract project, papermill, Matthew Seal walks you through how Netflix uses notebooks to track user jobs and make a simple interface for work submission. Youll get an inside peek at how Netflix is tackling the scheduling problem for a range of users who want easily managed workflows.

The reporters notebook

January 5, 2020

Beyond Twitter, Facebook, and similar networks, without question, data, code, and algorithms are forming systems of power in our society. Mark Hansen explains why it is crucial that journalistsexplainers of last resortbe able to interrogate these systems, holding power to account.

Intro: Chaos Engineering BoF

December 21, 2019

In this session, we will cover the work performed by the community since we made the proposal for a CNCF Chaos Engineering WG at KubeCon Copenhagen. We will review the WHITEPAPER and future direction …

Pat Helland and me: How to build stateful distributed applications that can scale almost infinitely

December 20, 2019

You are (w)here? Geospatial web dev off the beaten map

December 12, 2019

Focusing on a mix of artificial, scientific, and environmental sensing data, Aurelia Moser explores fantasy and farcical mapping, teasing out the tough parts of geocoding on real and mythical spatial matrices while delving into the contrived topographies of null island, paper towns, "dumb" cities, and the infinitely curious world of geospeculative design in JavaScript.

The Paradise Papers: Behind the scenes with the ICIJ

December 5, 2019

Last November, the International Consortium of Investigative Journalists (ICIJ) published the Paradise Papers, a yearlong investigation on the offshore dealings of multinational companies and the wealthy. Pierre Romera offers a behind-the-scenes look into the process and explores the challenges in handling 1.4 TB of data and making it available securely to journalists all over the world.

Automation and analytics enablement in life insurance

November 29, 2019

Divya Ramachandran explains how top insurance companies have used handwriting transcription powered by deep learning to achieve a more than 70% reduction in daily operational processing time, develop a best-in-industry predictive model for assessing mortality risk from decades of archived forms, and enable a smarter claims leakage review, which led to a 10x ROI in its first year.

Good Enough for the Finance Industry: Achieving High Security at Scale with Microservices in Kubernetes

November 27, 2019

Security is a challenge for most companies. Especially those in periods of rapid growth. It is often taken for granted as we trust the frameworks we use to implement the necessary security protocols f …

Vectorized query processing using Apache Arrow

November 19, 2019

Query processing technology has rapidly evolved since the iconic C-Store paper was published in 2005, with a focus on designing query processing algorithms and data structures that efficiently utilize CPU and leverage the changing trends in hardware to deliver optimal performance. Siddharth Teotia outlines the different types of vectorized query processing in Dremio using Apache Arrow.

TL;DR NIST Container Security Standards

November 17, 2019