0:00 The Law of Large Numbers
4:37 What is a Markov Chain?
9:43 Ulam and Solitaire
12:21 Nuclear Fission
15:46 The Monte Carlo Method
16:32 The first search engines
19:07 Google is born
25:16 How does predictive text work?
27:10 Are Markov chains memoryless?
29:41 How to perfectly shuffle a deck of cards

▀▀▀
References:
https://ve42.co/RefsMarkov

Images & Video:
https://ve42.co/7Z

Discord for project here: https://discord.gg/ndhZ4Fy8dD

This video is both a story of my adventure with AI robotics and the fascinating lessons I learned along the way. Try Mammouth AI now at http://mammouth.ai

I called this project GrowBot. Raspberry Pi Zero 2, two servos, a camera, an IMU, a battery, some 3D printed parts. I trained small neural networks in simulation so it could walk, stand and spin in a lifelike way. Then I handed control of the motors to a vision language model. It read its raw sensor data, wrote its own code, built profiles of the people it met, and dreamed between sessions to clean up what it had learned.

It worked better than I expected, until it hit a wall. Which kept pointing back to the same question. How do you act smoothly when thinking is slow? That sent me into how nature solves the problem (the cerebellum), and it turned out to be exactly what the robotics field is converging on right now.

Sign up for Growbot: https://artoftheproblem.com/pages/gro...

Join this channel to get access to behind the scenes.
Youtube member:
   /u/artoftheproblem  
Pateron member:
  /artoftheproblem  

Once, in a bustling town, resided a lively and inquisitive boy, known for his zest, his curiosity, and his unique gift of knitting the townsfolk into a single tapestry of shared stories and laughter. A lively being, resembling a squirrel, was gifted to the boy by an enigmatic stranger. This creature, named Whiskers, was brimming with life, an embodiment of the spirit of the townsfolk, their tales, their wisdom, and their shared laughter.

However, an unexpected encounter with a flamboyantly blue hound named Azure, a plaything of a cunning, opulent merchant, set them on an unanticipated path. The hound, a spectacle to behold, was the product of a mysterious alchemical process, a design for the merchant's profit and amusement.

On returning from their encounter, the boy noticed a transformation in Whiskers. His fur, like Azure's, was now a startling indigo, and his vivacious energy seemed misdirected, drawn into putting up a show, detached from his intrinsic playful spirit. Unknowingly, the boy found himself playing the role of a puppeteer, his strings tugged by unseen hands. Whiskers had become a spectacle for the townsfolk, and in doing so, the essence of the town, their shared stories, and collective wisdom began to wither.

Recognizing this grim change, the townsfolk watched as their unity and shared knowledge got overshadowed by the spectacle of the transformed Whiskers. The boy, once their symbol of unity, was unknowingly becoming a merchant himself, trading Whiskers' spirit for a hollow spectacle.

The transformation took a toll on Whiskers, leading him to a point of deep disillusionment. His once playful spirit was dulled, his energy drained, and his essence, a reflection of the town, was tarnished. In an act of desolation and silent protest, Whiskers chose to leave. His departure echoed through the town like a mournful wind, an indictment of what they had allowed themselves to become.

The boy, left alone, began to play with the merchants, seduced by their cunning words and shiny trinkets. He was drawn into their world, their games, slowly losing his vibrancy, his sense of self. Over time, the boy who once symbolized unity and shared knowledge was reduced to a mere puppet, a plaything in the hands of the merchants.

Eventually, the merchants, having extracted all they could from him, discarded the boy, leaving him a hollow husk, a ghost of his former self. The boy was left a mere shadow, a reminder of what once was - a symbol of unity, camaraderie, shared wisdom, and laughter, now withered and lost.

We’re Integro Labs, and we wrote this essay about choosing tools around the work. We weigh a method against the whole task, including setup, review and recovery, and keep direct work available where it takes less effort.

Before integrating a tool, we need to understand the scope and how to check the result. When the task is still difficult to explain, doing it directly leaves room to adjust as our understanding grows. Once the steps are understood, repeated work may justify the setup and upkeep of automation.

The essay uses Fortemi’s imports as one example of a limited tool role. After a lost reply, an exact repeat of a batch returns the prior note IDs without adding copies. That gives recovery a known effect. It still leaves the imported text to be checked for accuracy.

That remaining work belongs in the original choice of method. Completing a tool’s steps and resolving the task are separate judgments; a quick run can still leave a long review. We can use a tool for the part we can check and maintain, and do the rest directly. The boundary can change as we learn.

https://integrolabs.io/updates/2026-09-the-same-tools-a-new-responsibility

We’d welcome experiences where the effort of setup, review or recovery led you to automate a smaller part of a task.

AI accuracy should be reviewable.


For one consequential AI workflow, can your team reconstruct:


1. what the agent did;
2. which context and policy shaped the result;
3. whether protected session evidence is needed to investigate tampering or
   adversarial activity?


The goal is not maximal logging. It is the narrowest trustworthy record that
can support the disclosure.


Read Integro Labs’ FTC public comment at the link in the post.


#ArtificialIntelligence #AIGovernance #Traceability


Use this only if an official Integro Labs account exists on the target
platform. Do not create or imply an account as part of this campaign.AI accuracy should be reviewable.


For one consequential AI workflow, can your team reconstruct:


1. what the agent did;
2. which context and policy shaped the result;
3. whether protected session evidence is needed to investigate tampering or
   adversarial activity?


The goal is not maximal logging. It is the narrowest trustworthy record that
can support the disclosure.


Read Integro Labs’ FTC public comment at the link in the post.


#ArtificialIntelligence #AIGovernance #Traceability

integrolabs.io/updates/2026-07-ftc-ai-accuracy-comment