Solving complex problems with a computational ecosystem

Computing has changed over the last half century with fundamental new methods for solving problems. Early on relational databases solved the problem of easily storing data, the Internet helped people access information and big data analytics gave businesses insight and knowledge. Many of these solutions are now in the cloud but there are trends colliding and tugging at cloud computing in a world where complex connections between people and computers are forcing more real-time interactions and decision making.

Introspective Systems has developed a software platform that simply but elegantly enables developers to ride six emerging megawaves:

  1. Internet of Things – when sensors inevitably get smarter they will want to “socialize” with each other, not just the cloud.
  2. Drone swarms – when today’s cool toys become tomorrow’s fleets of problem solvers, they will want to “socialize” with each other in flight.
  3. Collaborative AI – when Deep Learning starts teaming up with a dozen other AI techniques as appropriate, wicked problems will get solved.
  4. Internet of Microservices – today’s selective microservices approach to decentralizing corporate IT is just the start.
  5. Edge / Fog computing – Gartner Group and Cisco among others see edge or fog computing as the emerging post-cloud architecture.
  6. V2R – massive simulations (Virtual) will soon feed real-world internet of things control systems (Reality) in a virtuous V2R2V2R… cycle.

The innovation connecting these megawaves is called an executable graph, or xGraph. Just as graph databases fueled the social internet explosion, xGraph is poised to fuel and converge these next megawaves of computing, each of which is developing today on different platforms.

Graph databases are perfect for managing relationships between data on a massive scale, most visibly when people’s relationships are mapped through that data (Facebook, LinkedIn et al).

Executable graphs are perfect for managing relationships between software programs on a massive scale, most importantly for really smart software: machine learning and other artificial intelligence, “big math” data analytics, scientific algorithms, sensor fusion, and real time control systems.

At scale these become “systems of systems” and even “ecosystems of systems” that require a new architecture, not just to make them work but to make them comprehensible to their human developers. The goal of xGraph is to hide complexity wherever possible, enabling the world’s best problem solvers to enhance their own, and others’, ability to see and realize new possibilities.

This new merging of megawaves can be called the Internet of Intelligent Things (IoIT)