According to research firm IDC, “Decision intelligence is the missing piece of an organization’s technology stack, giving users the insights they need to make the best decisions with the best possible outcomes. This technology will change how information is synthesized, insights are developed, and decisions are made at scale.” Link
OpenAI CEO, Sam Altman, says further progress will not come from making LLMs bigger. “I think we’re at the end of the era where it’s going to be these, like, giant, giant models,” he told an audience at an event held at MIT late last week. “We’ll make them better in other ways.” Altman’s declaration suggests an unexpected twist in the race to develop and deploy new AI algorithms. Link
Ben Evans: “We’ve had ChatGPT for 18 months, but what’s it for? What are the use-cases? Why isn’t it useful for everyone, right now? Do Large Language Models become universal tools that can do ‘any’ task, or do we wrap them in single-purpose apps, and build thousands of new companies around that?” “One upon a time every startup had SQL inside, but that wasn’t the product, and now every startup will have LLMs inside.” Link
Sparkling Logic announced the launch of AI Assistant, that leverages a large language model (LLM) form of generative AI pre-trained on various decision management tasks. Users will be able to interact with AI Assistant using natural language to create and modify project assets such as data, decision flows, and business rules and generate easy-to-understand explanations for decision logic outcomes. Link
Sapiens Decision new copilot ModelAI leverages GenAI to automatically convert natural language to decision models allowing business users to increase the access, speed, and efficacy of decision automation. Link
LocalSolver has been renamed to Hexaly which claims to be the world’s fastest optimization solver for Routing, Scheduling, and Packing problems. Link
Check out also Timefold solver that handles the same problems and now inherited OptaPlanner after Red Hat announced its End of Life. Link
Jim Sinur: “All of the art for the first quarter resulted from experiments with Gen AI. I used Kaiber for the videos and Microsoft Image Creator. I started the videos with the following images to give the AI tool a starting point and a storyboard to tell the story of each song. Overall, I liked the experience as an artist, but it won’t keep me from doing art by hand or fractals, which also require computer assistance. Here are the art pieces for each song in the order they are on the album.” Link
This was written today by Cassie Kozyrkov, Google’s first Chief Decision Scientist. “Can we calm down, please? AI is just another approach to automation. Automation is not new and it’s not ‘solved‘… I understand the AI disillusionment that’s been creeping up recently. People have been promised magic, but LLMs are still just a tool! They can drive incredible results *and* they are imperfect tools that need a lot more work... Consumers are smart. They want things that actually solve problems. Technology is cool, but the industry wins when products are built to solve specific problems for specific people.” Link
In 1960, the famed computer scientist Don Knuth wrote a technical paper in which he considered an integer programming model for minimizing memory access latency of an IBM 650. It included 51 variables and 43 constraints. Knuth ran Gomory’s algorithm on an IBM 650 with less than 10K of memory, but was unable to find an optimal solution. In 1995 Dimitris Alevras successfully found the optimum value of 22,996 using CPLEX on a SPARCstation 5 and it took hours. These days open source MIP solvers are able to find an optimal solution in tenths of a second. Link
Gartner predicts that by 2028, 25% of chief data and analytics officer vision statements will become “decision-centric”, surpassing “data-driven” slogans, as human decision-making behaviors are modeled to improve Data &Analytics value. Link
Arash Aghlara goes further suggesting that Data & Analytics leaders should STOP thinking about “data” and “analytics” altogether. Link
Harshil Patel describes how to align Data-Driven and Decision-Centric approaches using Machine Learning. Link
Richard Susskind writes “about the use of AI to draft legislation and regulation and then to generate legal rules in the form of executable code.” He states that AI will draft complex legislations within five years and new tools will make breaking the law harder.” Link
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