Update on Research PSCLS

Reddit r/artificial Models
sequential-learning representation-learning language-model research experimental ai

Summary

The author shares early progress on Leo/PSCLS, an experimental system that learns sequence relationships and improves its story generation and metrics as it is trained on more stories.

I’m building Leo / PSCLS — an experimental system that learns relationships between sequences and updates its internal representations from experience. Here’s how its actual output changed as it saw more stories. 1K stories “Once upon a time to the store and said that there was a she bor and he lorander thing they were…” Basically nonsense. 3K stories “Once upon a time to the store and said that there was a she parted to see had a bided her tod and be bound aster…” Still broken, but the output is becoming more structured. 40K stories “Once upon a time, there was a big started to play with the should some too her mom and had a said, it was time. They happy and went to the park…” Now we’re getting recognizable story-like patterns, characters, actions and dialogue — although the grammar is still heavily broken. And the measured results improved too: 1K → 3K → 40K BpB: 2.678 → 2.641 → 2.334 Accuracy: 52.37% → 53.62% → 58.11% This is still an early experiment, not AGI. But watching the same system change its outputs as it learns more experience is pretty interesting. Next target: 250K → 500K → 1M stories.
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