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09 Jan 2017 – The Year of AI

Recently, January 5th, 2017, on my ride into work I was listening to BBC World Update with Dan Damon, as I often do, and heard him interviewing someone about the new artificial intelligence (AI) app for the British National Health Service from Babylon Health (similar story on TechCrunch). It’s a Chat Bot for SMS text […]

20 Oct High 5s of Intelligent Information Modeling

Converged Canonical Model

Quantitative data is easy to make into useful information by establishing correct associations and providing human experts with the right slicing and dicing tools. But in its native format, data is not independently meaningful. Many qualitative content sources are narrative, born as whole information. Such content is advanced beyond data because of the built-in associations, but inevitably more difficult for machines to […]

26 Jan Give Me Smart Requirements

Get SMART

I know how to solve this problem! I’ll just blast it to smithereens – Fire – Aim – Ready. Artificial Intelligence (AI) has been explored and developed in universities and startup companies throughout the developed world for decades, but is still struggling to reach the mainstream. There are many companies that effectively use intelligent processes and […]

29 Dec Unhuman Expertise

Expert System Architecture with Common Sense

Artificial Intelligence has suffered from a persistent scale problem: up to now, many techniques have been shown to work well and reliably in narrowly defined domains, but outside the domains of their expertise, they fall apart very quickly. No techniques of which I am aware, have exhibited common sense in the way we expect humans […]

10 Dec Measuring Knowledge

Measuring Knowledge

Sometimes you need to know about your knowledge. When you’re in the middle of trying to build a system that knows stuff, you may ask, how much does the system know after this training or learning cycle as a percent of the total knowable amount? When we test students in their learning cycles, we use a […]

26 Nov Planning and Scheming

Paint a Brain

Select a Knowledge Representation (KR) Scheme In prior posts I have been describing the steps of building knowledge systems. A major part of Step 3: Task 1 is defining how to store knowledge – selecting a scheme. Giarratano and Riley (1989) suggest making the selection of a scheme, such as rules, frames or logic, dependent upon […]

17 Nov Environmental Awareness for AI Geeks

Selecting an Environment and Tools I plan to take a few posts in this section to focus on expert systems (Giarratano 1989), exploring the development process in greater detail. While some projects require no development, some require you to select a platform or development environment or both. There are specially designed development platforms, tools and environments that provide much of the […]

09 Oct Resolving a Paradox

Square Paradox

In time and space some things are impossible, but the pen is more powerful than reality. I can draw a world in which stairs lead in crazy, mind-bending directions, and I could probably build a structure that implemented upside-down staircases to nowhere. But I could never build the cube shown here, because it violates some […]