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13 contributions to Data Alchemy
Most data problems aren’t technical — they’re conceptual
When something breaks, teams usually blame: the dashboard, the pipeline, or the model. But most data problems start much earlier. They start with unclear thinking. If you don’t know what decision the data is meant to support, no amount of cleaning or modeling will save you. The best data teams work in this order: 1. Define the decision that matters 2. Identify the signal that influences it 3. Ignore everything else That’s the core of data alchemy. Not collecting everything . Not modeling everything. But reducing complexity until truth appears. AI makes computation cheap. Clarity is still expensive. And that’s why good judgment — not better tooling —remains the true edge in intelligent systems.
1 like • 3d
great perspective
“AI doesn’t replace human intuition — it validates it.”
There’s a quiet misconception in every data conversation right now: that AI is here to replace human decision-making. But in reality —AI is here to prove intuition right (or wrong) faster. Think about it 👇Every bold idea starts as a hunch. Before AI, testing that hunch took weeks or months. Now, you can simulate it in hours. That’s not replacement — that’s amplification. The smartest teams aren’t “data-driven". ”They’re intuition-driven and data-validated". That’s the new equilibrium: Humans generate insight. Ai verifies it at scale. It’s not man vs machine. It’s instinct + intelligence = speed
0 likes • 17d
AI doesn’t replace intuition
“Insight isn’t found — it’s designed.”
People talk about “finding insights” in their data as if it’s a treasure hunt. But real insight doesn’t just appear — it’s engineered. Every valuable data insight starts with a great question. - What are we really trying to understand? - What variable actually drives this outcome? - What pattern matters, and what’s noise? AI helps us see faster, but not think better — that’s still on us. The best data teams don’t wait for magic moments. They build systems that generate insight consistently. In the end, insight isn’t luck. It’s design, iteration, and interpretation — the real alchemy of intelligence.
0 likes • 27d
Love this perspective
How to get patience while learning 😩
When I sit down to study Anything, I feel like finishing this thing or this video and making a new thing and then making money by making sales and because of this I am not able to focus properly nor am I able to understand things properly. What should I do then?
2 likes • Sep 8
Focus is muscle... train it daily.
Hierarchical Reasoning Model
"Reasoning, the process of devising and executing complex goal-oriented action sequences, remains a critical challenge in AI. Current large language models (LLMs) primarily employ Chain-of-Thought (CoT) techniques, which suffer from brittle task decomposition, extensive data requirements, and high latency. Inspired by the hierarchical and multi-timescale processing in the human brain, we propose the Hierarchical Reasoning Model (HRM), a novel recurrent architecture that attains significant computational depth while maintaining both training stability and efficiency. HRM executes sequential reasoning tasks in a single forward pass without explicit supervision of the intermediate process, through two interdependent recurrent modules: a high-level module responsible for slow, abstract planning, and a low-level module handling rapid, detailed computations. With only 27 million parameters, HRM achieves exceptional performance on complex reasoning tasks using only 1000 training samples. The model operates without pre-training or CoT data, yet achieves nearly perfect performance on challenging tasks including complex Sudoku puzzles and optimal path finding in large mazes. Furthermore, HRM outperforms much larger models with significantly longer context windows on the Abstraction and Reasoning Corpus (ARC), a key benchmark for measuring artificial general intelligence capabilities. These results underscore HRM's potential as a transformative advancement toward universal computation and general-purpose reasoning systems." https://arxiv.org/abs/2506.21734
1 like • Aug 6
Impressive results with minimal parameters.
1-10 of 13
Joshua Mitchell
2
5points to level up
@joshua-mitchell-8511
Pay-per-performance AI marketing campaigns. We only get paid after you get sales & collect money

Active 2h ago
Joined Jan 17, 2025
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