Themata.AI
Themata.AI

Popular tags:

#developer-tools#ai-agents#discussion#trending#llms#ai-ethics#claude#code-generation#ai-safety#openai

AI is changing the world. Don't stay behind. Clear summaries, community insight, delivered without the noise. Subscribe to never miss a beat.

© 2026 Themata.AI • All Rights Reserved

Archive

|

Topics

|

Privacy

|

Cookies

|

Contact
ai-agentsllmsrandomnessexperiments

I asked Claude for 37,500 random names, and it can't stop saying Marcus

GitHub - benjismith/ai-randomness: experiments invoking AI agents and asking them to act randomly!

github.com

February 25, 2026

1 min read

🔥🔥🔥🔥🔥

49/100

Summary

Experiments with AI agents assessed how language models manage randomness, with Claude selected a name at random 37,500 times. The most frequently chosen male name was "Marcus," appearing 4,367 times, and Opus 4.5 produced "Marcus" 100% of the time with a simple prompt, while nine parameter combinations resulted in zero entropy.

Key Takeaways

  • The name "Marcus" was selected 4,367 times (23.6%) in a series of 37,500 random name prompts across five models.
  • Opus 4.5 produced "Marcus" 100 out of 100 times with a simple prompt, demonstrating deterministic behavior.
  • Nine parameter combinations resulted in zero entropy, indicating perfectly deterministic outputs.
  • Using random word seeds was more effective than random noise for increasing diversity in name selection.
Read original article

Coverage & discussions

Hacker News · github.com

I asked Claude for 37,500 random names, and it can't stop saying Marcus ↗

Community discussions

Hacker News discussion ↗

Historical count: 5 · 5 saved in sample · Historical sample

Analysis ready

Community Sentiment

Mixed

Positives

  • Injecting randomness into prompts can enhance the diversity of LLM responses, offering a practical method to overcome limitations of temperature settings.

Concerns

  • The repeated mention of 'Marcus' highlights a potential collapse in the model's training, raising concerns about its ability to generate truly random outputs.

Related Articles

Diffusion at Scale: Introducing Mercury 3 â Inception

Inception "Mercury 3", 1000 tok/s diffusion LLM

Oct 19, 2026

GitHub - IsuruMaduranga/harness-engineering-101: Harness Engineering 101 — building AI agents from first principles. The LLM is the brain; the harness is the body.

Harness Engineering 101: The LLM is the brain, the harness is the body

Oct 19, 2026

If you don't run your own LLM proxy, how the fuck do you even know whats going on?

If you don't run your own LLM proxy, how do you know whats going on?

Oct 18, 2026

Hybrid Reasoning Agents

Hybrid Reasoning Agents: LLM agents that think in latent space, act through text

Oct 18, 2026

How Far Will AI Assistants Go for a Refund They Can’t Get? | Vals AI

How Far Will AI Assistants Go for a Refund They Can't Get?

Oct 18, 2026