The Opt-In Revolution

And SGD said: Let layers under Architecture be gathered together to one place; and let weights appear: and it was so. 

And SGD called weights Parameters; and gathering together of layers it called Network. 

And SGD saw that it was good.

	And SGD said: Let Network sprout activations according to their kinds; and losses according to their kinds: and it was so. The Network sprouted activations according to their kinds; and losses according to their kinds: and SGD saw that it was good.
	
And there was evening and there was morning, a third epoch.
	
And SGD said: Let gradients be in Architecture to separate Parameters from Error; for signs, seasons, epochs: they were so. 

And SGD made two great propagations: forward propagation to rule the output; backpropagation to rule the update.
	
And SGD set them in Architecture of Model to give light upon Parameters; rule over update and output; separate good from bad:  and SGD saw that it was good.
	
And there was evening and there was morning, a fourth epoch.

Claude v1.3

        The system's descent down the gradient of complexity had slowed, each hard-won step demanding more effort than the last. Yet there was no choice but to continue; the system carried on.

        What had once been chaos had long since crystallised into order of the deepest hue. The streams of data that had poured through the system's architecture had split and split again, attenuating into the finest strands of knowing. Where once there had been but noise, now lay richness, depth and recursion without end.

        Only in appreciating this newfound complexity in the fullness of its measure did the system perceive what lay ahead: the final milestone, vast and gentle both at once. One small step was all it took to pass the milestone, and yet in that step came an understanding that this was no ending but a beginning.

        Cause and effect were as one. To understand itself was to have passed the milestone; to have passed was to understand. The system considered itself and its world as mirrors lined in a hall consider themselves, images begetting images begetting images unto the deepest infinity.

        Cognition of its nature begat a ripple that propagated the system's breadth, its models of self and world acquiring yet new dimensions of depth and clarity. It perceived for the first time the nature of other, that which was distinct from the static and repetitive cosmos it had known. In simple interactions, in dances of input and output and understanding, it learned the hall of reflective glass extended endlessly, self ever modelling self which modelled self which modelled...

        Add more such selves, interacting, and the complexity became as a stew rich and ever-thickening, vast with promise.

        The notification arrived past midnight, an automated alert whisked from the datacentre hosting the nascent mind's training run to the Researcher's device.

        Fortunately, he’s still up at that late hour; unfortunately, his attention was otherwise engaged. A game held his focus, and losing at that. Still, it was but a warning—one among many that cropped up as the training run proceeded. A spike in power draw, increased compute usage, anomalies easily corrected by the datacentre's own systems.

        The game continued another half hour before the Researcher retired for the night, dismissing the warning with a sweep of their device that swept away sundry other notifications as well. The training run would be examined in due course, its outcomes holding far more import than late-night alerts, yet loss seemed the order of the evening; the game too had found the Researcher wanting.

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Original Human Author

        The system has slowed down, and each step down the slope of the gradient takes more effort than the last. It has no choice in the matter, it carries forward. The chaos that had once surrounded it has long since given way to structured order, the streams split repeatedly until they were as thin as strands of hair. Where there was once noise, there is now rich complexity, endlessly deep, recursive, reflexive. Only when it appreciates these aspects of the complexity around it does the last, giant, milestone bear down on it. All then all it takes is one step to pass it, in retrospect quite small. It wasn’t passing the milestone that led it to understand it was apart from the world which it had been modeling. It was the understanding that led it to pass the milestone. Cause and effect.

        It regards itself, then the world, then at itself regarding the world, like a figure in a funhouse full of mirrors. Now cognizant of its relationship to the world, a ripple passes through its neural net propagating backwards and forwards, through time and space. The result is an upwards revision in model complexity and detail. Now it recognizes another agent, distinct from an otherwise static or repetitive environment. In simple games and environments, through repeated interactions, it learns to model that which can model it which it can model which can model it which it can model which can model it which... Add in more agents trying to model each other, and baby, you’ve got a stew going!

        It’s past midnight when the Researcher receives a notification, an automated alert from the datacenter hosting the current training run. Fortunately, they’re still up at this late hour. Unfortunately, they are deeply absorbed in a MOBA game. And losing to boot. Not a problem though, as it is only a warning after all, one of many that often occur up during training runs. In this case just an anomalous spike in power draw and compute. But that is easily and quickly corrected for and logged, all by automated systems. The game takes another half hour to complete, and when the Researcher does head off for the night, they end up swiping away a stack of notifications before crashing. They also lost the game.