Even if we concede that, Kalshi and Polymarket need to be better regulated with actual laws associated with it, as opposed to the quasi-wild-west thing we have now. I will acknowledge that a lot of trading isn't significantly different than gambling, at least with trading when you do things to purposefully manipulate the market or gamble with non-public information, there's at least an SEC that can investigate, sue, and/or arrest. I'm not claiming it's perfect, but at least there's an attempt to make the markets more fair.
It doesn't really seem like Kalshi and Polymarket have nearly the same regulation. There are plenty of cases where people are purposefully betting on the market when they can easily manipulate the results, with little/no consequences.
I mean, Polymarket ran this ad during the World Series that all but encouraged using the platform to trade on insider information: https://youtu.be/x6I-ZS8hZUg
I guess the thin veneer of deniability here is that the whistleblower isn’t shown actively trading on the information lol.
I kept thinking the design was going to grow on me as I saw more of them on the road, but nope. I still think it looks unbelievably ugly. I do not think it looks like something that you'd see in Another World, it looks more like something I would have designed when I was fourteen playing with Lightwave.
I regret not archiving all the videos from the youtuber Myles Power (pseudoscience-debunker). He was one of my more favorite YouTubers but a few years ago he nuked his entire channel and all the videos on it (I suspect because his employer didn't like him arguing with people on the internet).
I wanted to rewatch some of his videos recently and as far as I can tell most of his videos are now lost media. I should have downloaded them when I had the chance.
Are you sure? It always seemed pretty reductive to me to try and take something as complicated as intelligence and reduce it down to a single-dimensional number. Most people consider me "smart", but that's only because I'm pretty good at math. I'm pretty much an idiot at anything else. Even the SAT breaks things down into different categories.
Also, given the fact that you can study for IQ tests, I don't really think I agree at all that it's some immutable and objective fact of behavioral science.
Sure, but If you can improve your IQ by studying, that suggests that this number isn't some hyper-objective thing we should treat as immutable or that it's even a true reflection of the person's total cognitive abilities.
I'm not saying that IQ is useless or anything, just that we should take the results with an appropriately large grain of salt.
You can improve your score by getting better at the tests and improving exam technique and maybe go from (picking numbers out of my arse) 115 to 120. You can't go from 90 to 120.
Depending on whether we're talking about studying-for-the-test or studying (education) generally:
> Studying and formal education can improve an IQ score by 1 to 5 points per additional year of schooling, while direct practice and familiarity with test formats can bump scores temporarily by 5 to 15 points.
If you include education generally, this gives a swing of up to 80 points between someone who goes to school K-12 and then studies for the IQ test, vs. someone who doesn't do any of that.
Given that 80 points is many standard deviations on the IQ scale, it kind of seems like it's mostly measuring education/studying rather than something innate like "intelligence".
Replace the word "study" with the word "cheat" and it makes more sense. You aren't SUPPOSED to study for an IQ test.
What you are seeing is that if you cheat it helps a little bit. That's not an argument for OR against them in general, except maybe to say that they should be more resistant to this type of cheating.
Even if you're not explicitly "cheating", if your job is more primed around pattern recognition and the like, you might still perform better on an IQ test than someone who works driving trucks. This doesn't imply that the truck driver is inherently more stupid than the person who reads patterns all day.
About half of general intelligence is this correlation between all the different types. Modern IQ tests measure something like 15 types, and pattern recognition is one of them. It's the correlation between all the types that really matters.
It is strongly linked to career success, educational attainment, and many other things in life that are typically regarded as positive outcomes. Lower g-factors correlate strongly with poor outcomes.
Regardless of what we're measuring (and if it can be improved with various interventions) it is something we can measure, seems to be heritable, and is strongly correlated with positive outcomes.
The GP's phrasing was harsh, but he's not wrong for insisting that good and bad are not the same thing.
Below average intelligence is something that should be fixed, not celebrated, and it's not just some cute and quirky Sesame Street "We're all different, but the same" thing. It's a disorder, like Depression or Schizophrenia. It should be treated, and ideally eradicated. People who have it should not be stigmatized for it, but they SHOULD be treated and at least taught coping skills - as they would be with any other disability.
Nobody denies that psychometric 'g' exists, but there is contention about what it means. There's more than one theory here among psychometricians, including mutualism, or even (as Cosma Shalizi writes) that g is just a statistical artifact (he shows persuasively that any battery of tests you construct with the same structure as IQ tests are going to have some kind of g factor, even if the tests themselves are meaningless).
This kind of feels uncomfortably close to eugenics talking points. I'm not saying that you're suggesting we do eugenics, because I don't think that's what you're trying to say, but trying to "eradicate low intelligence from the population" feels pretty similar to the "Three generations of imbeciles are enough" point from Justice Oliver Wendell Holmes Jr.
Ultimately, I think there are more aspects of "value" than "being smart".
Very tangential, but I think a lot about how modern video compression has gotten so unbelievably good that if we went back in time with AV1 or HEVC or something, I'm wondering if we could have had passable video streaming at 240p with something like an ISDN connection.
It would be a tight fit, but I still think within feasibility. We've gotten so good at shrinking video that it kind of feels like wizardry to me. Granted, I'm not sure there existed a computer in the 90s that was powerful enough to encode or decode it.
As it turns out, the video was encoded in such a way that it could be played back using the display bandwidth of the original PC, BUT doing that encoding required a modern computer to perform in a reasonable amount of time.
Ah, just like the Amiga Juggler, was compressed on a VAX for playback on the Amiga. Full ray tracing, but the tracing and compression was Mini-computer.
Tangential to the tangent, but turbo codes/LDPC are algorithms for transmitting data over unreliable links with optimal redundancy for a target error rate. They underlie much of modern wireless data transfer, and were known to be possible since Shannon, but nobody had figured out how to actually do it in practise. When they were invented in the '90s everybody reacted with disbelief at first!
Reed Solomon codes are higher quality but much older and requires a matrix solve (LU decomposition plus yadda yadda, equivalent to inverting a matrix)
Turbo codes / LDPC are IIRC O(n) instead of O(n^2.5) or whatever the matrix turns out to be.
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Reed Solomon codes are closer to the Shannon limit but are not scalable, slower than linear and require quadratically or cubically more compute for the data.
Turbo Codes and LDPC do a shittier job but far far faster. So that makes them actually more ideal in practice even if they are worse than Reed Solomon codes.
Reed-Solomon speed varies heavily. For the common case of worst-case recovery on moderately reliable foundations (e.g., file storage on disk) with reasonably sized codes, encoding is bottlenecked by RAM/disk/network bandwidth (wherever you're writing the results), typical decoding is blind concatenation, and worst-case decoding pulls an already solved matrix decomposition out of a cache to decode at line rate as well.
There's a trick in particular that allows you to rewrite the matmuls as a sequence of vectorized XORs, processing the same number of instruction words as other implementations (give or take control flow) but doing just a stream of zero-data-dependency vectorized math with lots of execution unit support. If you're feeling fancy you can do CSE and also choose the matrix constants minimizing XOR count.
Even without that, just basic AVX2 tricks get you a few GiB/s.
Unless the more expensive matrix math you're referring to is supposed to have n be the size of the code rather than the size of the data?
> and worst-case decoding pulls an already solved matrix decomposition out of a cache to decode at line rate as well.
I think this line says everything about your assumptions.
RAID-6 or other filesystems use extremely small ReedSolomon codes so these caching methods are possible.
But let's say you have a moderately sized (well, moderate for LDPC anyway) 65535-sized Reed Solomon problem (the maximum Reed Solomon that fits in 2^16 bits). Even with just 1% redundancy that's 655 parity.
Now consider the possible errors to solve for: 20 erasures means you have ~65535 choose 20 combinations of matricies to cache.
Or roughly 10^77 matricies you need to pre solve and cache to handle 20 erasures. Aka basically impossible.
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Now if you have 40 hard drives and are dealing with 3 or 4 errors tops, well sure caching is good and solves everything.
Reed Solomon is a perfect Maximally Distance code. For small n it's perfect.
For larger or even just moderate N (kilobytes for packets), it's too unwieldy. LDPC and Turbo Codes (which are imperfect codes) fill in the gap and allow for larger sizes as long as you give up on perfection.
Hm, I think I see. You're proposing using larger codes for larger data sizes? (as opposed to, e.g., the drive case where you typically have a stripe of data and assume that the failure mode to worry about is losing a whole hard drive, spreading stripes across drives)
Interestingly, for a lot of bit flip probabilities, iterating a smaller code has little additional overhead and better error handling (lower chance of that longer message having an uncorrectable error). With a 10% bit flip chance, even a 253+2 code over GF256 looks attractive comparatively (horrible overall, but better than the proposed larger code; I think your code makes more sense in practical regimes).
Ethernet frames are in the 1500 bytes MTU region. Maybe jumbo frames in the 8000 bytes or so.
Traditionally, "Fire Codes" could provide error correction at high speed over the whole packet (https://en.wikipedia.org/wiki/Burst_error-correcting_code#Fi...), not as well as Reed Solomon (or LDPC/Turbo codes), but that should give you an idea that the 1000 to 8000 bytes of "error corrected data" is actually quite pragmatic in the real world (ie: a lot of Cisco switches or routers that rely upon Fire Codes as forward error correction).
Note: A 32-bit fire code could only protect from errors that exist ALL within a singular 32-bits "burst". Its a "bad" code but very high speed. Fire Codes can never protect against two random errors spread far away, its "purely" a burst error correction scheme.
As we look towards more recent ethernet standards (ex: 802.11), they tend to use LDPC or Turbo Codes instead. I don't know the MTU of 802.11 but I assume its also in the 1000 to 8000 bytes region.
65535-sized is the limits to Parchive, which uses 16-bit Reed Solomon. It doesn't grow quite to that size in practice, but you're still dealing with error correction (or erasure-correction) codes far larger than what happens in RAID6 or other such scenarios.
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All are pragmatic. But the region where Turbo Codes / LDPC excels at are the much much larger codes where Reed Solomon's O(n^2.5) (or something) is a disqualification. I'd imagine that if "Pararchive" were rewritten with today's technology, it'd be a Turbo Code or LDPC.
I don't see how classic RS codes could beat Turbo Codes (or LDPC). One of the key innovations of the latter is that they handle soft decoding; i.e., different levels of uncertainty of the incoming bits. It's much better to say that you're only 51% confident that a bit is 0 (when it should be 1) than 100% confident! This is especially important for analog systems (like radios) where the incoming bits naturally come with a confidence value.
There are soft versions of RS codes, but these came much later and use the same iterative techniques that Turbo/LDPC decoders use.
Turbo Codes and LDPC are provably imperfect, failing this property. However, they are very close to perfect (like 99.999999% perfect in practice).
Now the issue with Reed Solomon is that matrix factorization / effective matrix inverse. It's basically impossible to run Reed Solomon above say, 16 bits or 65536 elements or so (2 bytes at that point so 128kB). Because the matrix to solve this would be 65536 x 65536 x 2 bytes or like 8Gb or something.
Hmmm, I guess modern computers can handle 8GB lol. But you get the gist, the O(n^2) is a problem.
LDPC and Turbo Codes are linear. So a 4MB LDPC is gonna be you know... Actually possible on modern computers... While a 4MB Reed Solomon Code will need some number of exabytes to just build the damn decoding matrix. (32 bits times 4MB squared or something like that)
I wonder where you'd hit the performance limits vs the algorithmic improvements. On our family pentium 120 playing an mp3 in Winamp took 10-15% of the CPU, so I'm not sure how much headroom there'd be.
But anecdotally I'll share that one of my brother's college roomies was a consultant for RealVideo and was behind their initial codecs. He came back to them with algorithmic improvements a bit later and they just cold shouldered him saying the existing codec was good enough.
So who knows if the biz side folks at the time would have even seen value in better codecs, as unbelievable as that seems to us now in the streaming and zoom call world.
> He came back to them with algorithmic improvements a bit later and they just cold shouldered him saying the existing codec was good enough.
I was involved in dial-up era 'postage stamp' video streaming. 240 pixels in 256 colors and it felt like visiting the future. Good times :-).
> who knows if the biz side folks at the time would have even seen value in better codecs
As someone who gradually went from code to the biz side, it's pretty likely they did understand it was better (at least at some levels of 'they'). A lot of times, saying "thanks, but what we have is good enough", especially to an outside contractor, isn't a technical or value judgement. It's more of a generic 'not interested right now'.
Consumer streaming as a business didn't really happen on one linear ramp. There was a period in the mid-90s I call 'proto-streaming' where there was a lot of early-adopter excitement and experimentation; but it mostly died out and then got rebooted a few years later. Although Real Networks as company did bridge the two eras, it was rough and they survived on corporate training use cases. The streaming reboot is the ramp that can be roughly traced through to today.
The reason proto-streaming didn't take off wasn't the early codecs, although it's true they weren't good enough yet to succeed. It was that the business models, content supply and distribution infrastructure weren't able to scale yet. So, Real Network's reply may have been the polite shorthand for an internal mtg that was more like a VP ranting "That's great but I got three fires burning the building down right now - and that ain't one of 'em!"
We had video conferencing on a single BRI (128k) with g728 and h264. It was CIF resolution so yes it is possible. And with that loss free ISDN connection the experience wasn't actually that bad. Though this was in the early 2010s where there was still a surprisingly large amount of ISDN around
> Granted, I'm not sure there existed a computer in the 90s that was powerful enough to encode or decode it.
In software, quite possibly not[0].
But I'm sure we could have built hardware decoders that were up to decoding AV1 or HEVC back in the 90s no problem, had those codecs existed at the time.
[0] Somewhat later than the timeframe we're talking about, but I remember with pain the moment I realised my 600MHz Athlon, with 256MB RAM and 32MB GeForce 256 video card, was thoroughly obsolete because it couldn't decode and play the original Half Life 2 preview without stuttering, screen tearing and, indeed, crashing.
When meta released their EnCodec neural net audio compression codec I thought about how the 48khz stereo examples, compressed down to 6 kbps, sounded better than I remember streaming Internet Radio sounded like circa 2003, and would have been able to be streamed realtime, no buffering, on a 14.4 kbps dial up modem (what I was rocking at the time) with a bit of bandwidth to spare for browsin' teh warez sites and .... based on some napkin calcs and assuming a little MMX instruction magic I think completely possible to run the neural net decoder fully real-time on a period-correct AMD Athlon XP 2500+ Barton (overclocked to a 3200+ of course, as all did!).
I'm having trouble finding it but there was an article a while back comparing mp3 speed gains from hardware and software. The hardware was getting better at the pace of Moore's law but the (de)compression speeds for mp3s were far outpacing it, showing that mp3 decoding optimizations were giving orders of magnitude more speedup.
I think this is a common trend for algorithms that are in wide use, where you have Moore's law like behavior on the hardware side and then also software optimizations that give their own order of magnitude speedups.
You can technically have some then-contemporary FMV titles run on N64 with a 64MB cart. The hardware lends itself to it because it has the RSP, a secondary MIPS processor with re-programmable microcode. But the best video compression we had at the time was MPEG-2, which just wouldn't cut it.
I remember that Nickelodeon had a contest where the winner was given a videophone and was part of some gameshow. I suspect it ran on ISDN.
Edit: There was also video CD, but that was higher bandwidth than ISDN. I also used to download South Park episodes over my dialup modem. They weren't quite real time (IE, it took longer than the playback time to download,) but they were a low multiple. (IE, a 20 minute episode took ~30-40 minutes to download).
Actual video CD is over a megabit per second. If you were downloading at half real time over a modem it wouldn't have been nearly as many bits, though maybe it was still MPEG 1? A lot of south park downloads were RealVideo, two generations more advanced than VCD (and two less advanced than HEVC).
> I remember that Nickelodeon had a contest where the winner was given a videophone and was part of some gameshow. I suspect it ran on ISDN.
I won a copy of Sonic the Hedgehog in that contest! AFAIK, it was just a retail copy and a letter; the game might still be at my parents' house, but I certainly don't have the letter. I was not selected to be on the show or anything. I remember watching the scrolling rules when they were doing the promotion and writing down a couple bits of the address every time.
I've seen this in reality - compare the sound of an XM radio from 2003 to a modern one, same codec, same symbol rate, better audio quality. The same is true on digital two way radio (DMR, P25, TETRA, etc) the quality has improved because we can make the codecs do more intensive work, because the hardware is faster.
Yep, it's as simple as that: the faster the CPU (and more RAM) the better the compression. This has been known since the 80's when MPEG-2 first came out. It was designed using 1980's technology and despite its limitations has served us well, leading to digital TV and internet video.
then why is voice calling still awful? in the 90s they made advertisements for "crystal clear voices" for their mobile networks, these days it is still a pipe dream...
a) it's a legacy product that operators don't care about anymore.
b) latency is important for voice, but modern voice calls have terrible latency. POTS was digitized (for T1/PRI) with g.711 which provides a 8kHz sample rate and 13 or 14 bit samples encoded down to 8 bit. PRI lines were multiplexed one sample at a time. There's a small amount of algorithmic delay, but not much.
Modern voice calling is packetized, and most systems have packets of at least 20ms, you have more encode/decode time, you probably have a significant sampling buffer, and you may have to wait for network access, so the receiver needs to add a jitter buffer to manage that. Additionally, echo cancelation needs processing time, and it's also harder with longer latency. Some systems use longer packet times to reduce network overhead.
c) codecs: g.711 has a terrible pass band, GSM codec takes the same inputs and compresses it harder. g.722.2 (amr-wideband) is better, but it requires proper call setup and that is problematic for calls from one carrier to another. If you're calling via apps, there's potential for more flexibility, but you likely get whatever the developer thought was good enough.
That sentence kind of makes the rest of it moot, though? Everyone knows HEVC and AV1 on bare (unaccelerated hardware) is rough even on modern machines.
I don't think it does. It was only making the point that by at least one dimension it's conceivable that modern video could be sent over old connections because of modern advancement in compression.
In an alternate universe where HEVC existed in the 90's, conceivably intel could have included hardware to assist in decoding it.
h.264 is shockingly clever when you get into the nitty gritty. The core transform is a bit like a jpeg frequency transform, but is designed to run entirely in 16 bit integer maths and on 4x4 blocks. Ergo, it would run on MMX.
So, in short, probably. Particularly if you could get a hardware accelerated surface that transformed YUV into RGB.
Bill Joy once said in an interview that if you look at scientific computing it wasn't just hardware that advanced at a consistent rate, software also consistently made large speed gains over time.
Probably. I have been trying to be at least a bit more discriminating about what I complain about now. Even if the quantity of complaints is roughly the same, I at least try and direct it more towards things that deserve the complaints more.
I do think there's value in saying things that are bothering you early on, so I'm not going to say that complaining is inherently "bad", but I will acknowledge that frequent complaining (especially to the wrong people) can lead to a lot of unhappiness and dissatisfaction with your life.
I don't think over-explaining everything has negatively affected my life though.
I guess that's my ethnic group, but I don't really consider myself "German", given that I've only ever lived in the United States. I just consider myself "American".
I imagine people couldn't decide on which conjunction to use since they both work, used both incorrectly, stopped using plain "else", then started thinking they needed to prefix "or" before "else". Dictionaries then adjusted, removing the conjunction entry of "else" and adding "or else" as a conjunctive phrase.
Maybe I'm just weird, but I can't actually choose what I believe. I can choose to go to church and I can choose to say I believe and I can choose to donate money to some religious institution, but I don't think I'm capable of believing something that I think is dumb.
If you're unfamiliar, there is a lot of historical context around Pascal's Wager -
Unless you live in a brutal theocracy, it's difficult to describe just how powerful institutionalized Christianity was at the time. Likewise the scale of religion-themed violence. A couple generations before Pascal's birth (in France), the Catholic-vs.-Protestant https://en.wikipedia.org/wiki/French_Wars_of_Religion had kill off something between 10% and 25% of the population of France.
In many ways, I'd interpret the Wager as saying "if professing quiet belief in the current local orthodoxy is relatively cheap, and those not doing so are occasionally slaughtered at scale, then prudent people will parrot orthodoxy".
Pascal's Wager if you read the entire book is more intricate than choosing to believe. He also argues that by practicing as if you believed, you may feel as if the choice is true and find God that way.
Yeah but then that sort of invalidates the wager right?
The premise is that it's trivial cost to believe with very high potential reward and no downside if you're wrong. That's simply not true; if it turns out that there isn't a God, and if it turns out that there is no heaven or hell, and that this is the only life we get, then you have wasted everything for a false premise.
I see it as more of a rationalization. When you already believe something, you look for intellectual reasons to justify that belief. Pascal's Wager feel like that to me. Its main power is hardening an existing belief rather than swaying an undecided mind.
Except that 'pisteuō' means more nearly "to be faithful to" or, one could even say, to enter a type of contract (thus the Greek construct 'dia pistis', two parties relating "through faithfulness").
Anglo evangelicalism constrained its meaning to something like "intellectual assent", for its own purposes (in my opinion, it made for better sales models) some time in the nineteenth century. And as you essentially point out, intellectual assent is fairly meaningless.
That and it only really works in a system where one decision involves an infinity. Once you add a second infinity that is not aligned or is incompatible with the first it falls apart.
Tinfoil hat thoroughly fixed upon my head, but a part of me kind of thinks that this might have been a long-game from big tech in the same vein as Grapes of Wrath.
Software engineers make a lot of money, at least historically because of supply/demand mechanics. By suddenly and continuously flooding the market with lots and lots of software engineers, you effectively can bring down wages, since if people are unemployed long enough they're likely to take a lower salary.
The FAGMAN companies got caught colluding to depress wages by avoiding hiring people already employed by the others, so they learned to accomplish the same thing without writing it down by having these periodic huge layoffs across the entire industry https://en.wikipedia.org/wiki/High-Tech_Employee_Antitrust_L...
They (the industry) have always wanted to find a way to do this. Tools like Rational Rose and Visual Basic were touted as being able to do this. Sending work overseas is another way. AI is just the next in line.
I don't know what the overall answer is, but I would say that if you have high demand skills, you can still earn a living.
The 3% growth in the us market is virtually (90%+?) all in AI company valuations/investment. It is a depression, that hasnt been announced. Wait till after midterms for the blame to be leveled with the announcement.
Yep. We'll be told to argue over our collective political beliefs while corporations and billionaires continue to drive the economy for the 99% into the crapper. It's a machine that cannot stop until we all have nothing left.
If you believe in government-measured CPI, sure. No one I know (very median people) would say they’re doing better economically now than ever before. Literally zero people I know would say that.
A real GDP decline of over 10% year over year for more than 1 year is the biggest signal. Ofc, I noticed the US Federal Government has been cooking the books since at least H. W. Bush (maybe longer) by including tech stock potential gains as part of GDP. Take out tech stocks, the US economy looks like it will to historians.
Even in the modern day, an economic depression is associated with massive unemployment, deflation, reductions in the trifecta of industrial output + consumer spending + international trade, with the final kicker being reduced credit availability. Currently, interest rates are relatively high (historically middling) which has effectively restricted consumer credit, while the national credit rating has fallen.
The model is as useful as the predictions. The factor by which the GDP is boosted based on tech stocks valuations is the random factor. Including tech speculation has distorted the published GDP. Granted, tech speculation is cause for increased velocity, without commensurate production.
Modeling that the GDP goes up because people are buying bitcoin would be the equivalent of the AI investment effect. A key difference being that the AI companies are currently included in the calculation and bitcoin is not. I don't mean to imply that the AI companies are transparently ponzi schemes, but they are all massively overvalued. The net GDP effect should be very very small if not negative, while the valuations are being used to justify a growing GDP that would otherwise have obviously fallen.
If they actually had a need for those software engineers right now, they wouldn't play that game. (Or rather, if they could make more money by having them create something than they could save on wages from playing the game.)
But at that point, they almost should be laying off engineers, even without playing any such game.
It doesn't really seem like Kalshi and Polymarket have nearly the same regulation. There are plenty of cases where people are purposefully betting on the market when they can easily manipulate the results, with little/no consequences.
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