solomatov

Could you recommend which quantization level to use with it?

Does github copilot ToS allow this?

Do they have any sandbox out of the box?

What do you mean by custom LMStudio license? Your employer requires reviews of proprietary EULAs or do you try to get a custom licensing deal from LMStudio?

Could you compare it to other similar software? E.g. Codex App, Conductor, and others? Why your app?

How is quality for what Qwen 8B provides compares to proprietary models? Is it good enough for your use case?

But what is the result of your work? What do you commit to the repo? What do you show to new folks when they join your team?

Is it essentially using LLMs as a compiler for your specs?

What do you do if the model isn't able to fulfill the spec? How do you troubleshoot what is going on?

You aren't supposed to read code, but do you from time to time, just to evaluate what is going on?

Thanks for the link.

So, basically you made a replacement for webflow for your use case in 10 days, right?

>But it does reduced by an order of magnitude the amount of money you need to spend on programming a solution that would work better

Could you share any data on this? Are there any case studies you could reference or at least personal experience? One order of magnitude is 10x improvement in cost, right?

Is it open source? Do they disclose which framework they use for the GUI? Is it Electron or Tauri?

>I think that really high quality code can be created via coding agents. Not in one prompt, but instead an orchestration of planning, implementing, validating, and reviewing.

Do you have any advice to share (or resources)? Have you experienced it yourself?

It's a very well known pattern. But what about others? There're a lot of very interesting stuff there.

This all sounds interesting, but how effective are they? Did anyone has experience with any of them?

I couldn't find any mentions of whether they train their models on your source code. May be someone was able to?

Is anyone aware of a good llm orchestration libraries for go like langchain for Python and Typescript?

I prefer MacBook to iPad most of the time. The only use case for iPad for me where it shines is when I need to use a pencil.

Does anyone know whether they have optimized memory management, i.e. virt machine not consuming more RAM than required?

Do you have any references to share?

Not a lawyer, but my understanding it's not since legal obligations is a reason for processing personal data.

Why should it be at the kernel level? Which advantages does it give?

IMO, it's not about ethics, it's about legal risks. What if you want to fine tune a model on output related to your usage? Then my understanding is that all these derivatives need to be under the same license. What if G will change their prohibited use policy (the first line there is that they could update it from time to time)? There's really crazy stuff in terms of use of some services, what if G adds something in the same tune there which basically makes your application impossible.

P.S. I am not a lawyer.

It's very nice that it has the Apache 2.0 license, i.e. well understood license, instead of some "open weight" license with a lot of conditions.

Is there a premium option to control which of your data will be used for training? Or is it implemented the same way as Gemini Pro?

May I ask you to give examples of insights from topology which improved existing models, or at least improved our understanding of them? arxiv papers are preferred.

Does anyone know if there were any attempts to test Mamba on really large scale? To me this model looks as the most promising successor to the transformer architecture. Does anyone know why it might not be the case or what are other alternatives?

May be you could give a link to a book which might be a better fit for practitioners?

Do I understand correctly that for all of the above, the task results need to be verified by humans at the end?

A bit off topic, but what would you consider as the best applications of agentic ai?