Live data from Hacker News

Gemini 3 Pro vs. 2.5 Pro in Pokemon Crystal

blog.jcz.dev

1–10 of 97 posts

Re: Gemini 3 Pro vs. 2.5 Pro in Pokemon Crystal

#2
Being through the game recently, I am not surprised Goldenrod Underground was a challenge, it is very confusing and even though I solved it through trial and error, I still don't know what I did. Olivine Lighthouse is the real surprise, as it felt quite obvious to me.

Re: Gemini 3 Pro vs. 2.5 Pro in Pokemon Crystal

#5
Nice writeup! I need to start blogging about my antics. I rigged up several cutting edge small local models to an emulator all in-browser and unsuccessfully tried to get them to play different Pokémon games. They just weren't as sharp as the frontier models.

This was a good while back but I'm sure a lot of people might find the process and code interesting even if it didn't succeed. Might resurrect that project.

Re: Gemini 3 Pro vs. 2.5 Pro in Pokemon Crystal

#6
post #4

"Crucially, it tells the agent not to rely on its internal training data (which might be hallucinated or refer to a different version of the game) but to ground its knowledge in what it observes. " Does this even have any effect?

I very much doubt it

Re: Gemini 3 Pro vs. 2.5 Pro in Pokemon Crystal

#7
post #4

"Crucially, it tells the agent not to rely on its internal training data (which might be hallucinated or refer to a different version of the game) but to ground its knowledge in what it observes. " Does this even have any effect?

I'm wondering about this too. Would be nice to see an ablation here, or at least see some analysis on the reasoning traces.

It definitely doesn't wipe its internal knowledge of Crystal clean (that's not how LLMs work). My guess is that it slightly encourages the model to explore more and second-guess it's likely very-strong Crystal game knowledge but that's about it.

Re: Gemini 3 Pro vs. 2.5 Pro in Pokemon Crystal

#8

I wonder how much of it is due to the model being familiar with the game or parts of it, be it due to training of the game itself, or reading/watching walkthroughs online.

There was a well-publicised "Claude plays Pokémon" stream where Claude failed to complete Pokemon Blue in spectacular fashion, despite weeks of trying. I think only a very gullible person would assume that future LLMs didn't specifically bake this into their training, as they do for popular benchmarks or for penguins riding a bike.

Re: Gemini 3 Pro vs. 2.5 Pro in Pokemon Crystal

#9
post #4

"Crucially, it tells the agent not to rely on its internal training data (which might be hallucinated or refer to a different version of the game) but to ground its knowledge in what it observes. " Does this even have any effect?

Yes, at least to some extent. The author mentions that the base model knows the answer to the switch puzzle but does not execute it properly here.

"It is worth noting that the instruction to "ignore internal knowledge" played a role here. In cases like the shutters puzzle, the model did seem to suppress its training data. I verified this by chatting with the model separately on AI Studio; when asked directly multiple times, it gave the correct solution significantly more often than not. This suggests that the system prompt can indeed mask pre-trained knowledge to facilitate genuine discovery."

Re: Gemini 3 Pro vs. 2.5 Pro in Pokemon Crystal

#10

Nice writeup! I need to start blogging about my antics. I rigged up several cutting edge small local models to an emulator all in-browser and unsuccessfully tried to get them to play different Pokémon games. They just weren't as sharp as the frontier models. This was a good while back but I'm sure a lot of people might find the process and code interesting even if it didn't succeed. Might resurrect that project.

I have to think they need to know enough of the guides for the game for it to work out, how do they know whats on screen?
Post reply on HN