Brian Sletten

Forward Leaning Software Engineer

Brian Sletten is a liberal arts-educated software engineer with a focus on forward-leaning technologies. His experience has spanned many industries including retail, banking, online games, defense, finance, hospitality and health care. He has a B.S. in Computer Science from the College of William and Mary and lives in Auburn, CA. He focuses on web architecture, resource-oriented computing, social networking, the Semantic Web, data science, 3D graphics, visualization, scalable systems, security consulting and other technologies of the late 20th and early 21st Centuries. He is also a rabid reader, devoted foodie and has excellent taste in music. If pressed, he might tell you about his International Pop Recording career.

 

Talks on Wurreka:

Machine Learning is clearly here to stay. While it is a far cry from actual Artificial Intelligence, it provides many invaluable and remarkable ways to learn from the data we are collecting about our customers, products and daily activities. The past afforded us machine learning libraries which became machine learning frameworks. Now, we are designing and building machine learning platforms that facilitate entire initiatives in reusable and extensible ways. We will discuss many of the drivers of modern machine learning systems and the platforms that we are seeing emerge.

We think about architecture in terms of its capacity to describe existing systems or its ability to induce runtime properties, but we often do not spend enough time thinking about its role in security. An architectural risk assessment (ARA) is an organizational activity that should be done periodically, usually at the beginning of a project or prior to a major refactoring. It is an attempt to align security goals with business goals and to measure and describe the risks associated with systems and the people who use and design them. It is also a useful approach for considering potential for abuse and how that can be mediated. We will discuss an overview of the approach and its various activities.

When the clouds descend to the Earth, we call that fog. When cloud computing moves closer to your end users, we do not really have a name for that yet, but I have seen the term “fog computing” and think it fits. We are seeing new environments emerge from vendors that allow you to treat computation as something to locate around the world for low-latency client interactions. Think of it like what Content Delivery Networks (CDNs) do for static files (HTML, JavaScript, stylesheets, etc.) but for multi-tenancy software. It’s a great way to mix serverless and microservices initiatives with the realities of global deployment.

We do not usually think of Java when we think about modern Deep Learning systems. Syntactically and culturally it is not the best fit when compared to languages such as Python, R or Julia. There have been some new libraries and frameworks emerging, however, that will allow you to take advantage of modern algorithms and techniques on the Java platform sometimes even with hardware acceleration via GPUs. We will introduce the major players in the field and show some compelling examples running in Java.

Java has always been one of the languages and runtimes with the best support for Semantic Web standards. There have been some updates in the last several years, however, that create a bunch of new opportunities for bringing these technologies into your Java applications. We will introduce you to the standards, but also highlight some of the open source and commercial software that will breath new capabilities for flexible data integration, inferencing and the ability to evolve over time.

We will cover:

  • Resource Description Framework (RDF) and RDFS
  • JSON-LD
  • SPARQL
  • Web Ontology Language (OWL)
  • Linked Data

While still new to most people, WebAssembly provides a formidable vision of safe, fast, portable code. Through clever choices and well-considered design, the basic vision allows us to target browsers as a platform using a variety of languages other than (but compatible with) Javascript. This technology coupled with advancements in the Web platform are setting up the future of Web-delivered applications to look more like (and likely to replace) desktop applications.

The numerics of machine learning seem like the least likely thing you would expect to run in a browser. TensorFlow.js provides exactly that. This Javascript implementation of the TensorFlow APIs is backed by GPU-accelerated WebGL, WebAssembly and the optimizations available to modern Javascript engines.

Now, as our production systems become more distributed geographically, we can push some ML capabilities to the edge.

The Semantic Web and its related technologies provide an incredibly powerful model for driving the cost of data integration down to nearly zero by applying Web-related standards to data. So, how do we help developers who are overwhelmed, frightened or annoyed by its data models and formats?

Everyone can have semantically rich, interoperable data and modern application tools, frameworks and user interfaces. There is a surprisingly simple mechanism by which “normal” developers can benefit from the power of the Semantic Web and the latter's developers can integrate with the panoply of tools and toys under constant development by the former.

The trick is JSON-LD. A simple, but deliberately designed extension to JSON that bridges both worlds and is finding its way into many other uses.

You will learn about:

  • The JSON-LD format
  • How to frame, sign and validate it
  • How to convert it to/from RDF
  • How to describe Hypermedia systems with Hydra and JSON-LD
  • How to embed and consume JSON-LD in HTML documents
  • How JSON-LD is being used in a variety of mass market ways

The LLVM Project has been around for over a decade, but is increasingly important as a compiler infrastructure to get reuse and portability, shared optimizations and a faster time to market. Many newer programming languages have chosen it as the basis of their toolchain including Swift, Julia, Rust and more. In this talk, we will talk about the tools, components and layers of LLVM and how it is helping usher in new visions of portability and reuse.

While still new to most people, WebAssembly provides a formidable vision of safe, fast, portable code. Through clever choices and well-considered design, the basic vision allows us to target browsers as a platform using a variety of languages other than (but compatible with) Javascript. This technology coupled with advancements in the Web platform are setting up the future of Web-delivered applications to look more like (and likely to replace) desktop applications.

Rust has quickly become an incredibly popular language with exceptional tooling, documentation and a renowned community that welcomes and helps those who are new. It is intended as a systems programming such as C/C++ but has modern functional capabilities and intentionally-designed safety features.

While it has mostly been in use for open source projects so far, it is quickly becoming important to initiatives at Apple, Microsoft and other companies so it is a great time to learn how it is different and how it allows you to convert run time errors to compile time errors.

It does have a steep learning curve, however, so we will walk through some of the common early gotchas and help you quickly become proficient in this popular and powerful new language finding its way into all manner of software development.

Our industry never stops changing, but sometimes those changes are trivial and fluffy and we can ignore them. Sometimes they are fundamental and enduring. This workshop is going to highlight some of the most important trends happening in the hardware, software, data and architecture spaces and why you should be paying attention to them.

We will focus on a group of independent technologies that are forming the basis of powerful strategies to modernize our IT systems at fundamental and incremental levels. This workshop will help you prepare for the future and focus on learning things that will have long-ranging impact for years to come.

It’s an exciting time to learn about machine learning, data science and AI, but it isn’t always easy for “regular developers” to find their way into this space. After training nearly 3000 people around the world on the topic, I have found approaches that make it easier to get started and discover where you can contribute depending on your background. Come hear about how you can update your career over time to participate in these emerging technical fields.

Machine Learning is clearly here to stay. While it is a far cry from actual Artificial Intelligence, it provides many invaluable and remarkable ways to learn from the data we are collecting about our customers, products and daily activities. The past afforded us machine learning libraries which became machine learning frameworks. Now, we are designing and building machine learning platforms that facilitate entire initiatives in reusable and extensible ways. We will discuss many of the drivers of modern machine learning systems and the platforms that we are seeing emerge.

The numerics of machine learning seem like the least likely thing you would expect to run in a browser. TensorFlow.js provides exactly that. This Javascript implementation of the TensorFlow APIs is backed by GPU-accelerated WebGL, WebAssembly and the optimizations available to modern Javascript engines.

Now, as our production systems become more distributed geographically, we can push some ML capabilities to the edge.

Imagine:

  • Reusing existing models in distributed and decentralized architectures
  • Image and object detection from local video streams
  • Event classification from IoT-based sensors
  • Interact with WebAssembly-optimized code on all browsers and platforms
  • Natural Language Processing of user text and audio

See Highlights of
Wurreka

Hear What Attendees Say

PWC Logo

“Once again Wurreka has knocked it out of the park with interesting speakers, engaging content and challenging ideas. No jetlag fog at all, which counts for how interesting the whole thing was."

Cybersecurity Lead, PwC

Intuit Logo

“Very much looking forward to next year. I will be keeping my eye out for the date so I can make sure I lock it in my calendar"

Software Engineering Specialist, Intuit

Groupon Logo

“Best conference I have ever been to with lots of insights and information on next generation technologies and those that are the need of the hour."

Software Architect, GroupOn

Hear What Speakers & Sponsors Say

Scot Davis

“Happy to meet everyone who came from near and far. Glad to know you've discovered some great lessons here, and glad you joined us for all the discoveries great and small."

Scott Davis, Web Architect & Principal Engineer, ThoughtWorks

Oracle

“What a buzz! The events have been instrumental in bringing the whole software community together. There has been something for everyone from developers to architects to business to vendors. Thanks everyone!"

Voltaire Yap, Global Events Manager, Oracle Corp.

Venkat Subramaniam

“Wonderful set of conferences, well organized, fantastic speakers, and an amazingly interactive set of audience. Thanks for having me at the events!"

Dr. Venkat Subramaniam, Founder - Agile Developer Inc.