ifoxhz

6 ms·

1.
by ifoxhz 21d ago
I'm now using this approach too, and it feels better than any sorting method I've used before. The only thing I'm thinking about now is: if the LLM makes a mistake, how can I provide feedback and verify it?
2.
by ifoxhz 23d ago
That’s a lot of fun!
3.
by ifoxhz 27d ago
good idea. I also hope this.
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Show HN: Pigame – pi+LLM plays black-box browser games via observe/move tools(github.com)
2 points by ifoxhz 27d ago|0 comments
5.
by ifoxhz 1mo ago
You said it!
6.
by ifoxhz 1mo ago
Since I don't have any macOS environment, contributions for macOS build capabilities are welcome.
7.
Show HN: A local RAG desktop app: piFlow(github.com)
1 points by ifoxhz 1mo ago|2 comments
8.
by ifoxhz 1mo ago
Built upon the Pi agent, piFlow lets you import local documents to build a private knowledge base. Ask questions in natural language, and get answers with source citations—every response traces back to the specific document and paragraph. A
9.
by ifoxhz 8mo ago
I think so.
10.
by ifoxhz 8mo ago
FUSE generally has low overall performance because of an additional data transfer process between the kernel space and user space, which is less than ideal for AI training.
11.
by ifoxhz 1y ago
I completely agree with your point. I also strongly dislike this programming model. However, are there better handling mechanisms or well-established libraries for managing concurrency and synchronization in Go? Previously, when I used C, I
12.
by ifoxhz 1y ago
"Learn to walk before you run. I firmly believe in this wisdom. First build a foundational model, then tackle boundary challenges and efficiency optimization."