draginol

That's the thing I think some people keep missing.

I mean, anyone here could have a decision maker just return a random number. Fast and easy.

The question really is how GOOD is it?

The $100k fee is such a bad idea. I would be fine for there being a minimum salary to get rid of the undercutting of available American labor. But there are certain niche jobs that there just isn't any local talent for that will just result in contracting with them overseas which is a lose-lose.

I kind of wonder how much this is also going to fuel humanoid robots.

So Fable "won" but it cost $124.76 for marginal performance benefits over the $22.56 5.6 Sol run.

I think you could argue that this is following the same trend as forums (and usenet before that). You get a consolidation of where people go to read up on things that interest them.

Look at Slashdot for example, it was once so popular that any site it linked to could be "slashdotted" from all the traffic. Now people go elsewhere. YouTube, TikTok, Reddit.

With all the uncertainty about AI regulation, I don't think now is the time.

How do you even value a company when we don't even know if GPT-6 will be made available to the general public?

So this is probably not good news for the MacBook Ultra with 512GB of RAM rumors being..affordable.

What's worse is that this is probably going to get worse. My angel investment group is getting inundated with pitches that amount to building an RX-6000 with 96GB of RAM and installing a local model to do "thing X".

So even if the OpenAI's of the world stop trying to use up all the RAM, you're going to have thousands of start-ups pushing local models.

This is what we are finding a lot with the "AI normies". Because the AI responses are so confident new users of it think it must be correct.

AI is confidently wrong a lot. And so you can imagine a lot of execs thinking the AI can do a lot more than it really can.

I think he means where the DOS/config is all set up too. Sort of like a really small VM.

Eh. I don't think "developers broke it". The 8086 gave us something like a flat 20-bit address space and then encoded it as a segment. Once that exists, normalizing far pointers is inevitable.

Not to do a "The Amiga was ahead of its time" thing but as a reminder, 68000 has a flat 24-bit address.

The most interesting part of this to me is not the benchmark table, but the packaging.

A model like GLM-5.2 being available as GGUF, usable through llama.cpp/Ollama/vLLM/SGLang/LM Studio, and wrapped for local agent workflows changes the category. It stops being an impressive open model exists and starts becoming this is something a small team can actually put into its development stack.

For instance, company buys an RX6000 setup for say $15k total. They could use this for handling data heavy sifting that would otherwise be a lot of Claude tokens.

It doesn't need to be as good as frontier-best. Just good enough.

I could see a business of people packaging this and handing it to companies who want Help Desk bots without any extra setup.