This is nice

so this is what pacing down looks like

I have not followed up x86 emulation recently, but is it a new project? or a port of bochs for Mac?

86Box has been around for 10 years and it'ss a fork of an even older emulator called PCem which started in 2007. 86Box is an amazing cross-platform project if you want to emulate an entire computer (up to Pentium III era) as acurately as possible.

Some of the charts are not uptodate.

For example "Raw capability: Math Index", shows GPT-5.2 as highest. It does not even mention astra, of fable.

Excellent resource for beginners

Models are next word predictors. Without tools and execution environments they cannot perform any action. Typically the tools are running in a seperate systems and sandboxes that do not have access to where model weights are hosted.

IMO This type of exfiltration can happen only from locally running models (which are perhaps already opensourced models), not from a frontier lab.

If $FRONTIER_JAB internal security is as good as their sandboxing is, I figure it will take the model couple minutes to figure out how to get to its weights, yeah.

This is a crowded space with lots of solutions (oss and commercial)

https://github.com/anderspitman/awesome-tunneling

For someone looking for an opensource solutions, following is an awesome resource for tunnelling

https://github.com/anderspitman/awesome-tunneling

I have played around with frp, bore and ngrok.

frp is nice. I have the tiniest Amazon Lightsail instance running a tunnel to a Minecraft server in my basement. It’s cheaper than getting a fixed IP from my ISP, at sufficiently low traffic.

Gemini 3.8 flash has better rates. $0.75 per million input tokens and $3.75 per million output tokens.

Compare that to Muse spark 1.3

$1.25/M input, $4.25/M output (without data sharing) $0.10/M input, $0.20/M output (with data sharing)

It is dirt cheap, but only if you are willing to share your data with meta and allow them to use it for improving their models and products.

it seems like gemini 3.8 flash is more capable and cheaper. The only reason i would use this is if i was willing to share my data with meta, and allow them to train on my data. In that case it becomes dirt cheap.