Alan Trefler: The Big RPA Bubble

Alan Trefler, the Founder and CEO of Pegasystems, just published an article about Robotic Process Automation (RPA). “It’s the hot topic among the C-Suite. Where to implement. How to implement. How many headcount can be saved through robotic implementations. Business leaders want robots – powered by AI – to drive automation into every mundane task people now do … but there’s a lot of misinformation and misunderstanding about what bots can and can’t do for an organization.” Link Continue reading

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Decision-Centric RPA

Arash Aghlara compares traditional Robotic Process Automation (RPA) with decision-centric RPA when both robots and staff share the logic for repetitive operational business decisions. “Enabling robots to make such decisions is not about technologies like AI, Machine Learning, Neural Networks, Predictive Analytics, etc. at all. Operational business decisions are a routine part of day-to-day jobs. Staff make decisions day in and day out while performing tasks and activities related to their jobs. Decision-Centric RPA enables robots to make decisions and follow business rules without introducing technical debt to organisations.” Link

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Decisioning Challenges of Driverless Cars

It is a lot harder to make an autonomous car than to sell the idea to AI-obsessed audiences. Christian Wolmar, the British author and broadcaster, said in this interview: “This is a fantasy that has not been thought through, and is being promoted by technology and auto manufacturers because tech companies have vast amounts of footloose capital they don’t know what to do with, and auto manufacturers are terrified they’re not on board with the new big thing,” he said. “So billions are being spent developing technology that nobody has asked for, that will not be practical, and that will have many damaging effects.” Whatever our expectations/ believes are, we cannot ignore the discussed challenges. From the DM perspective, there is a “decision processing system” within the driver’s brain and/or within the car’s “brain” and our decisioning techniques should be ready to handle the problems discussed in this interview and its 235 comments. Link

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Machine Learning Applied: China vs. US

In this MIT Technology Review “Tech companies should stop pretending AI won’t destroy jobs” Kai-Fu Lee gives several reasons why China will have at least a 50/50 chance of winning the AI race: 1) China has a huge army of young people coming into AI; 2) China has more data than the US—way more. Data is what makes AI go. A very good scientist with a ton of data will beat a super scientist with a modest amount of data; 3) Chinese AI companies have passed the copycat phase; 4) The Chinese government’s stated plan is to catch up with the US on AI technology and applications by 2020 and to become a global AI innovation hub by 2030. Read more

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Decision Optimization for Dynamic Pricing

FICO posted an interesting article “Fair Pricing with Price Optimisation”. A similar system “Using Machine Learning, Business Rules, and Optimization for Flash Sale Pricing” has been developed by OpenRules.  These examples demonstrate the power and flexibility of Decision Optimization when business rules, machine learning and optimization tools are used together. Constraint and Linear Solvers can bring an additional power to more traditional DMN-like settings. Decision Optimization can be used to identify not just the best price, but the best associated offer or product structure to meet the customer expectations. Powerful tools are available that can overlay blended optimization strategies relating to product, pricing, marketing, and other decisions.

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Decision Intelligence Seminar: February 5, 2019 in Belgium

KU Leuven University, our newest sponsor, is one of the leading European universities with strong research commitment to Business Decision Analytics. On Feb. 5, 2019 it will run the Decision Intelligence Seminar organized by consortium of senior researchers from the Faculty of Engineering, the Faculty of Engineering Technology and the Faculty of Economics and Business of KU Leuven university. In the seminar, reputed academic speakers will present the current state-of-the-art in decision  management methodology and technology, while international business speakers discuss their experiences with decision intelligence in banking, manufacturing, HR, insurance and governance.

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Progress in Natural Language Processing

In August, researchers from the Allen Institute for Artificial Intelligence, a lab based in Seattle, unveiled an English test for computers. It examined whether machines could complete sentences. In October Google researchers unveiled a a new language representation model called Bert. These new language systems learn by analyzing millions of sentences written by humans. A system built by an OpenAI lab analyzed thousands of self-published books, including romance novels, science fiction and more. Google’s Bert analyzed these same books plus the length and breadth of Wikipedia. Read more

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