James Gosling retires, Java keeps going strong

== James_Gosling – Wikipedia == Java is strong in 2024 ==

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July-2024 Challenge “Smart Investment”

We’ve just published a new challenge “Smart Investment”: A client of an investment firm has $10,000 available for investment. He has instructed that his money be invested in particular stocks, so that no more than $5,000 is invested in any one stock but at least $1,000 be invested in each stock. He has further instructed the firm to use its current data and invest in the manner that maximizes his overall gain during a one-year period. Link

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Graph Types and Ontological-Driven Data Structures

Joe Hoeller wrote about common misconceptions about graphs and AI: “Graphs are essential in various domains, ranging from computer science to bioinformatics. However, distinguishing between different types of graphs and understanding their unique properties and applications is crucial. This article aims to clarify these distinctions by focusing on Directed Acyclic Graphs (DAGs), Label Property Graphs (LPGs), Bipartate Graphs, and Semantic Knowledge Graphs” Link

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LLMs and Complex Business Problems

David Ferruchi’s new article “Large Language Models Created Demand for AI Capable of Complex Reasoning They Can’t Deliver Alone” explains why a more holistic approach to AI combined with different forms of reasoning is needed to help us make better decisions. David raises a crucial question: How can we ensure the quality of LLMs when solving complex business problems where the outcome needs to be 100% accurate and provide the long chain of precise reasoning steps? LLMs alone do not, and will not, meet this expectation based strictly on how they work. David dives deeper into the very notion of precision, complex reasoning, and step into the fascinating realm of language itself. Link

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DecisionCAMP-2024 Program Announcement

DecisionCAMP is the major annual gathering of practitioners dedicated to Decision Intelligence technologies including Rule Engines, Machine Learning, Optimization, and Generative AIThe Org Committee has just announced a great Program for the 2024 event. Register for free and attend all sessions online.

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How to Introduce Optimization

Prof. Warren B. Powell published a new book “A Modern Approach to Teaching an Introduction to Optimization“. He states: “Optimization should be the science of making the best decisions we canThe vast majority of optimization problems are used to make decisions that arise over time, which means they are sequential decision problems that have to be solved as new information continues to arrive. While he concentrates on the question “We need to modernize how we introduce students to optimization“, many of his observations are valid for bringing the optimization approach and supporting tools to business analysts. Free PDF

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Text to Knowledge Graph

Dan Selman published an article that describes how to convert natural language text to knowledge graphs. Dan extended Concerto Graph by adding a new method mergeTextToGraph which simplifies the conversion of a block of text to a Knowledge Graph ensuring that the structure of the nodes and edges conforms to the Concerto data model that is associated with the Graph Model. All source codes are available and you may try to test it with your own data models. Link

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Progress Towards the Holy Grail

In 1996 Prof. Gene Freuder wrote the paper “In Pursuit of the Holy Grail” proposed that Constraint Programming was well-positioned to pursue the Holy Grail of computer science: the user simply states the problem and the computer solves it. For the last 7 years he runs a series of workshops aims to encourage and disseminate progress towards that goal.

This year workshop will be held on Sep 2. It includes a panel discussion “Have Chatbots Reached the Holy Grail?”. The answer is presumably “no, but”. Why not? What progress do they embody? How can we get closer? Neuro-symbolic, bespoke chatbots, coping with hallucinations, beyond LLMs, … ? If you would like to participate in the panel, submit a PDF containing a one-paragraph position statement – see Link

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Combining Constraint Solvers and LLMs


David Ferrucci: “Ever wondered how AI can tackle complex enterprise problems with precision and reliability? By combining constraint solvers and LLMs, we can turn natural language into actionable knowledge that drives intelligent applications. This approach ensures that our solutions are not only mathematically precise but also interactive and collaborative.

From acquiring business knowledge to using it to drive problem-solving applications, we bridge the gap between language fluency and precise reasoning. Link

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Supply Chain => Decision Intelligence 

Niels van Hove: “Decision Intelligence is a natural evolution in Supply Chain planning & execution technology”

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