Would also be a good solution, yes: Removing themselves entirely from the problem.
Looking at how e.g. Roland is repeatedly building new hardware around the same digital "analogue emulation" engine, this shift in the market could make it more viable again to build actual analogue hardware.
Or..."let's add Wi-Fi and a subscription model so the device has to check-in to our servers every week"
(this is already happening, especially many established brands seem to be leaning more and more in this direction)
Low interest rates cause higher house prices, because people can then afford monthly payments for bigger principals and they're all still bidding/buying from more or less the same pool of housing.
Yes, going back into antiquity. The English Crown borrowed around 14% in the 13th and 14th centuries [1]. The Roman grain markets had lending embedded, too, though nothing resembling a risk-free rate. (Monarchies borrowing had an element of coercion to them, so the rate one would lend freely to them was probably higher than the rate they contracted.)
What one can reasonably argue is that there hasn’t been a market-set risk-free rate since the Enlightenment, possibly since Bagehot and the invention of independent central banking. (Some people argue we still don’t have a risk-free rate today.)
Yes. It is covered in various books. Galbraith covered it in “Money…”[0] I’m not totally sure you can draw parallels to the old world, though. The modern economy seems so different, but basically, rates seem to follow the course of a civilization. IIRC, Low when things are stable, higher at the edges as things destabilize. It’s been a few years since I read the book, though, and I may be misremembering things.
If that results in testable predictions, we check them, compare with representations and then are left with just one. And if it doesn't result in testable predictions it can be left for people to write papers on.
This quietly assumes that "representations" of reality only encode neutral objective facts (that can be objectively judged, good luck finding a judge everyone agrees on), and "representations" does not encode intentions and value judgements, ie internalized training logic.
But that leaks in, and of course it does! If training only rewards "objective truth" we might expect that sort of neat ontological cleanliness, but we all know real training goals are more complicated.
There doesn't appear to be a bright clear distinction between objective facts and subjective values/intentions in neural networks. The distinction is perhaps illusory, just another of our preconceived notion about the nature of thought...
The Qwen failure modes I’ve experienced won’t be overcome by running it longer or in more parallel sessions.
In the fall and winter (right now) I’m heating the house anyway so running LLMs 24/7 is basically free to me. So I try it. The models have are limited in their intelligence. I have tasks where I could let Qwen run for days with concurrent workers and never get anywhere, but 15 minutes with Opus solves the problem.
What were the reasons to assume it would be true? I mean if you assume that NP < EXPTIME (which seems very likely) then you end up with algorithms that run in exponential time, but can't simulate turing machines with polynomial overhead. Obviously you can't simulate TMs with just anything, but most of the time... computation finds a way?
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