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Has anyone used Xenharmlib before? I'm curious about it and a huge fan of the feel of JI, but not super experienced with composition myself, and I was wondering what types of things people have done with it.

Think about what OpenRouter primarily traffics in and what you can do with that raw material.

The point is that open weights turns puts inference on the open market, so if your model is actually good and providers want to serve it, it will drive costs down and inference speeds up. Like Cerebras running Qwen 3 235B Instruct at 1.4k tps for cheaper than Claude Haiku (let that tps number sink in for a second. For reference, Claude Opus runs ~30-40 tps, Claude Haiku at ~60. Several orders of magnitude difference). As a company developing models, it means you can't easily capture the inference margins even though I believe you get a small kickback from the providers.

So I understand why they wouldn't want to go open weight, but on the other hand, open weight wins you popularity/sentiment if the model is any good, researchers (both academic and other labs) working on your stuff, etc etc. Local-first usage is only part of the story here. My guess is Qwen 3.5 was successful enough that now they want to start reaping the profits. Unfortunately most of Qwen 3.5's success is because it's heavily (and successfully!) optimized for extremely long-context usage on heavily constrained VRAM (i.e. local) systems, as a result of its DeltaNet attention layers.

It is partly the medium's fault. A lot of the sins of CD/digital mastering wont fly on vinyl because there's physical constraints around what you can literally press into the record groove.

I've had a Framework 13 for several years now, so I'm excited to see this kind of thing start to happen. Praying the next one out is a GPU/tensor workload unit so I'm not stuck at home on my desktop when I want to mess around with local AI models...

Love it, they're teaching LLMs how to skim texts properly, which is exactly the right approach for handling long contexts.

I see a lot of debate about whether AI is "conscious" or has "consciousness", with people talking past each other without a firm grasp on their own stances, so I made a quick quiz to help you locate where you stand.

Yeah. I noticed a lot of "It's not just X. It's Y." which is the biggest tell for me.

Copy paste? Use something like desktop commander and just let it edit the files for you directly. It'll even run commands to test it out. Or go further and use Cline/RooCode and if you're building a webapp it'll load your page in a small browser, screenshot the contents, and send that to the model. The copy-paste stuff is beginner mode.

Much debated question but if we run with your definition, then A2A adds communication capabilities alongside tool-calling, which is ultimately a set of programmatic hooks. Like "phone a friend" if you don't know the answer given what you have available directly (via MCP, training data, or context).

My assumption is that the initial A2A implementation will be done with MCP, so the LLM can ask your AI directory or marketplace for help with a task via some kind of "phone a friend" tool call, and it'll be able to immediately interop and get the info it needs to complete the task.