Brian Sletten

The Architectures of Information : REST, Linked Data and Knowledge Graphs

Monday, 9:00 AM EST

Architecture is a tool of structure and facilitation. It is a set of practices designed to elicit a capacity to absorb change. The Web is one of the most successful architectures ever built and most developers still have only a weak grasp on its implications. In the new world of mass technical layoffs, it will be more important than ever for developers, technologists, and architects to do more with less. It will be crucial to demonstrate a capacity to embrace change, not fear it.

In this workshop, we will connect the architecture of the Internet to the Web to API strategies to Linked Data and finally to Knowledge Graphs as a facilitating set of choices and practices to allow our information to embrace technical and business change. We can capture value for longer.

Architecture, Protocols, and Standards

Tuesday, 10:30 AM EST

The Internet works as it was designed. Occasionally new uses, new technologies, and new scenarios confound those designs and force us to evolve. Fortunately, the architecture allows this quite easily, but where and how to effect change is not always obvious.

For those who wish “Full Stack Engineering” to be a more accurate view of their background than simply developing front AND back end systems, this talk will be a comprehensive and illuminating discussion about how the designs of the 1960s have evolved as an architecture and updated collection of protocols and standards.

Machine Learning Platforms : Architecture and Learning

Tuesday, 1:00 PM EST

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 architectures that we are seeing emerge as well as the security implications of protecting them.

Machine Learning Platforms : Architecture and Learning

Tuesday, 3:00 PM EST

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 architectures that we are seeing emerge as well as the security implications of protecting them.

Modern Software Deployments : Heterogeneity, Parallelism, and the Cost of Computation

Wednesday, 11:00 AM EST

The locus of computation is no longer relegated to the quaint notion of a CPU running on a computer. Our modern business mandates require us to embrace a menagerie of computational elements involving CPUs, systems on chips (SOCs), GPUs, FPGAs, ASICs and more. Avoiding a feature-tested explosion of complexity in our applications is crucial to successful delivery strategies that embrace all of these elements and locations. There are waves of change crashing into our industry involving explosions of data, an end to the non-linear trends of Moore’s Law-based speed ups, and a realization that computation costs time, money, power, and more.

At the intersection of architecture, hardware evolution, and more stable software is a fascinating set of technologies that will help lay the foundation for 21st Century software systems.

ChatGPFFT : The Impact of Large Language Models (Or: How I Learned to Think Critically About Technology)

Wednesday, 7:30 PM EST

It’s inescapable. The capabilities that ChatGPT and Large Language Models provide have become discussion topics on the news, in social gatherings, online, at work. Things that would have seemed impossible a few years ago are now nearly pedestrian in how ubiquitous they are becoming on a daily basis. While they show very well, very few people actually understand what is going on, and worse, what is or isn’t possible.

Additionally, there are concerns about the costs involved, the security risks, and the inherent latencies of cloud-based systems. There are additional costs that are not factored into model deployments that we need to consider as well. How do the trends in IT of increased parallelization, heterogeneity, and distributed systems impact the use of these models?

How should we evaluate these achievements as we make decisions on how to adopt and adapt to powerful new technologies? What will they mean for us as a society and as individual knowledge workers? In addition to a discussion specifically about ChatGPT and its peer technologies and what they portend, we will
also discuss critically evaluating new technology as we make decisions in the future.

IPFS : Architecture and Decentralization

Thursday, 9:00 AM EST

Decentralization and Content-based addressing represent a significant advancement in the development of stable, scalable, censorship-resistant systems. They require a remarkable amount of architectural thinking to work effectively. The Interplanetary File System (IPFS) is an umbrella project covering a cornucopia of extremely well designed layers that will prop up and extend the Web in many new directions. Come here about a future that looks a little bit like combining the Web with Git, Bittorrent, Self-certifying file systems, Distributed Hash Tables and more.

We will discuss the architectural layers of this approach and what each brings to the table.