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August 9 - November 1, 2025
The photosynthetic life-forms became victims of their own success, slowly suffocating in a cloud of their own waste. The rise of oxygen was followed by one of the deadliest extinction events in Earth’s history.
What began as a pollutant to one form of life became fuel for another.
Fungi are currently, and likely have always been, Earth’s garbage collectors.
In Adrian’s frog muscle experiments, a neuron might fire one hundred spikes in response to a certain weight. But after this first exposure, the neuron quickly adapts; if you apply the same weight shortly after, it might elicit only eighty spikes. And as you keep doing this, the number of spikes continues to decline. This applies in many neurons throughout the brains of animals—the stronger the stimuli, the greater the change in the neural threshold for spiking.
Dopamine is not a signal for pleasure itself; it is a signal for the anticipation of future pleasure.
Why would evolution have created brains with such a catastrophic and seemingly ridiculous flaw? The point of brains, as with all evolutionary adaptations, is to improve survival. Why, then, do brains generate such obviously self-destructive behaviors?
Evolution embedded an ancient biochemical failsafe to ensure that an organism did not waste energy trying to escape something that was inescapable; this failsafe was the early seed of chronic stress and depression.
They are seen in our involuntary reflexes and in our most ancient brain circuits. Indeed, rats with their entire brains removed, with nothing left but their neural circuits in their spinal cord, still show latent inhibition, blocking, and overshadowing.
A neural architecture for valence in which stimuli is evolutionarily hard-coded into good and bad
In our metaphor, the basal ganglian student initially learns solely from the hypothalamic judge, but over time learns to judge itself, knowing when it makes a mistake before the hypothalamus gives any feedback. This is why dopamine neurons initially respond when rewards are delivered, but over time shift their activation toward predictive cues. This is also why receiving a reward that you knew you were going to receive doesn’t trigger dopamine release; predictions from the basal ganglia cancel out the excitement from the hypothalamus.
The importance of curiosity in reinforcement learning algorithms suggests that a brain designed to learn through reinforcement, such as the brain of early vertebrates, should also exhibit curiosity.
In vertebrates, surprise itself triggers the release of dopamine, even if there is no “real” reward.
Gambling and social feeds work by hacking into our five-hundred-million-year-old preference for surprise, producing a maladaptive edge case that evolution has not had time to account for.
On land, even at night, you can see up to one hundred times farther than you can underwater. Thus, fish opted not to simulate and plan their movements but instead to respond quickly whenever something came at them (hence their large midbrain and hindbrain, and comparatively smaller cortex).
simulating actions is astronomically more computationally expensive and time-consuming than the reinforcement-learning mechanisms in the cortex-basal-ganglia system.
the neocortex of a rat, a monkey, and a human all look relatively the same under a microscope.
According to Mountcastle, the neocortex does not do different things; each neocortical column does exactly the same thing. The only difference between regions of neocortex is the input they receive and where they send their output; the actual computations of the neocortex itself are identical. The only difference between, for example, the visual cortex and the auditory cortex is that the visual cortex gets input from the retina, and the auditory cortex gets input from the ear.
None of this is an obvious result. Imagination could have been performed by a system separate from recognition. But in the neocortex, this is not the case—they are performed in the exact same area. This is exactly what we would expect from a generative model: perception and imagination are not separate systems but two sides of the same coin.
The neocortex seems to be in a continuous state of predicting all its sensory data. If reflex circuits are reflex-prediction machines, and the critic in the basal ganglia is a reward-prediction machine, then the neocortex is a world-prediction machine—designed to reconstruct the entire three-dimensional world around an animal to predict exactly what will happen next as animals and things in their surrounding world move.
Humans spend a painful amount of time wallowing in regret.
But here is the weird thing—we don’t truly remember episodic events. The process of episodic remembering is one of simulating an approximate re-creation of the past. When imagining future events, you are simulating a future reality; when remembering past events, you are simulating a past reality. Both are simulations.
contrary to our perceptions of how accurate our memories are, it has been shown that eyewitness testimony is terrible: 77 percent of the wrongfully convicted individuals exonerated by the Innocence Project were originally convicted because of mistaken eyewitness testimony.
The basal ganglia has no intent or goals. A model-free reinforcement learning system like the basal ganglia is intent-free; it is a system that simply learns to repeat behaviors that have previously been reinforced.
when we ask, “Why did the AI system do that?,” we are asking a question to which there is really no answer. Or at least, the answer will always be the same: because it thought that was the choice with the most predicted reward. In contrast,
This mechanism of cooperation doesn’t scale; the limit of human group size maintained only by direct relationships has been estimated to be about one hundred fifty people. In contrast, common myths of things like countries, money, corporations, and governments allow us to cooperate with billions of strangers.
The real reason why humans are unique is that we accumulate our shared simulations (ideas, knowledge, concepts, thoughts) across generations.
We are the hive-brain apes. We synchronize our inner simulations, turning human cultures into a kind of meta-life-form whose consciousness is instantiated within the persistent ideas and thoughts flowing through millions of human brains over generations. The bedrock of this hive brain is our language.
On the eastern side of the mountains, however, in an environment of dying trees and progressively more open grasslands, evolutionary pressures began tinkering. It was this lineage that would eventually become human.
The initial niche our ancestors seemed to fall into was scavenging carcasses.
In other apes, tools are a useful but not essential feature of their survival niche. In H. erectus, however, the manufacture of complex tools was a requirement to survive. A Homo erectus without a stone hand ax was as doomed as a lion born without teeth.
What is the most natural activity we use language for? Well, we gossip. We often can’t help ourselves; we have to share moral violations of others, discuss relationship changes, keep track of dramas. Dunbar measured this—he eavesdropped on public conversations and found that as much as 70 percent of human conversation is gossip. This, to Dunbar, is an essential clue into the origins of language.
Every roundabout of this cycle made our ancestors’ brains bigger and bigger. As social groups got bigger (powered by improved gossip, altruism, and punishment), it created more pressure for bigger brains to keep track of all the social relationships. As more ideas accumulated across generations, it created more pressure for bigger brains to increase the storage capacity of ideas that could be maintained within a generation. As the usefulness of inner simulations increased due to more reliable sharing of thoughts through language, it created more pressure for bigger brains to render more
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Not everything in evolution evolved “for a reason.”
What is most amazing about the success of LLMs is how much they seemingly understand about the world despite being trained on nothing but language. LLMs can correctly reason about the physical world without ever having experienced that world.
If there is anything that truly makes humans unique, it is that the mind is no longer singular but is tethered to others through a long history of accumulated ideas.
