Champion/Challenger and Operational Negation

In May Stacey West from FICO took a thorough look at Champion/Challenger strategies testing and how it can be successfully implemented to enhance your organisation’s decisions. In her new post she is discussing how Champion/Challenger strategies may become unreadable because of operational negation. Learn what operational negation is and how to avoid it. Link

Posted in Decision Modeling, QA, Testing | Leave a comment

Forrester’s Report “Digital Decisioning Platforms”

Forrester just published a new report “Introducing AI-Powered, Human-Controlled Digital Decisioning Platforms“: Digital decisioning platforms (DDPs) allow application development and delivery (AD&D) pros to combine the best of human decision logic with the best of AI to implement application-embedded automated decisions, i.e., digital decisions. DDPs accomplish this by providing a suite of capabilities that enable business subject-matter experts to define decision logic, incorporate data-driven decision intelligence technologies such as machine learning (ML), govern change, and deploy digital decisions within business applications.  Link

Posted in Business Analytics, Digital Decisioning | Leave a comment

The AI Evolution and the Challenge of Decision Automation

In his latest post Prof. Warren Powell contrasts “using AI to automate decisions to Tesla’s aggressive use of robotics to automate their assembly lines. It is important to understand the most common use of AI today (machine learning) with the tools for making decisions. I also talk about “failures” of AI as primarily failures in setting expectations. AI is not a revolution – it is an evolutionary process, and we have to do more than just automate what people do, and how they do it.” Link

Continue reading

Posted in Artificial Intelligence, Decision Optimization, Machine Learning | Leave a comment

ML & FSM help amputees walk more naturally

Researchers from the University of Utah designed a robotic leg that learns from the user’s motion how to help amputees walk more naturally.  It uses machine learning to generate a human-like stride. It also helps wearers step over obstacles in a natural way. Link   Continue reading

Posted in Artificial Intelligence, Machine Learning, State Machines | Leave a comment

Regressing Testing Decisions

Today Carole-Ann Berlioz (Sparkling Logic) led the first post-DecisionCAMP-2020 Zoom Session presenting “Best Practices for Regressing Testing Decisions”. Watch her presentation and Q&A at https://www.youtube.com/watch?v=k8sDhKzU0_Y

Posted in Uncategorized | 1 Comment

Decision analytics: What is AI?

Prof. Warren B Powell from Princeton University: “The most common types of AI come in three flavors: rules, machine learning, and making decisions (“optimization”). Rules are used for guiding computers to identify patterns or make recommendations, and have to be designed by people. This is how AI was done in the 1970’s. Learning involves using an external dataset to fit a statistical model.” Link Continue reading

Posted in Artificial Intelligence, Decision Making, Decision Optimization, Machine Learning | Leave a comment

Giving GPT-3 a Turing Test

GPT-3 is a general language model, trained on a large amount of uncategorized text from the internet. It isn’t specific to a conversational format, and it isn’t trained to answer any specific type of question. The only thing it does is, given some text, guess what text comes next.
Ofer Razon wrote: GPT-3 discussions are all over the network now, and while we all see some mind-blowing use cases that tease our mind what can come next, we also get to see the pitfall of AI/ML systems. Put in simple words – it doesn’t know how to say “I don’t know”.  This article “Giving GPT-3 a Turing Test” is a must-readLink

Posted in Artificial Intelligence, Natural Language Processing | Leave a comment

Implementing Rating Engines

Carole-Ann Berlioz from Sparkling Logic posted practical product-agnostic recommendations for  implementation of various decision engines aimed at calculating a fee or cost: rating engine, pricing engine, compensation calculation, fee calculation, claims calculation, etc. Link

Posted in Uncategorized | Leave a comment

Teach Your Microservices to Dance

Jonathan Schabowsky from Solace.com focuses on the choreography of stateless event-driven microservices: “Orchestration entails actively controlling all elements and interactions like a conductor directs the musicians of an orchestra, while Choreography entails establishing a pattern or routine that microservices follow as the music plays, without requiring supervision and instructions.” In the decision management world the role of a conductor is usually played by a BPM engine or some kind of ruleflow, while  choreography is implemented with as an event broker when “everything happens in an asynchronous manner, without waiting for a response or worrying about what happens next“. Link
Continue reading

Posted in Architecture, Event-driven, Events, Microservices | Leave a comment

Blockchainizing Existing Databases

In his latest post Bozho wrote: “Blockchain has been a buzzword for the past several years and it hasn’t lived to its promises (yet). Blockchain is largely a shared database. Sharing data with other participants in a given business process in a secure way that doesn’t allow any of the participants to cheat.  There are dozens of blockchain projects, networks, protocols, “standards”, but deploying and integrating a separate blockchain solution is usually a large project in itself and especially in the COVID-19 crisis likely gets postponed because of the questionable return on investment.” From decision management perspective, “blockchainizing” existing databases will feed the perpetually running decision-making systems with new facts coming from various sources in real-time. Link

Posted in Blockchain | Leave a comment