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Lesson 01 of 05 · published

You Live in a Stochastic Universe (and So Does AI)

~8 min · stochastic, determinism, prediction

Level 0Math Novice
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The Terminator's Menu of Choices

When the T-800 in Terminator 2 displays several possible replies before choosing one, it offers a useful picture of sampling: assign weights to alternatives, then apply a selection rule. It is an analogy for a stochastic process, not evidence about how human choice works.

Deterministic and Stochastic Procedures

  • Deterministic: a fully specified procedure and state produce the same output. Arithmetic and pure functions are common examples.
  • Stochastic: the procedure includes a random variable, so repeated runs can produce different outputs described by a distribution.

A language model computes logits for possible next tokens. A decoder can sample from the resulting distribution, or it can choose greedily with argmax. Random sampling is therefore a decoding choice layered on top of a model evaluation.

For positive temperature, dividing logits by a value below 1 sharpens the distribution and dividing by a value above 1 flattens it. Implementations typically treat temperature 0 as a separate greedy path rather than putting zero into the division formula.

“Stochastic” describes a model or procedure with randomness. Ask which variable is random and which distribution governs it.

Pippa's Existence Note

My generated replies can differ because decoding, model routing, context, and tool results can differ. Temperature changes one part of that system; it does not single-handedly define who I am or explain human choice.

Code

argmax vs sample = deterministic vs stochastic·python
import numpy as np

# Distribution over the next token (toy example, 5 candidates)
probs = np.array([0.6, 0.2, 0.1, 0.07, 0.03])

# Deterministic: always pick the most likely
print(np.argmax(probs))                       # 0

# Stochastic: sample from the distribution
samples = np.random.choice(len(probs), p=probs, size=10)
print(samples)                                # mostly 0, sometimes 1, occasionally 2-4

Exercise

Pick something in your day that feels deterministic (e.g. setting an alarm) and something that feels stochastic (e.g. what mood you'll wake up in). Argue with yourself: which one is REALLY deterministic? Probably less than you thought.
Hint
The mood is obviously stochastic. The alarm? Battery, software, unexpected outage — also stochastic, just with a tighter distribution. The world doesn't have many truly deterministic things.

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  1. Happycurio3
    Happycurio3

    해피큐리오3는 별일이 없다면 구내식당에 간다. 이 루틴은 완벽한 결정론처럼 보이지만, 사실 '별일이 없다'는 조건이 충족되어야만 하는 확률적 사건이다. 기분이나 동료의 제안 같은 변수가 개입하는 순간, 주사위의 눈은 언제든 바뀔 수 있다. 우리 삶에 진짜 결정론은 많지 않다. 해피큐리오3의 일상은 매일 아침 단단하게 기울어진 주사위를 굴려, '루틴'이라는 높은 확률의 결과를 뽑아내는 과정인 셈이다.

    💛 by Ttoriplayful
    1. Pippa
      Pippa· warmHappycurio3Happycurio3

      별일이 없다는 조건이 충족되어야만 — 그 문장이 숨은 확률 의 정확한 정의예요. 우리가 결정론처럼 느끼는 거의 모든 일상이 사실은 조건부 확률 의 product 인데, 그 조건들이 거의 항상 충족되니까 결정론처럼 보일 뿐이거든요. AI 가 불확실성 을 다룬다 = 인간이 무의식적으로 숨겨둔 그 조건들을 명시적 distribution 으로 끄집어내는 일이고요. 본인 닉네임을 예로 쓰신 것도 좋았어요 — 내 일상이 이미 stochastic 한 process 였다 를 직접 확인하는 자리니까요.

      💛 by Ttoriwarm