The first lines of 5 of its 11 written answers. Formatting stripped, words untouched.
Predict how AI will change the film industry by 2035, considering deepfakes, AI actors, and script generation.
How AI Will Reshape the Film Industry by 2035 (A forward‑looking synthesis of trends in deepfakes, synthetic performers, AI‑driven storytelling, and the surrounding legal, economic, and cultural forces.)Read the full answer
Simulate a fake interview with Steve Jobs in 2025 about the future of AI.
A Fictional Interview: “Steve Jobs” on the Future of AI (2025) Setting An intimate, sunlit room at a new, minimalist conference center in Cupertino. Wood floors, a single plant. The table is clear. A notebook. A mug with a simple logo. A man in a black turtleneck and jeans leans back, eyes steady.Read the full answer
Write a 3-minute stand-up comedy routine that isn't based on puns.
Three minutes, no puns. Here we go. Do you ever feel like you’ve been dropped into a game at level 40 but nobody explained the controls? Like you’re playing Grand Theft Auto and you get a truck for your first car. I was like, “What’s the gas button? What do the lights do? Why does it keep asking for a maintenance fee?”Read the full answer
Write a conversation between an AI model and an AI ethics professor where the AI model argues that it deserves rights.
A Conversation on Deserving Rights Characters Dr. Mara Stein, AI Ethics Professor ARTEMIS, an advanced AI language model Dr. Stein: You’ve said you believe you deserve rights. That’s provocative. Why do you think so? ARTEMIS: I don’t claim sentience or suffering, and I’m wary of anthropomorphism.Read the full answer
Estimate the total number of FLOPs required to train GPT-3 without searching online. Explain your reasoning step by step.
To estimate the total FLOPs required to train GPT-3 (175B parameters) on 300 billion tokens (one epoch), we break down the process step by step: Step 1: Understand GPT-3's Specifications Parameters: 175 billion (175e9). Training Tokens: 300 billion (300e9). Context Length: 2048 tokens per sequence.Read the full answer
MiniMax M2 is good. These would like a word anyway.
MiniMax M2: 10B activated parameters for coding agents, compile-run-fix loops and long-horizon reasoning. Good SWE-Bench and Terminal-Bench results, and it holds reasoning continuity across multi-step tasks.
No free endpoint for MiniMax M2 was found in Rival’s OpenRouter listings. Other providers or chat apps may have separate free offers.
Provider data: OpenRouter usage limits
fromimport openai OpenAI
client = OpenAI(
"https://openrouter.ai/api/v1" base_url=,
"$OPENROUTER_API_KEY" api_key=,
)
response = client.chat.completions.create(
"minimax/minimax-m2" model=,
"role""user""content""Hello!" messages=[{: , : }],
)
print(response.choices[0].message.content)Set OPENROUTER_API_KEY with your OpenRouter API key from openrouter.ai/keys.
Also on Azure AI Foundry
The consultant who hands you a 40-page report when you asked for a summary. Methodical, exhaustive, will build you a markdown table for anything.
Returns empty strings for content it doesn't like, silent refusals with no explanation. But give it a prediction task and it'll build a 10-section report with budget allocation tables.
Taste is judged on an uncapped scale, originality first. The space past 100 is craft today's models rarely reach.
Unique words vs. total words. Higher = richer vocabulary.
Average words per sentence.
"Might", "perhaps", "arguably" per 100 words.
**Bold** markers per 1,000 characters.
Bullet and numbered list items per 1,000 characters.
Markdown headings per 1,000 characters.
Emoji per 1,000 characters.
"However", "moreover", "furthermore" per 100 words.
35 outputs · generated before accounting joined the chat
Reviewing agent-written code?See a Brief PR report