Part 5/9:
The fundamental mechanics of Transformer models rely on probabilistic methods, specifically utilizing gradient descent techniques that deal with probabilities to resolve logic questions. Initially, the limitations in computing power hindered the effectiveness of such models, stymying the depth of answers that could be provided.
In contrast, deterministic systems, which focus on exact logic connections between facts, showcase an alternative route. However, confronting similar hurdles of compute demands, the promise of deterministic systems remained largely unexplored until now.