🧠 How AI Addresses Our Brain’s Limitations

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Welcome back AI prodigies!

In today’s Sunday Special:

• 📜The Prelude

• 💭Why We Think the Way We Do

• 🤖Where AI Beats the Brain

• 🔑Key Takeaway

Read Time: 6 minutes

🎓Key Terms

• Tokens: The smallest units of data used by AI models to process and generate text.

• Deep Learning (DL): Mimics the human brain by creating multiple layers of “artificial” neurons to solve problems.

• Large Language Models (LLMs): AI models pre-trained on vast amounts of data to generate human-like text.

• Rapid Access Memory (RAM): A computer’s short-term memory that stores large volumes of data for AI models to quickly access.

🩺 PULSE CHECK

📜THE PRELUDE

Humans have developed electricity, learned the universe’s fundamental principles, and discovered how to add, remove, or modify genetic material like DNA.

But we’re also surprisingly bad at basic things. We forget names. We misjudge risks. We get distracted mid-conversation.

So, why does our brain exhibit both rational and irrational behaviors? And how is AI designed to complement our brain’s natural limitations?

💭WHY WE THINK THE WAY WE DO

The Brain’s Evolutionary Journey?

The brain isn’t optimized like software. At just 2% of our body weight, it consumes around 20% of our resting energy. This disproportionate energy use is a result of millions of years of evolution that prioritized developing our brains to be fast, efficient, and good enough for survival.

Because early humans faced high-stakes scenarios with limited resources, evolution favored Heuristics, or mental shortcuts, which helped them survive by enabling them to make high-stakes decisions under pressure with limited energy use. Now, these mental shortcuts make us prone to bias and error, especially in complex modern environments where instincts can mislead us.

Today, our basic needs are met. However, our brain’s cognitive frameworks of the past remain. For example, we often prioritize what’s emotionally impactful over what’s objectively true because our emotional memories are encoded more vividly than our factual memories. That’s why we perceive patterns even when none exist and feel confident even when we’re wrong. These leftover cognitive frameworks lay the foundation for modern irrationality.

Why We Seem Irrational.

The evolution of the brain has led to a mismatch between older, less rational cognitive frameworks and newer, more rational cognitive frameworks. This mismatch is what causes us to act in ways that seem irrational.

The Limbic System (i.e., a group of structures in our brain), which includes the Amygdala, plays a crucial role in processing how we experience emotions and feelings like anxiety, anger, and fear. The Limbic System is fast and automatic, often triggering emotional responses before our brain can intervene. So, why can’t our brain intervene? The Neocortex (i.e., the outermost layer of our brain), which includes the Prefrontal Cortex, plays a crucial role in deploying higher-level cognitive functions like planning, self-control, and decision-making. The Neocortex operates more slowly than the Limbic System.

This evolutionary setup creates conflicts in the brain between immediate emotions and delayed reasoning, which leads to several paradoxes of human behavior: procrastination, unfounded anxiety, and overreactions followed by regret.

AI = Less Irrational?

Increasing our efficiency can mitigate procrastination, unfounded anxiety, and overreactions followed by regret. This kind of efficiency is what AI promises to deliver. So, how does AI deliver this kind of efficiency?

🤖WHERE AI BEATS THE BRAIN

Although LLMs like OpenAI’s GPT-4.5 aren’t conscious, they hold three distinct advantages over our brains:

1. They Don’t Compromise on Capacity.

Humans are incredibly capable, but our brains come with built-in cognitive constraints, especially regarding Working Memory (WM): the mental workspace we use to hold and manipulate information. Our WM is limited, with our brains only able to juggle up to 9 chunks of information at once, and even that can shrink under stress, fatigue, or when faced with distractions.

LLMs don’t have these biological constraints. They rely on RAM to process information through Tokens. For example, OpenAI’s GPT-4.5 can handle up to 128,000 Tokens for a single user query (i.e., prompt). That’s equivalent to analyzing over 300 pages of a comprehensive report in just seconds. For context, it would take humans days to read, comprehend, and process 300 pages of a comprehensive report.

What’s even more impressive is AI doesn’t forget or filter information unless it’s programmed to. Unlike our brains, which regularly discard, compress, or distort information to save energy and reduce mental overload, AI can retain all the information within their Token limit related to inputs to generate optimal outputs.

2. They Work 24/7.

Human cognitive performance is constrained by mental fatigue. In other words, prolonged workflows, particularly those involving complex tasks, deplete essential Neurotransmitters like Dopamine, impairing our focus and decision-making capabilities.

In contrast, AI relies on computational resources like processors, memory, and electricity, unaffected by the same biological limitations our brains encounter. AI doesn’t experience complex emotions like stress or fatigue and can remain impartial when performing complex tasks without any decline in performance, regardless of how many times it needs to repeat them.

3. They Scale!

AI’s ability to scale workflows by processing multiple complex tasks simultaneously without sacrificing speed or accuracy is unmatched. For example, OpenAI’s GPT 4.5 can sequentially analyze and generate actionable insights from hundreds of scientific documents in minutes. In scientific fields like drug discovery, DL can sift through millions of chemical compounds and predict their ability to inhibit target proteins in the human body that can alleviate the symptoms of diseases.

🔑KEY TAKEAWAY

Our brains are built with compromises: low memory, narrow attention, and imperfect reasoning. AI lacks these biological constraints. When we use mental shortcuts, AI uses data. When we tire, AI persists. When we estimate, AI calculates. The more we understand our brain’s cognitive limits, the better we can design AI tools to help us achieve what we can’t do alone.

📒FINAL NOTE

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