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

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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

Neil Raden: “Before the world went analytics crazy…”

Neil Raden: I’m re-posting an article I published six months ago about Process Intelligence a.k.a. Process Mining. I’ve been getting a lot of questions about this lately. “Is Process Intelligence (Mining) a distinct discipline from analytics?” Link 

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Challenge Aug-2019: Stateful Decisioning

Nowadays it’s not enough for decision making applications to simply execute a complex rules-based transaction, forget about it, and wait for the next one. They should be able to learn from already executed transactions and evaluate new facts as they become available. As many BR&DM vendors advance their products to support such stateful, perpetually running applications, we bring  back the old Challenge that mainly remains unresolved. So, how would you support the following Dynamic Loan Evaluation scenario today? Link  Video

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