DARPA Explainable AI Program

Defense Advanced Research Projects Agency Explainable AI (XAI) program:

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How Do Your Decision Microservices Communicate?

After you deploy your business decision models as microservices, you need to organize your inter-service communication.  Usually, your decision microservices are stateless. But what if they need to maintain some state? What if they updated values and those values got automatically propagated to other microservices via an in-memory platform? There are no database lookups, no file system writes, and no conflicts. For example, microservices tasked with running machine learning models need to maintain the state of their models and their parameter weights. This brings the important question: where are the states stored? Watch the Hazelcast’s webinar “How In-Memory Computing Enables a New Generation of Microservices.” See also “How to Make Microservices Communicate” Share your preferred communication mechanisms with the DM Community.

Posted in Architecture, Microservices | 1 Comment

Challenge Sep-2019 “Crack the Code”

While we are still waiting for the first solution for our Aug-2019 Challenge “Stateful Decisioning“, we’ve just announced a fun Challenge for Sep-2019 “Crack the Code“. Try it with any tool or just your common sense. Link

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QnA Panel “Ask a Vendor” at DecisionCAMP

DecisionCAMP will run a QnA Panel “Ask a Vendor” on Sep. 18 at 17:00 – see schedule. The presenting vendors will be given 5 minutes each to briefly describe their latest achievements, next important moves, and answer questions from the audience. There will be seven BR&DM vendors on the panel:

  • FICO
  • IBM
  • Oracle
  • OpenRules
  • Red Hat
  • Sapiens
  • Trisotech.

This panel will be moderated by Sandy Kemsley. You still may register for this important event (for just €150) and meet the DM experts face-to-face in Bolzano next month.

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New Gartner IaaS Magic Quadrant

On July 19 Gartner published its latest “Magic Quadrant for Cloud Infrastructure as a Service, Worldwide“. AWS is being recognized as the Leader for 9th consecutive year following Microsoft, Google, Alibaba, Oracle, and IBM. The report describes their offerings with strengths and cautions. All these cloud infrastructures are potential destinations for modern Operational Decision Services. Link

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DeepMind’s Losses and the Future of AI

Wired just published an article that analyzes  how the recent DeepMind’s losses will affect AI in general. “The investment community notices significant losses; if DeepMind’s losses were to continue to roughly double each year, even Alphabet might eventually feel compelled to pull out. And it’s not just the money. There’s also the lack of tangible financial results thus far. At some point, investors might be forced to recalibrate their enthusiasm for AI.” Link

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Business Decision Models are moving to Serverless World

Posted in Architecture, Business Rules, Decision Models, Serverless, Trends | Leave a comment

IBM Research launches explainable AI toolkit

IBM Research introduced AI Explainability 360, an open source collection of state-of-the-art algorithms that use a range of techniques to explain AI model decision-making. “That’s fundamentally important, because we know people in organizations will not use or deploy AI technologies unless they really trust their decisions. Link

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Flash Points: Business Rules, Events, and Integrity

Ron Ross just published “Flash Points: Business Rules, Events, and Integrity“: “Flash points are the specific events when a rule needs to be evaluated based only on the semantics of the rule itself. For a behavioral business rule, flash points are the events where the rule could be violated. Flash points for the same rule can occur in multiple processes, procedures, use cases, etc. Comprehensive support for flash points is essential for maintaining the integrity of business solutions. Invoking flash points automatically requires ‘stateful’ platforms.” Ron will be our presenter at the upcoming DecisionCAMP. Link

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Opinion: Traditional Rule Engines Outlived their Usefulness

This LinkedIn article “How Traditional Rules Engines Stifle Innovation” states: “AI and advanced analytics are key to life insurance innovation. While the industry tries to make use of these technologies, the insurance application continues to play a central role in the underwriting process and… so does the traditional rules engine. While rules engines started as a novel way to automate underwriting in the 2000’s, the technology has outlived its usefulness and may actually hurt current efforts to innovate. Here’s why…”  Link What’s your opinion? Place your comments here.

Posted in Decision Making, Insurance Industry, Rule Engines and BRMS | 1 Comment