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- Newsletter 257: Connecting Neurodivergent Thinking with Large Language Models
Newsletter 257: Connecting Neurodivergent Thinking with Large Language Models
🧠Insights from AlphaGo, DeepMind, and the Turing Test
Good morning, fellow lateral thinkers!
Like yesterday’s, today's topic might call for an extra cup of coffee (or two).
I’ve been reflecting on some fascinating parallels between how neurodivergent thinkers like us process information and how large language models (LLMs) like GPT operate.
I know this is a bit more detailed than usual, but stick with me—hopefully, this conversation will click with the way you naturally think.
How My Mind Works—And Why It’s Similar to AI
I’ve always found myself predicting where conversations are going, finishing people’s sentences, and jumping ahead in my head.
It’s part of my neurodivergent (and likely autistic) thinking style—a mix of lateral, non-linear connections that don’t always follow the typical path.
Recently, while watching a YouTube video explaining LLMs with visuals, it hit me: how these models predict the next word is a lot like how my brain works when I’m engaged or excited.
The AI Connection
Large language models are built to predict the next word in a sentence based on the context, kind of like how I’m always anticipating where a conversation is headed.
But the prediction can feel off if the AI (or I) misses key context. Sound familiar?
This is where we neurodivergent thinkers find common ground with how these AIs operate—connecting ideas that others might not see as related.
Learning from AlphaGo and DeepMind
This realization reminded me of the AlphaGo documentary, which showcases how DeepMind’s AI outsmarted one of the world’s top Go players with moves that didn’t make sense—at least not to the humans watching.
But there was logic behind it, even if it was unconventional.
This is what lateral thinking is all about—making unexpected connections that others might miss.
While I’m not the biggest fan of board games (they’ve never really been my thing as a dyslexic thinker), I enjoy games like Mancala and Checkers, but Go is at a different level.
Simple but strategic games resonate with me because they align with how I process patterns.
AlphaGo’s strategic moves reminded me of how I and other neurodivergent folks often think outside the box.
The Significance of the Turing Test
Another critical piece of this puzzle is the Turing test—a benchmark to see if a machine can behave in a way indistinguishable from a human.
While there’s debate over whether AI has fully passed it, tools like ChatGPT are getting closer than ever.
These models don’t just mimic human thought—they mirror the non-linear, associative patterns that neurodivergent thinkers like us naturally use.
Why This Matters
What struck me is how much LLMs reflect our way of thinking.
Both rely on pattern recognition, connecting ideas, and constantly predicting what’s next.
We jump between concepts, linking seemingly unrelated ideas in ways that, to us, make perfect sense.
It’s a powerful reminder that what might seem unconventional or different is quite advanced.
I hope you enjoyed today’s deep dive into the connection between neurodivergent thought patterns and cutting-edge AI.
Let’s continue to think differently and embrace our unique ways of processing the world.
We Think Like You.
Best regards,
Matt Ivey & The Dyslexic AI Team
- LLMs and Neurodivergent Thinking: The parallels between how AI and neurodivergent minds process information highlight the power of lateral, pattern-based thinking.
- AlphaGo and Strategic Thinking: DeepMind’s work shows how unconventional strategies can be effective when there’s a deeper logic behind them.
- The Turing Test’s Significance: Advanced AI is getting closer to human-like thinking, reflecting the non-linear patterns common among neurodivergent thinkers.
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What should the next deep dive be about? |
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