Gravity Wells
Economic dynamics where scarce resources flow disproportionately to entities with the greatest ability to pay and deploy, creating self-reinforcing concentrations of power. In the AI economy, gravity wells form around three critical bottlenecks: compute (with TSMC packaging capacity initially allocated to Apple and NVIDIA), power (with Microsoft and Meta securing nuclear plants through 20-year contracts), and talent (with top engineers concentrating at leading AI labs). For organizations competing in the AI era, understanding gravity wells determines whether you capture resources or scramble for scraps—those positioned at the center don't just get resources, they define what resources are worth.
Referenced in these posts:
The Alephic AI Thesis: 2025
The AI revolution will be dictated by three physical constraints—compute packaging capacity, energy availability, and organizational agility—that concentrate power in gravity wells. Whoever controls these choke points, not merely the best models, will shape the next decade of AI.
Related terms:
Temperature
Temperature is a parameter controlling a language model’s randomness: at 0 it always picks the most probable next token for deterministic, reliable output, at 1 it samples more broadly for varied, creative results, and above 1 it becomes increasingly random. Choosing the right temperature (e.g., 0 for consistent data extraction or 0.7–0.9 for brainstorming) balances reliability and diversity.
Inference
Inference is the process of running a trained model on new input to generate a prediction or output—such as sending a prompt to GPT-4 and receiving a response. Unlike training, which is costly and infrequent, inference occurs millions of times per day, with speed (tokens per second) and cost (dollars per million tokens) determining an AI feature’s responsiveness and economic viability.
Conway's Law
Conway’s Law states that organizations designing systems are constrained to produce designs mirroring their own communication structures. For example, separate sales, marketing, and support teams often yield a website organized into Shop, Learn, and Support sections—reflecting internal divisions rather than user needs.