The Black Belt Of Digital Decisions

In Jan-2017 Mike Gualtieri from Forrester published a report “Prescriptive Analytics: The Black Belt Of Digital Decisions” which tied Analytics to actionable Decisions. Mike wrote: “Enterprises must stop wasting time and money on unactionable analytics. These efforts don’t matter if the resulting analytics don’t lead to better insights and decisions that are specifically linked to measurable business outcomes.” Since then the term “prescriptive analytics” was replaced with “Decision Intelligence” but the listed technologies became even more important today:

  • Descriptive analytics: enables analytics users within an enterprise to query data integrated from multiple applications
  • Predictive analytics: creates predictive models
  • Streaming analytics: detects events and patterns in real-time streams of data
  • Search and knowledge discovery: leads to insights, and insights lead to knowledge
  • Simulation: imitates a real-world process or system over time using a computer model
  • Mathematical optimization: the process of finding the optimal solution to a problem that has numerically expressed constraints
  • Machine learning: identify patterns or make predictions by analyzing historical data that is representative of the domain
  • Pragmatic AI: continuously learn from new information, build knowledge, and then use that knowledge to make decisions and interact with people and/or other machines. LINK
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Challenge July-2023 “Rules as Preferences”

In the real world not all rules can be satisfied and we may consider them as preferences. For example, our June-2023 Challenge “Miss Manners” used well-tuned data with equal numbers of males and females at each party. Of course, real data is not like this, but we still want to help Miss Manners to seat all guests while sticking to her rules as much as possible. So, the seating arrangement “boy-girl-boy-girl and each guest has someone on the left or right with a common hobby” becomes not a Rule but a Preference. Let’s see how modern decision intelligence tools can address this advanced version of the notorious “Miss Manners” benchmark. Link

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What’s New in DMN 1.4 and 1.5

Bruce Silver published the latest news in the DMN standard including:

  • New FEEL Functions: STRING JOIN(), CONTEXT PUT(), NOW() AND TODAY(), NEW ROUNDING FUNCTIONS
  • New Boxed Expressions: FILTER, CONDITIONAL, ITERATOR
  • DRD Changes
  • Other: Import into the Default Namespace, Allowed Values and Unary Tests, list replace(), Scientific Notation

Link

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DecisionCAMP-2023 Program has been Published

DecisionCAMP-2023 Program and Schedule are now available! This major annual Decision Management event will feature 19 interesting presentations from well-known and new presenters in the area of Decision Intelligence. They will cover many hot topics such as the common use of LLM and Rule Engines, Declarative Decision Modeling, Decision Testing and Explanations, Knowledge Representation, Decision Optimization, and real-world use cases. You may register for free now. Link

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Fake court citations from ChatGPT

The Guardian: Two US lawyers fined for submitting fake court citations from ChatGPT. A law firm also penalized after chatbot invented six legal cases that were then used in an aviation injury claim. Link

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Business Rules Manifesto – 20th Anniversary

Business Rules Manifesto is 20 years old and “it is as fresh as the day it was written. Only 2 pages, free, and translated into 18 languages, the Business Rules Manifesto ushered in a whole new way of thinking about business problems and automated solutions. With the emerging need for AI guardrails, as well as now a far more mature view of agile, more relevant than ever,” – says Ron Ross. Link

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Towards Programming as Conversation

With LLMs taking the world, the prediction “What comes after serverless? Conversational Programming!” becomes a reality. It is interesting that even in 1967 Marvin Minsky understood the possibility of a 2-way conversation between programmer and computer, where the program is written in collaboration:

Link

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About LLM Reasoning and Planning Abilities

Today Yann LeCun wrote: “Auto-regressive LLM have very limited reasoning and planning abilities. I do not believe we can get anywhere close to human-level AI (even cat-level AI) without (1) learning world models from sensory inputs like video, (2) an architecture that can reason and plan (not just auto-regress). Now, if we have architectures that can plan, they will be objective driven: their planning will work by optimizing a set of objectives at inference time (not just training time). These objectives can include guardrails that will make those system safe and subservient even if they end up having much better world models that humans. Then, the problem becomes to design (or train) good objectives functions that will guarantee safety and efficiency. It’s a hard engineering problem, but not as hard as some have made it to be.Link

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Combining LLM with Traditional Coding

A project lead of Google Bard just announced that “Bard is improving at mathematical tasks, coding questions and string manipulation through a new technique called implicit code execution. Plus, it has a new export action to Google Sheets… With this latest update, we’ve combined the capabilities of both LLMs (System 1) and traditional code (System 2) to help improve accuracy in Bard’s responses.” Link

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What AI is, isn’t, and could be

Marc Andreessen wrote: “What AI is: The application of mathematics and software code to teach computers how to understand, synthesize, and generate knowledge in ways similar to how people do it. AI is a computer program like any other – it runs, takes input, processes, and generates output. AI’s output is useful across a wide range of fields, ranging from coding to medicine to law to the creative arts. It is owned by people and controlled by people, like any other technology.

What AI isn’t: Killer software and robots that will spring to life and decide to murder the human race or otherwise ruin everything, like you see in the movies.

What AI could be: A way to make everything we care about better.” Link

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