This isn't without it's challenges however.

1. This will increase costs drastically, since they would need to a run a sandbox per use to ensure data isolation.

2. Increased latency, and this directly limits how much of the harness can be moved to the cloud before the users notice sluggishness

All requests to an LLM are idempotent, for every API call you need to send it the entire conversation history so that it can process it. LLMs do not learn or remember anything, which makes it super easy for users to switch LLMs on the fly. Most popular AI frameworks, make this a one-liner change these days.

And that makes me wonder if the trillion dollar valuations for OpenAI and Claude are even justified. Cause if that is justified, then Kimi, Qwen, Deepseek etc are also valued at a trillion dollars. Or all of them are worth a lot less. One of those statements is true.

Also this makes me wonder if the next iteration of LLMs would be based on fine-tuning, where LLMs actually learn from your past behaviour so that it would grant some amount of stickiness to the product. OpenAI used to offer fine tuning runs for GPT-3.5, but they don't seem to do that anymore.

Another reason could be that they want to close the gap between their valuations and OpenAI/Anthropic.

Either Chinese labs are worth more or OpenAI/Anthropic are worth less. One of those is true

I live in India and have used 1Gbps Fiber since almost 10 years and pay only 40$ for it. Internet access in India is quite cheap and fiber is quite easily available

If you don’t want an AI Agent to read private repos then you do not give the AI agent access to the private repos. This is not a permission bypass issue but a prompt injection issue which can’t be reliably solved at the Agent layer

But not all of my physical games CD/DVDs are in mint condition and some have scratches.

I use a DAC by focusrite which can do 24-bit, and if I want to listen to higher fidelity audio on my planer headphones then I should be able to. Why should I limit myself to 16-bit

The issue is the higest voted issue on their gitlab repo: https://github.com/anthropics/claude-code/issues/6235

LLMs are getting better at a rapid pace and in a year or two, Chinese LLMs should easily catch up with the best of the models. Models have kind of reached a saturation point and that’s why OpenAI and Anthropic are doing an IPO now. Because a year down the line when their lead diminishes even more, they would be worth lesser money.

SpaceX has clients to put payloads into space, but those clients have always looked for good low cost alternatives. It is going to have competition in the future and will lose customers.

Is there some code or results from experiments where we can see the speed up?

Your title is clickbait

If you meant American citizen human rights, then you’re correct.