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> You don't have to have health insurance at all,

There are (or were) tax time penalties for failing to have healthcare coverage. Possible USA laws have changed recently.

> What gp wanted to say is that models are now so smart and useful that even if they managed to be EVEN MORE smart and useful, you wouldn't even notice it.

If benchmarks across the board keep trending up and you still don't notice a difference, that's not evidence the model stopped improving. More likely your tasks aren't hard enough to expose the gains, or the model has passed the point where you're able to judge it.

You can only tell a good answer from a great one up to your own ceiling. Once the model clears that, both look the same to you, and the extra capability is real whether or not you can see it.

> "--speculative-config",

Regarding that last option: speculation helps max concurrency when it replaces many memory-expensive serial decode rounds with fewer verifier rounds, and the proposer is cheap enough. It hurts when you are already compute-saturated or the acceptance rate is too low. Good idea to benchmark a workload with and without speculative decoding.

> specific type of manipulable gullibility

A congregation trained to say “amen” on cue.

Not a bad idea, but how do we prevent this from creating incentives to engineer similar situations in the future?

Sound like Singapore's system rewards competence + stability, and that makes it hard for opposition to scale, because the incumbents can absorb popular ideas while keeping institutional advantages.

That’s demoralizing if you’re doing party-building. But the flip side is: it means citizens do have leverage, just not always in the form of “replace the government.”

Money is less about personal consumption and more about a voting system for physical reality. When a company holds billions in IOUs, they are holding the power to decide what happens next. That capital allows them to command where the next million tons of aluminum go, which problems engineers solve, and where new infrastructure is built.

Even if they never spend that wealth on luxury, they use it to direct the flow of human effort and raw materials. Giving it away for free would mean surrendering their remote control over global resources. At this scale, it is not about wanting more stuff. It is about the ability to organize the world. Whether those most efficient at accumulating capital should hold such concentrated power remains the central tension between growth and equality.

FYI: Newer LLM hosting APIs offer control over amount of "thinking" (as well as length of reply) -- some by token count others by an enum (high low, medium, etc.).

I hear you on intergenerational stuff. I just don’t think “public education is a scam” fits what most kids actually receive.

Kids are not only getting classroom time. They inherit a whole baseline that previous taxpayers built: safer streets, clean water, courts that mostly function, vaccines, roads, libraries, stable money, and the accumulated tech and culture that makes modern jobs even possible. That bundle is huge, and it starts paying out long before anyone is old enough to “owe” anything.

Also, adults are not literally trapped. People can move, downshift, opt out of a lot, or choose different communities. Most don’t, even when they complain loudly, and to me that’s a pretty strong signal the deal is at least somewhat reasonable. Not perfect. Not fair for everyone. But not a cartoon pyramid scheme either.

If there’s a real fight worth having, it’s making the burdens and benefits less lopsided across generations, not pretending the whole social investment in kids is fake.

> I do not believe there exists a way to safely use LLMs in scientific processes.

What about giving the LLM a narrowly scoped role as a hostile reviewer, while your job is to strengthen the write-up to address any valid objections it raises, plus any hallucinations or confusions it introduces? That’s similar to fuzz testing software to see what breaks or where the reasoning crashes.

Used this way, the model isn’t a source of truth or a decision-maker. It’s a stress test for your argument and your clarity. Obviously it shouldn’t be the only check you do, but it can still be a useful tool in the broader validation process.

There is no single definition for all scientists. However if you define free will as choices that are completely free of deterministic or even statistically deterministic causes that science could in principle predict, then most scientists would say: no, that kind of free will probably doesn’t exist.

> closed lid would flex slightly in your backpack, and press keys on the keyboard,

FYI: Over time, this repeated pressure + rubbing (especially with dust or grit in between) can leave permanent key-shaped marks or “ghosts” on the screen. Thin laptops and bags that are tightly packed or bulging make this a lot more likely, since there’s less rigidity and more pressure on the lid.

I mostly agree with your intuition, but I’d phrase it a bit differently.

Temperature 0 does not inherently improve “quality”. It just means you always pick the highest probability token at each step, so if you run the same prompt n times you will essentially get the same answer every time. That is great for predictability and some tasks like strict data extraction or boilerplate code, but “highest probability” is not always “best” for every task.

If you use a higher temperature and sample multiple times, you get a set of diverse answers. You can then combine them, for example by taking the most common answer, cross checking details, or using one sample to critique another. This kind of self-ensemble can actually reduce hallucinations and boost accuracy for reasoning or open ended questions. In that sense, somewhat counterintuitively, always using temperature 0 can lead to lower quality results if you care about that ensemble style robustness.

One small technical nit: even with temperature 0, decoding on a GPU is not guaranteed to be bit identical every run. Large numbers of floating point ops in parallel can change the order of additions and multiplications, and floating point arithmetic is not associative. Different kernel schedules or thread interleavings can give tiny numeric differences that sometimes shift an argmax choice. To make it fully deterministic you often have to disable some GPU optimizations or run on CPU only, which has a performance cost.