emmettm

>faster and better hardware has never resulted in more efficient software, I really didn’t expect it to be any different here.

I agree with this.

By "high hardware prices", I am implying that we are not getting faster and better hardware.

NVidia halted 5090 production yesterday. As a consumer, where can I buy this faster and better hardware you speak of?

- Miserable startup times are now "solved" by leaving it always running.

- Someone in this thread said the curl installer was slow because the install script needed cute progress bar rendering. To be clear, I don't care about the installer user experience, but I want to spend a moment on this point, because having used OpenCode for over a year, I think this perfectly sums up the entire experience. A commit born from "Claude, please make the installer look sick as fuck with loading bars and stuff" will always be preferred by the developers over a commit that reverts such a change for a 10 MB drop in memory use.

- Tried to read the unreadable announcement website after waiting for the little ThreeJS demo to load. I gave up.

- Logs from various old sessions leaked up to 16GB on some temp folder on my drive. The harness prompts are still token heavy. I know neither of these are real issues, and chat logs are a useful feature for many, but I felt validated to see someone else in the comments also complaining about the silent storage of chat sessions leaking into my drive in a random folder being the default behaviour.

IMO, this release goes far beyond OpenCode. I had always imagined that the advent of LLMs developing human-level coding abilities, combined with the high hardware prices as a result of it, would act as a forcing function to inspire a new generation of ultra-performant, bloat-free open software.

But this release is proving me wrong in every way.

We are entering a new era, what George Hotz coined "maximalist software": A new dawn of computing, where one one hand, we can simply prompt a superintelligent LLM to "please prove the Riemann hypothesis", and it will actually work. On the other hand, the chat log for the proof disappeared, because because the 2 GB Bun server (yes, the one meant to interact with a plaintext LLM API) just crashed.

lol, underrated comment

The linked article claims the average word error rate for Voxtral mini v2 is lower than GPT-4o mini transcribe

The representation is learned. Also, see Sutter's "Bitter Lesson" essay

Free on GitHub :) https://github.com/emcf/thepipe