When most people see a volatile time series, they think it’s random. But chaos and randomness are not the same. Chaos has structure – sensitive to initial conditions, and governed by deterministic laws. What if we could map time series data onto a chaotic system and let its internal dynamics do the forecasting? In this…

Traditional machine learning models are built to generalize. And while that works well in many cases, it’s also their Achilles‘ heel, they often miss the sharp edges, the anomalies, the rare patterns that matter most. But transformers changed the game. In this post, I introduce a new mental model for understanding attention: the 3D similarity…

Fuzzy Cognitive Maps (FCMs) are powerful tools for modeling systems where variables influence each other in complex, uncertain ways. Traditionally, building them requires domain experts, people with deep knowledge of how concepts interact. But what if we could replace these experts with language model agents? Multi-Agent System powered by Large Language Models (LLMs) can autonomously…

Fuzzy logic has long offered an elegant framework for reasoning under uncertainty – but designing good fuzzy systems has remained more of an art than a science. What if we could automate the design of fuzzy systems, make their internals differentiable, and even train them via gradient descent? 1. Automatic Generation of Membership Functions Instead…

1. We Are Not Born to Serve Markets We are not consumers. We are not units of labor. We are sentient, creative beings – capable of love, wonder, and transformation. A system that reduces us to our purchasing power, productivity, or profit is not a civilization. It’s a cage with LED lights. We outgrew the…

My journey to automatically generate fuzzy rules for a fuzzy engine led me to frequency-based algorithms like Apriori and FP-Growth.As I tried to understand how they work, I began to wonder if it would be possible to write a simple classifier based purely on support values. When all features in a dataset are one-hot encoded,…

In the previous parts of this series, we explored key innovations that could reshape computing: Now, let’s take a bold step forward and envision what all these technologies combined could lead to a Star Trek-like future where computing becomes instantaneous, intelligent, and seamlessly integrated into every aspect of life. The End of Waiting: A World…

Transforming CPUs into Lookup Engines with Quantum Communication In our previous discussions, we explored how local result caches using CAM memory could eliminate redundant computations at the device level. Now, we’re taking a bold leap into the future with the concept of a global result cache – a vast, distributed registry where computed results are…

In our journey toward more efficient computing, we’ve recognized that a significant amount of energy is spent on redundant tasks. Modern CPUs often perform the same calculations repeatedly—whether across different threads, processes, or even different devices in distributed systems. This redundancy isn’t just a performance bottleneck; it also contributes to the massive energy consumption we…

In today’s computing landscape, performance often hinges on how quickly we can locate data. Whether it’s checking if an element exists in an array, searching through a list, or performing complex lookups in vast databases, much of our processing power is dedicated to finding the right piece of information. This challenge has led to the…