Realising Decision Intelligence with neurosymbolic Rainbird


Decision Intelligence & Neurosymbolic AI –
A guide for leaders

Dr. Lorien Pratt’s 2008 vision of “Decision Intelligence” has come to fruition with Rainbird’s emerging neurosymbolic capabilities. This joint whitepaper, with Rainbird co-founders James Duez and Ben Taylor, explores the potential of neurosymbolic AI delivering Decision Intelligence.

Abstract

The last 12 months have seen significant breakthroughs in the advancement of AI.

This paper explains the potential of Decision Intelligence and Neurosymbolic AI in maximising the value that can be extracted from AI today in the pursuit of digital transformation, while minimising risks. 

It addresses key questions and concerns being voiced by leaders about the use of these technologies. In particular, in the context of Large Language Models (LLMs) like GPT-4, which are powerful creators of generated content but lack reasoning, logic and explainability.  

We introduce a neurosymbolic approach, which integrates extended knowledge graphs, LLMs and neural networks to deliver the combined strengths of these technologies while avoiding their weaknesses. It discusses the ability of this composite approach to address the limitations of current AI with a focus on improving explainability, reliability and trust. 

We highlight the benefits of Neurosymbolic AI, including its ability to handle the decision complexity that is more typical of current enterprise demands, reduced data requirements in a world that has had a saturated “data first” mindset, and provide transparency and explainability where governments are making a concerted effort to introduce greater governance obligations to protect the population at large.

Finally, we outline Rainbird’s specific AI lifecycle. This includes the steps of; building models from documentation and expertise, refining them with data, testing and deploying them, interacting with them in natural language, and ensuring they learn from experience. 

Decision Intelligence Webinar


James & Ben are joined by the co-inventor of Decision Intelligence, Dr Lorien Pratt, as they discuss DI, trust in AI & how Fraud can positively impact fraud detection.

In this webinar, we will cover

  • An introduction to Decision Intelligence
  • Client success story in Fraud
  • How companies can use DI
  • The Rainbird engine

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Processing Natural Language


This demo will cover:

  • How a Rainbird model understands eligibility for gadget insurance and can be asked a natural language question with fuzzy data
  • Processing a query correctly with a full evidence-based chain of reasoning
  • Turning explanation back into natural language for inclusion in a report

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R&D Tax


This demo will cover:

  • Using documentation and knowledge of tax experts to build an R&D system
  • How to connect to a workflow
  • How to analyse multiple organisations
  • How to generate evidence-based reasoning for every outcome

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Financial Fraud


This demo will cover:

  • Using documentation and knowledge of fraud experts to build a fraud system
  • How to connect to a workflow
  • How to analyse multiple accounts
  • How to generate evidence-based reasoning for every outcome

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AI Roadmaps, Which Tools to Use, Making the Case for AI, Training, and Building GPTs


Welcome to Episode 150 of The Artificial Intelligence Show—a special milestone that marks the launch of a brand-new series: AI Answers. In this episode, Paul Roetzer is joined by Cathy McPhillips to debut a fresh format to systematically answer the best questions we get during our live AI education sessions.

Over the past few years, our free Intro to AI and Scaling AI classes have attracted more than 32,000 learners—and they’ve asked hundreds of smart, tough, practical questions. This new series tackles them head-on. Continue reading “AI Roadmaps, Which Tools to Use, Making the Case for AI, Training, and Building GPTs”