Readit News> On the contrary, we have one working example of general intelligence (humans)
I think some animals probably have what most people would informally call general intelligence, but maybe there’s some technical definition that makes me wrong.
Anecdotally, from the Europeans I know, this is true. When the topic comes up, I will mention that we almost universally have air conditioning here in Canada. (As we do.) After any initial surprise fades over AC in a country generally known for being cold a retort comes usually along the lines of "well you're practically Americans culturally anyway". That may be part of it, sure.
But I think it's mostly that electricity is cheap here, while it reaches almost 40 °C in summer.
Speaking of electricity, the article doesn't really mention energy costs. Here in Canada I don't know many who don't have AC because they don't like it philosophically, but I know some people who don't have one, or who don't use their AC as much as they would like, because they just can't afford it. And it's not the AC itself. It's the electricity. A window unit running on high will consume its weight in electricity in one summer, or sooner.
And that's at Canadian electricity prices, where we pay about 0.10 CAD (0.06 EUR / 0.07 USD) per kWh here. To run AC like Canadians do (often with central air to cool the entire home) could cost potentially thousands of dollars a year, if we paid German electric rates.
TL;DR KANs are tricker to train than traditional neural networks, but they largely have similar loss values given equivalent parameter counts.
Part of this may be due to the fact that most of the optimizers and other components of the training stack have been tuned over decades for MLPs, and there may well be ways out there to get training to work even better for KANs.
I don't personally find a lot of appeal in KANs for big, deep models like LLMs or anything close to that scale. KANs and their B-Splines are much less hardware-friendly than matrix multiplication. However, they are interesting to me from an interpretability perspective, and there may be some unique possibilities there for smaller cases.
The graph simply says to me: "More money has been invested in the market over time, the market has generally been worth more over time."
However, there can be money created by the market, because people and companies can borrow money while using the value of the assets they own as collateral. This borrowing does cause new money to appear from thin air, which means that the market is a source of money, not a sink. As this borrowed money increases the money supply just like physical money-printing would, the price of assets tends to rise along with it, as much of that borrowed money gets put towards buying those assets, increasing the number of buyers, and someone has to be convinced to sell.
This creates an unstable feedback loop of rising borrowing against rising asset prices causing higher asset prices, and it can of course operate in the reverse mode as well, where falling asset prices result in loans being called in, causing the money supply to shrink, pushing asset prices down even further.
(This crash is not a necessary outcome; if the assets correspond to productive investments and real growth, this results in abundance which can in various ways allow those debts to be held or paid off without falling asset prices.)
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A dominant majority in public schools starting late 1970s seems to follow the "Lying to Children" approach which is often mistakenly recognized as by-rote teaching but are based in Paulo Freire's works that are in turn based on Mao's torture discoveries from the 1950s.
This approach contrary to classical approaches leverages torturous process which seems to be purposefully built to fracture and weed out the intelligent individual from useful fields, imposing sufficient thresholds of stress to impose PTSD or psychosis, selecting for and filtering in favor of those who can flexibly/willfully blind/corrupt themselves.
Such sequences include Algebra->Geometry->Trigonometry where gimmicks in undisclosed changes to grading cause circular trauma loops with the abandonment of Math-dependent careers thereafter, similar structures are also found in Uni, for Economics, Business, and Physics which utilize similar fail-scenarios burning bridges where you can't go back when the failure lagged from the first sequence, and you passed the second unrelated sequence. No help occurs, inducing confusion and frustration to PTSD levels, before the teacher offers the Alice in Wonderland Technique, "If you aren't able to do these things, perhaps you shouldn't go into a field that uses it". (ref Kubark Report, Declassified CIA Manual)
Have you been able to discern whether these "patterns" as you've called them aren't just the practical reversion to the classical approach (Trivium/Quadrivium)? Also known as the first-principles approach after all the filtering has been done.
To compare: Classical approaches start with nothing but a useful real system and observations which don't entrench false assumptions as truth, which are then reduced to components and relationships to form a model. The model is then checked for accuracy against current data to separate truth from false in those relationships/assertions in an iterative process with the end goal being to predict future events in similar systems accurately. The approach uses both a priori and a posteriori components to reasoning.
Lying to Children reverses and bastardizes this process. It starts with a single useless system which contains equal parts true and false principles (as misleading assumptions) which are tested and must be learned to competency (growing those neurons close together). Upon the next iteration one must unlearn the false parts while relearning the true parts (but we can't really unlearn, we can only strengthen or weaken) which in turn creates inconsistent mental states imposing stress (torture). This is repeated in an ongoing basis often circular in nature (structuring), and leveraging psychological blindspots (clustering), with several purposefully structured failings (elements) to gatekeep math through torturous process which is the basis for science and other risky subject matter. As the student progresses towards mastery (gnosis), the systems become increasingly more useful. One must repeatedly struggle in their sessions to learn, with the basis being if you aren't struggling you aren't learning. This mostly uses a faux a priori reasoning without properties of metaphysical objectivity (tied to objective measure, at least not until the very end).
If you don't recognize this, an example would be the electrical water pipe pressure analogy. Diffusion of charge in-like materials, with Intensity (Current) towards the outermost layer was the first-principled approach pre-1978 (I=V/R). The Water Analogy fails when the naive student tries to relate the behavior to pressure equations that ends up being contradictory at points in the system in a number of places introducing stumbling blocks that must be unlearned.
Torture being the purposefully directed imposition of psychological stress beyond a individuals capacity to cope towards physiological stages of heightened suggestability and mental breakdown (where rational thought is reduced or non-existent in the intelligent).
It is often recognized by its characteristic subgroups of Elements (cognitive dissonance, a lack of agency to remove oneself and coercion/compulsion with real or perceived loss or the threat thereof), Structuring (circular patterns of strictness followed by leniency in a loop, fractionation), and Clustering (psychological blindspots).
The pros of software are so OP that it hard to justify investing in anything else. Software has incredibly low cap-ex and incredibly high margins. Five humans with five laptops can create a lawn maintenance app worth tens of millions.
To get that same value from, say, building lawn mowers, you need a factory...annnd already the value prop is "nope".
Take note that there is no hardware version of Hackernews. There is no hardware/manufacturing VC scene. Hell even the hardware that is produced today is just a vessel to sell a $19.99/mo software subscription to use the product. Look at what Tesla did, they are getting a reality check on their cars, but Ah!, Tesla is now a software company developing a software package that turns hardware (their cars) into reoccurring profit machines!
Software has eaten the first world, and this is what is looks like. A hyper inflated tech scene where all innovation is happening, and a totally anemic everything-else scene (except finance, that's huge too).
If you want to make it less vague, you can read Keynes.
It's inequality that is the important one, money printing doesn't impact it (except for it impacting inequality). In simple language, people don't want to spend all their money on consumption (the "demand is infinite" you see on econ101 is an approximation), and so when only two dozen people have all the money there aren't many things you can sell and turn a profit. But those people still want to invest all the money they aren't using, there is just nothing to invest into.
At the turn of the 19th to the 20th century, explaining this was a huge open problem in economics.
The phenomenon I described can happen with many or with few transactions. It only requires more buyers than sellers, and money creation through borrowing against the rising price of assets. Creation of money through borrowing is not an increase in the velocity of money, it's an increase in the supply of money.