AI is not coming for your job.
Your CEO is!
AI is not coming for your job.
Your CEO is!
βAlan M. Turing thought about criteria to settle the question of whether Machines Can Think, a question of which we now know that it is about as relevant as the question of whether Submarines Can Swim.β - Edsger W. Dijkstra.
This is especially applicable to LLMs
Our latest video from The Complexity Lounge has been posted with Carlos Gershenson - Balance: A Narrative for Complexity: www.youtube.com/watch?v=Bp5a...
Let's discuss why LLM's are incapable of true agentic behavior beyond a very simple use cases, due to their foundational structure. This video might get us started: www.youtube.com/watch?v=uyOR...
Why do we keep seeing the same tired old meme spewed about that we need AI to solve Climate Change? We have known for over 30 years EXACTLY what we need to do. If anything, the current manifestation of AI (LLMs), CONTRIBUTES to climate change. *sigh*
I suggest that you continually remind yourself as you watch with wonder, curiosity, and excitement each and every daily AI advancement, this one thing - If it can be militarized, it will be militarized (assume they are working on it now).
I am surprised, and slightly disappointed, that one of these YouTube AI influencer/experts hasn't demo'd their latest "benchmark" that tests creating a Snake game that books a trip for you, while navigating a brutalist cityscape and solving Rubik cube shaped buildings. Gimmee, gimmeee!
I have seen a 10x increase in unsubstantiated claims of some 10x increase in a random, vague, "improvement". It's a 10x increase in the level of absurdity. (10x is a very large number, should stop you dead in your tracks, and elicit an immediate response of "show me the data")
So what do you think is primarily driving AI, from the POV of workers: FOMO or FOBLO (Fear of Being Laid Off)?
"So from an executive perspective, lighting comically large piles of money on fire trying to teach graphics cards how to read is, surprisingly, the logical play. The rest, well, thatβs all just creative marketing."
-- Marcus Hutchins
#AI
malwaretech.com/2025/08/ever...
There are many sources that contribute to friction. I seldom use the term tech debt, unless it is...tech debt :)
Everyone is constantly talking about "changing the culture". This is fruitless. How about we work on "developing and nurturing the culture" instead. You cannot buy that. It takes stability, commitment, hard work, and a very long time.
Machines (or #AI) cannot #kaizen. Only people can kaizen. Humans MUST remain in the loop!
For those feeling a sense of despair in these troubled times, I can only respond with the following. I hope this helps: www.youtube.com/watch?v=U9zO...
"It wouldn't be real novelty, if we could predict (the outcome)" - @AliciaJuarrero
Addendum: If Senior Leadership are not applying these principles to their own work, it follows that Lean, Agile and kaizen will become primarily about compliance.
As soon as Lean, Agile, or Kaizen, becomes primarily about compliance - it is dead.
Agile Coaching tips from the 23rd century: www.youtube.com/watch?v=QxuJ... #AgileCoachTips #PsychologicalSafety
"Improvement efforts are often misguided since they are aimed at achieving cost savings rather than focusing on improving flow." β Eli Goldratt #Flow
If you replaced 'Theseus Ship' with 'Theseus' Axe', would it still be the same metaphor?
Contrary to the oft mis-attributed Einstein quote, in socially complex systems (open systems), "insanity" is doing the same thing over and over and expecting the SAME result! #Complexity
For fair selection everybody has to take the same exam: Please climb that tree. #context
Venn Diagrams are spherical cows.
Check out our latest talk with Dave Snowden at The Complexity Lounge! www.youtube.com/watch?v=WFJ5...
At the root of every queue (or bottleneck) lies a prior decision and the resultant behaviors. Queues don't create themselves. Experiment. Learn.
The concept of βShu Ha Riβ is itself a βShuβ way of thinking. In βRiβ, there is no βShu Ha Riβ.
Agree. I am focusing more on how the question is asked, which will determine whether the data that is captured is useful or not.
I am not crapping on them, I am just pointing out that they need to be used more thoughtfully if you expect them to inform your decision-making. They often assume a shared context that is either assumed, or that doesnβt exist.
Thatβs very cunning of you (answering a question with a question). Which one did you choose? #context
(On a scale of 1-5) - Likert Scales are: Mostly Useless, Somewhat Useless, Maybe, Somewhat Delicious, Mostly Delicious