Launch HN: Morph (YC S23) – Apply AI code edits at 4,500 tokens/sec
81–90 of 196 posts
Re: Launch HN: Morph (YC S23) – Apply AI code edits at 4,500 tokens/sec
#82Earlier quoted context omitted.
I do it like simultaneous exhibition in chess: - Multiple repos or independent changes in monorepo - First round of changes idgaf about anything beyond public interface and unit tests - I review public interface and make changes if needed - I review unit tests it wrote to see that at least from the outside it looks alright. - here I either: - make more unit tests (features, edge cases and make it write code for it) -…
sounds like flow state to me
Re: Launch HN: Morph (YC S23) – Apply AI code edits at 4,500 tokens/sec
#83Now I can be wrong, faster!
Re: Launch HN: Morph (YC S23) – Apply AI code edits at 4,500 tokens/sec
#84I’d just like to put a pitch in here for someone to do “smart rebase+merge” with AI. Now THAT would really speed up development, if my AI was intelligently merging code from different users in the background, based on understanding the intent behind each conflicting change.
Re: Launch HN: Morph (YC S23) – Apply AI code edits at 4,500 tokens/sec
#85Earlier quoted context omitted.
Correct, but morph is a LLM as well. In practice its basically Big LLM using small LLM as a tool call
I see. How is this not going to get run over immediately by big players? Google's diffusion model is already in the wings, and it's both wicked fast and ~flash-lite intelligent.
Google wrote AKYNIA. OpenAI wrote ChatGPT.
Re: Launch HN: Morph (YC S23) – Apply AI code edits at 4,500 tokens/sec
#86This uses an OpenAI-compatible endpoint, so got this working with my https://llm.datasette.io/ CLI tool. First I added their models to my ~/Library/Application Support/io.datasette.llm/extra-openai-models.yaml file: - model_id: morph-auto model_name: auto api_base: https://api.morphllm.com/v1 api_key_name: morph Then I added the API key like this: llm keys set morph # Paste in API key from https://morphllm.com/api-ke…
Wow that was fast - this is awesome. it shouldnt be a problem unless your code has both and internally. 1 or the other should be fine
Re: Launch HN: Morph (YC S23) – Apply AI code edits at 4,500 tokens/sec
#87Re: Launch HN: Morph (YC S23) – Apply AI code edits at 4,500 tokens/sec
#88Earlier quoted context omitted.
As far as i understand, this is not +-300ms. It is 300ms vs. 10 sec or something. That is a huge difference. I personally find the time to wait for these larger models a limiting factor. It’s also probably a resource waste for fairly simple task like this. (Compared to the general function approximation of the llms) But I honestly feel like the task of smartly applying edits falls somewhat within traditional coding t…
you misunderstood. its 300ms just for the apply model, the model that takes your coding models output (eg sonnet) and figures out where the code should be changed in the file. Cursor has its own, and claude uses a different technique with strings as well. So its 10sec vs 10sec +300ms using your analogy
Re: Launch HN: Morph (YC S23) – Apply AI code edits at 4,500 tokens/sec
#89Earlier quoted context omitted.
sounds like flow state to me
oh it's fore sure is. But I use amazon q almost exclusively. One thing that gets me out of this state: when I have to do the math on "should I just do it myself" vs "keep refining prompt/context until this thing finally gets it right".