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  • This reminds me of this post from ~3 years ago: https://news.ycombinator.com/item?id=33847479

    "Building A Virtual Machine inside ChatGPT"

    - https://www.engraved.blog/building-a-virtual-machine-inside/

    It's mentioned in the "Related Work" section too.

    by dpflan
  • This could be useful for honeypots (cybersecurity) although it also might have its own attack vector if the honeypot isn’t setup carefully. Sure, you can already virtualize some shells but I’m sure those have limits that this might not have.

    Cool project, thanks for sharing!

    by dwoosley
  • > Is it useful? Not really.

    So interestingly enough Anthropic has been using models of this kind for their alignment evaluations: https://alignment.anthropic.com/2026/reward-seeker/#:~:text=...

    by saagarjha
  • One of the first very cool demos I've seen of ChatGPT was in a post where the author prompted AI "pretend to be a terminal". Then went on to execute commands like `cd .fbi`, `ls files`, `cat files/confidential.txt`. Very fun demo. Looking forward to exploring similar idea with this terminal
    by ponyous
  • >I used Qwen2.5-Coder-0.5B as the starting point. I needed a small model to get close to realtime performance. Being a coding model, it had also already seen plenty of CLI usage.

    Interesting. I wanted to ask, how that model compares with the fine-tuned version, but I just saw the author provided benchmarks. Interesting that fine-tuning improved the memory so significantly, wouldn't have expected that.

    Though, on second thought, I had an experience where I was able to, as a human, fine-tune my memory beyond what I previously thought was possible!

    Reminds me of one of my favorite jokes.

    Excuse me, can you tell me how to get to Carnegie Hall?

    —Practice, man... Practice...

    by andai
  • This is a micro-implementation of what research calls a "Neural Computer", in which the entire UI itself is generative and driven by user actions.

    Neural Computers provide the illusion you are interacting with an underlying operating system/application, but are actually a recurring (user input) -> (predicted pixel output) loop.

    In theory, it would be impossible to tell a perfect "Neural" computer apart from a "real" one. Which is kind of a wild thought.

    https://arxiv.org/abs/2604.06425

    by gavinray
  • Very very cool! Impressed that it can be done with only fine tuning

    On a very similar theme, I recently built a “lossy git”, which stores your code by training a neural network, then it generates the code back to you on checkout

    * web demo: https://nicobrenner.github.io/lossy-git/demo.html

    * cli version: https://nicobrenner.github.io/lossy-git/

    The web demo runs entirely on the browser, both the version control and the neural network training/inference. You can commit and checkout both images or code - you can also paste/“upload” your own images, no server requests (everything clears from the page on reload)

    by nico
  • Thank for posting it, happy to answer any questions!
    by simedw

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