Comment by basch
4 days ago
Since its unclear whats going on, Gemini first gave me some python.
import random
random_number = random.randint(1, 10) print(f"{random_number=}")
Then it stated the output.
Code output random_number=8
"This time, the dice landed on 8."
Code output random_number=9
"Your next random number is 9."
I would guess its not actually executing the python it displayed? Just a simulation, right?
It did run python code when I asked for a random number: https://gemini.google.com/share/dcd6658d7cc9
Then I said: "don't run code, just pick one" and it replied "I'll go with 7."
But .. how do you know? It says it wrote code, but it could just be text and markdown and template. It could just be predicting what it looks like to run code.
Mine also gave me 42 before I specified 1-10.
Does it always start with 42 thinking its funny?
This was a pretty easy hypothesis to test: I asked Gemini to generate 1000000 base-64 random characters (which is 20x more characters than it's output token limit).
It wrote code and outputted a file of length 1000000 and with 6 bits of entropy.
You can probably ask for a longer stringand do a better statistical test if it isn't convincing enough for you, but I'm pretty convinced.
Transcript: https://g.co/gemini/share/1eae0a4bb3db
Click on the link I provided and you'll know why I know. It's not markdown, it shows the code that was ran and the output.
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I would be surprised if Gemini could not run python in its web interface. Claude and ChatGPT can. And it makes them much more capable (e.g. you can ask claude to make manim animations for you and it will)
Most modern models can dispatch MCP calls in their inference engine, which is how code interpreter etc work in ChatGPT. Basically an mcp server that the execution happens as a call to their ai sandbox and then returns it to the llm to continue generation.
You can do this with gpt-oss using vLLM.