Business Orchestration and Automation Technologies (BOAT)

Enterprise application leaders often struggle to implement process automation technologies due to the lack of a unified architecture. RPA, BPA, and other platforms are quite overlapping, most business automation vendors are working toward a general-purpose automation platform built around orchestration, connectivity and AI. Gartner calls this emerging platform the BOAT –  Business Orchestration and Automation Technologies. Join this complimentary webinar as a Gartner expert explores the new BOAT software platform. Link

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Safe Superintelligence

OpenAI co-founder Ilya Sutskever’s new venture, Safe Superintelligence, secures $1 billion for safe AI. “Building safe superintelligence (SSI) is the most important technical problem of our​​ time. We have started the world’s first straight-shot SSI lab, with one goal and one product: a safe superintelligence. It’s called Safe Superintelligence Inc. SSI is our mission, our name, and our entire product roadmap, because it is our sole focus. Our team, investors, and business model are all aligned to achieve SSI. We approach safety and capabilities in tandem, as technical problems to be solved through revolutionary engineering and scientific breakthroughs. We plan to advance capabilities as fast as possible while making sure our safety always remains ahead.” Link

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Have Chatbots Reached the Holy Grail?

On Sep 2, 2024 Prof Gene Freuder will run The Seventh Workshop on Progress Towards the Holy Grail. It will include the panel “Have Chatbots Reached the Holy Grail?”. You can read answers of 3 experts in constraint programming here. Similarly to many other decision intelligence experts, the common point of view about LLM capabilities is summarized by Thomas Schiex: “I believe that modern AI needs a more nuanced approach, blending data-driven intuition (System 1) with rigorous logical reasoning and planning (System 2). This integration is essential to get closer to what we usually recognize as intelligence. This could take some time.Link

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“DI is AI for Decisions”

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James Gosling about GenAI

James Gosling, the Father of Java, offers a thought-provoking critique on the GenAI hype, highlighting both its potential and the risks of overestimating its capabilities. Link

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IBM AI Roadmap for the next few years

Armand Ruiz, VP of Product – AI Platform @IBM, describes what is coming:

  • 2024: Build Modular and Multimodal Transformers for New Enterprise Applications
  • 2025: Alter the Scaling of Generative AI with Neural Architectures Beyond Transformers
  • 2026: Bring Robust Strategic Reasoning and Commonsense Knowledge to AI
  • 2028: Develop Broadly Intelligent Agents That Learn Autonomously
  • 2030+: Build Adaptable and Generalist AI for Effective Human-Machine Collaboration

“Beyond 2030, we aim to create adaptable and generalist AI that can collaborate effectively with humans. These AI models will be composed of modules with different cognitive abilities—such as perception, memory, emotion, reasoning, and action—allowing them to exhibit behavioral norms for social interactions and mutual theory of mind.” Link

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Gartner’s Definition of “Open Systems”

David Pidsley, The Decision Strategist at Gartner wrote: By “open” we’re referring to an open systems computing design pattern that allows for easy integration with other tools and platforms, often through well-documented APIs and standard protocols. Open systems provide some combination of interoperability, portability, and open software standards. This may but isn’t necessarily open source (with permission to use, copy and distribute it, either as is or with modifications, and that may be offered either free or with a charge – i.e. where the source code must be made available). Link

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Decision Model as Approximation for Business Problem

Carlos Armando Zetina: “The model is an approximation for a business’s decision problem because it inevitably needs to make simplifying assumptions such as limited scope, finite horizons, deterministic parameters, and cost approximations to be amenable to solving. Since the optimality gap is a measure based on the model, using it to measure a solution’s success is misleading.

What matters to the business is its Key Performance Indicators (KPIs) e.g. out of stock, actual transportation costs, lead times, revenue, profit margins and other KPIs the solution can directly impact. These KPIs should be tracked continuously before and after the optimization solution is in production, guiding model adjustments to make decisions that align better with the ultimate business goals. Optimization solutions in industry are living entities that require continuous improvement and KPI monitoring. Solving the model is only the beginning of the decision science process.” Link

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Solutions for July-2024 Challenge “Smart Investment”

We received 9 solutions for our July-2024 Challenge “Smart Investment”.
Used decision optimization tools:
IBM CPLEX
Llama3/CPLEX/watsonx
Corticon
Prolog
ChatGPT/Zimpl
IPython/ortools
cDMN
Excel Solver
OpenRules Rule Solver.

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Problem-solve with your peers

Gartner distributed a nicely formulated email: “Where is your next great idea going to come from? With an industry and role that is constantly evolving, some of the greatest insights you can get are from your peers.” It is true for several upcoming conferences such as:

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