A call for AI substance not for more hype

Today Stéphane Dalbera posted such a call: “… in the case of LLMs, too often the discourse remains high-level and aspirational. Demos abound, wow effect, but operational insights remain scarce. For a field that claims to redefine productivity, creativity, and even human reasoning itself, the lack of grounded, transparent, and reproducible narratives is troubling.” Interesting quotes provided in comments by Vincent Lextrait: Link

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“Decision Intelligence is AI for Grownups”

This phrase is often used to highlight how Decision Intelligence (DI) represents a more mature, pragmatic, and business-focused application of artificial intelligence. I asked Copilot why some people describe DI that way. See the answers at https://www.linkedin.com/feed/update/urn:li:activity:7352416233801060352/

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Is what photography did to painting similar to what AI does to software development? 

Google this question and see different answers. “This industry, by invading the territory of art, has become art’s most mortal enemy.” Was this quote said in 1859 about photography by Charles Baudelaire or in 2025 about AI art by somebody else? Read “Photography was historically considered art’s most mortal enemy. Is AI?” by Lizzy Larson.

One of the answers was published yesterday by a fine art photographer, Craig Boehman, and is called “In Defense of AI Art: History Repeats Itself, Again, Again, and Again“: The “anyone can do it” and “it will put people out of work” arguments. And has painting been superseded by photography? What nonsense. Check the auction houses. Paintings go for hundreds of millions of dollars and a mere photo has yet to reach 10 million. And there are very few cases of photos being valued this high. Naturally, value isn’t the only way to judge an art form. But there is no evidence whatsoever that photography has overtaken painting.

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The Rise of Small Language Models (SLMs)

Specialized small language models (SLMs) can outperform large, generalist models. Want to learn how? Read Armand Ruiz’s post on LinkedIn: “Inference is cheaper. Iteration is faster. Fine-tuning takes hours, not weeks. SLMs can run locally, privately, and securely and no datacenter needed“. See the related research paper stating that “SLMs are sufficiently powerful, inherently more suitable, and necessarily more economical for many invocations in agentic systems, and are therefore the future of agentic AI“.

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Smart orgs don’t chase models.They build decision systems.

This is a quote from Adam DeJans Jr. It is right to the point and should be shown completely: “Most AI systems can tell you what happened. Very few can tell you why. And almost none can tell you what to do next.

Yet we keep handing over high-stakes decisions (hiring, sentencing, pricing, credit scoring) to algorithms built to detect patterns, not understand them.

Here’s the problem:

AI is great at perception (seeing, hearing, translating), but in prediction tasks involving humans, the cracks start to show.

What people forget is that:
→ Accuracy ≠ value
→ A forecast ≠ a decision
→ Probabilities ≠ understanding
→ Correlation ≠ causation

If you’re using AI to replace judgment rather than support it, you’re not modern, you’re reckless.

Smart orgs don’t chase models. They build decision systems.
Link

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AI Aphorisms

Bruno Levy decided to share short sentences related to the conditions of possibility for AI reasoning and human-AI collaboration. Here is his first aphorism:

True reasoning is not a function of knowing everything, but a function of being structurally immune to believing the wrong thing.” Link

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AI ethics: Your face is not public domain

According to this LinkedIn post, “Denmark is about to make that official. Under a new amendment to the copyright law, the Danish government will give people the legal right to their own voice, face, and body – even when they’re digitally reproduced by generative AI. A deepfake of you will no longer be “just pixels.” It will be your protected identity.Link

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Challenge July-2025 “Rules with Regular Expressions”

This challenge gives vendors of different rules-based tools an opportunity to demonstrate how they handle business rules with regular expressions. They need to implement business rules such as below:

  • If the Degree Code is “MA Single” and the Course Code is similar to MA52# or MA62#, where # stands for any single character, add this course to the list of allowed courses.
  • If the Degree Code is not “CS%” and the Course Code is similar to CS%288% or CS%289%, where % stands for any combination of characters, add this course to the list of not allowed courses. Link
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Decision-Making Under Uncertainty

Uncertainty is the environment in which our decision models frequently operate. What drives real decisions under real uncertainty? Adam DeJans Jr. unpacks why most “optimization” efforts fail under real-world uncertainty in the 5-part mini-series:

Optimization under uncertainty needs to be embedded within your business as a living system. Its success is measured not by solver convergence or benchmark accuracy, but by decisions that consistently align operational realities with financial objectives under real-world volatility.

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Becoming an expert in AI

Source: https://shorturl.at/CyOPK

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