> the argument that billionaires will leave if taxed at a higher rate isn't compelling
I agree with this. California’s climate and culture will keep many a billionaire within tax nexus reach of the state. Of course, this isn’t a strategy every locale can pursue, but I don’t see a reason for California not to exploit its advantages.
Is there really a market dynamic in rent pricing anymore? I thought that algorithmic collusion had eliminated the need for landlords to compete on price.
> I thought that algorithmic collusion had eliminated the need for landlords to compete on price.
Well, that and non-enforcement of antitrust which is a big part of many of our current economic problems.
Massive corporate landlords like Greystar and Morgan Properties own so much of the market they can do a lot of pricing damage even without colluding with others (but of course they do that too).
The fix for this is to tap the overflow menu icon and choose “Reduce privacy protections”. (Wtf, Alibaba?) This appears to be related to use of iCloud Private Relay.
The gap really is closing, though. I don't remember the source, but there was a publication recently stating that it's 4 months at this point. So, 4 months where you can charge premium prices for the small subset of tasks where only a frontier model will do. I have to think the big AI duopoly is at an inflection point where most of their customers haven't just yet realized that they're being fleeced.
Qwen 3.8 Flash-Next is not dumb. If you've used it and that was your experience, your workload is either ultra-ultra-sophisticated or you're dealing with a broken quant/buggy chat template/other issue. That model is a smart, reliable workhorse.
it was an extremely simply workload with different off the shelf harnesses, they just all sucked when you compare it to a paid hosted model. It was fine for classifying stuff or summarizing though, but missed technical details.
This is a serving bug or quantization issue. I had all kinds of issues that were like this on DGX Spark until I found a single-GB10 vLLM recipe [1] that uses Nvidia's NVFP4 quant. The community quants did not work well.
Another failure mode you may see is inordinately long CoT. Properly served, the model is good at calibrating its CoT length to the difficulty of the immediate task.
I've experienced the same, IIRC also using NVIDIA's NVFP4 quant. Also just decided to ignore because it didn't seem to cause any real issues. I figure it might be a training thing, since the hallucinated user messages seem to occur immediately after tool calls or when it's checking its work.
> Personally, I’ve replaced OpenCode with a thin wrapper around Pydantic-AI as the pythonic analogue to Pi-Agent for headless use via Hermes
That's really interesting. I like Pydantic AI a lot and wondered why all of the harnesses seem to be written in Javascript instead of it. What do you use it for headless, though? I haven't tried Hermes or similar yet, so don't have a handle on what you do with them.
Model welfare, much like AI xrisk, is a concept born from evidence-free “what if?” questions. Some people ran with these what-ifs and developed ornate belief systems around them. And now they demand the rest of us take them seriously.
It is not surprising that the people who see God in these machines mostly do not subscribe to a traditional religion. The spiritual void has to be filled somehow.
I agree with this. California’s climate and culture will keep many a billionaire within tax nexus reach of the state. Of course, this isn’t a strategy every locale can pursue, but I don’t see a reason for California not to exploit its advantages.
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