Or maybe before - with grasping digits? Hard to tell.

When you travel away from the Sun, the light from it gets dimmer and dimmer and dimmer, until it becomes single photons appearing with more and more delays but on average energy of 'dimmer' light.

Fly towards the Sun and there isn't a sudden cutoff point where it goes from dark to bright, or bright to incandescent, it's a continual increase.

Same with life, lots of people born, lots of intensity around birth and infant children and parents and education, intensity diminishes with age as people spread out and dissipate, everyone's looking back in at the source of new life while getting further and further from it and more and more separated from each other and lower energy levels and less and less 'happening'.

Singularity? Moving towards the intensity with technological development and more intricate, faster, and sheerly more connectivity all over, more encoding of ideas into information patterns.

Unless you want to imagine it like flying towards the Sun becoming falling towards the Sun, becoming a specific point where everyone burns up and dies. :/

mad scientist laugh

Some of us seek this in the attainment of Nirvana.

Tesla has a market cap larger than Ford. Tesla also has been on the edge of bankruptcy every couple years and recently raised $1 billion in capital.

Broadly, no way do I believe that many people, not even fleets, especially not individuals, will put up with the charging time of a battery powered car. It's just so darned much more convenient to fill up a 20 gallon tank with gasoline.

My guess is that the promise of electric cars was boosted by both the anti-fossil fuel push and the self-driving push. IMHO, with Trump, the anti-fossil fuel people just lost, big time, for a long time. E.g., we won't have carbon taxes, the theme will be "drill, baby, drill", and US gasoline prices are on the way down. For self-driving, my view is that the lawyers will make the insurance rates too high and more lawyers will pass some very restrictive laws. Then self-driving will be for some special cases and/or will need a lot of highway engineering that will take a lot of time and money and won't happen for years. For more, no way can Tesla do something significant that GM, Ford, Chrysler, Toyota, Honda, BMW, MB, Kia, etc. can't do just as well or better. E.g., there were electric cars ~100 years ago, and the story has been the same since then or as a Ford exec once said "You build me a good battery, and I will build you a good electric car." For a while there was some hope for a capacitor, which can be charged as fast as the electric power connection permits, but that approach seems to have flopped. Finally, I'm guessing that Musk has had a lot of subsidies, and I have to guess that Trump will turn off that faucet. Net, I see no real hope for Tesla. IMHO, Tesla is going down, soon. So, some smart and/or lucky short sellers stand to make a bundle.

This may not hold true in the near future. With charging stations capable of putting out 350kW, we will have drastically reduced charging times. [0]

> Finally, I'm guessing that Musk has had a lot of subsidies, and I have to guess that Trump will turn off that faucet.

Actually, Tesla doesn't lose much if ZEV credits go away... In fact, the way things stand, other auto manufacturers are able to fully monetize their ZEV credits, while Tesla only makes 50 cents on the dollar. [1]

[0] - https://electrek.co/2016/12/26/tesla-supercharger-v3-zev-cre...

[1] - http://www.businessinsider.com/elon-musk-trump-decision-on-e...

For self-driving, there's no way that's going to be held back once it's better than a human driver. The demand is going to be incredibly high, and insurance companies will probably charge human drivers more - they tend to be very good about accurately assessing risk and charging accordingly.

Those other car companies tend to be very lacking on the software side of things.

Have you ever driven a Tesla?

Feel free to short it, but I think it's a very bad idea.

> Have you ever driven a Tesla?

No, but I fully accept that a powerful electric car would be a total hoot to drive. So, it would be quiet, smooth as silk, and be the fastest accelerating wheel driven vehicle so far. The key, of course, has been known for 100+ years: A series wound electric motor has, from the view of the math, infinitely large torque at stall, that is, before the armature has started to rotate. Then, before the armature is rotating very fast, the torque is still very high.

Also, get to put a separate motor at each wheel and do without a transmission, drive shaft, differentials, etc. So, get rid of a lot of mechanical parts. Also get rid of the often corroded exhaust system.

The torque and power can get from a carefully designed electric motor now is astounding.

Moreover, there may be some good opportunities to adjust dynamically, many times a second, the motor torque separately at each wheel to eliminate wheel spin, which actually hurts acceleration.

Again, my main concern is charging time: E.g., for summer driving, will want A/C, and that can take a lot of power; in the winter, want heat, and that also takes power.

Do a lot of high performance driving, and a Tesla is to be regarded as a high performance car, accelerating onto Interstate highways, passing cars, trucks, farm equipment on two lane roads, driving at 90 MPH, etc., can use a lot of battery energy. Once when I drove from my home in Maryland to my office at FedEx in Memphis, I drove my Camaro nearly the whole way at about 90 MPH -- didn't get stopped. Once when I was driving at night from Maryland to Indiana to see my fiance, I drove my Firebird nearly the whole way at 90 MPH -- didn't get stopped. I was lusting for pencil beam high speed driving lights, an air horn that could be heard for miles, and a more powerful fuel pump for pulling long hills at 100 MPH at full throttle at about 5000 RPM (Camaro 396, Turbo 400 transmission, second gear, 2.56 rear axle ratio) -- did that daily driving home from the Johns Hopkins University Applied Physics Lab!

When Dad and I went fishing in Arkansas, I did the driving, before dawn, while he slept, and I put our Buick on 100 MPH and kept it there. For people driving near the Rocky Mountains, they can want a lot of battery energy to climb hills.

Mostly just for commuting to work, I've put 200,000+ miles on each of three cars, a high end Camaro, a Buick Turbo T-Type, and a slow one, an SUV.

So, to me, a car means a lot of driving, maybe fast driving. So, that would make me concerned about Tesla charging time. That a Tesla can be considered a high performance car gives me more concern about charging time if that performance were used very much, e.g., as I have used high performance cars in the past.

My other concern about a Tesla would be the lifetime of the battery after a few thousand full rechargings as might be needed for 200,000+ miles of high performance driving.

For high performance driving, I'm lusting for a supercharged Corvette, and I'm happy that all it needs for energy is premium gasoline! :-)!

But yeah, charging up mountains at 100 mph will probably give you less than 3 hours :-D

Re driving fun, the torque is great, but I think the biggest thing is 0 throttle lag. Less of a problem with a supercharger than my old twin turbo, but still not instant like this. It's worth taking on a test drive, that's what really convinced me that this was the future. That and the 0-60 times of a 7 seater on par with an M5 (at the time), and the relative mechanical simplicity, and the better marginal economics, etc.

But, the 100 KWh is 123 HP for an hour or 61 HP for 2 hours or 30 HP for 4 hours. That's not a lota juice.

Apparently gasoline, burned, releases

33.4 KWH

So, the Tesla battery has the energy of burning 3 gallons of gasoline.

If a gasoline powered car is 33% efficient, then the 100 KWH of a Tesla is about like a 10 gallon tank of gasoline.

Hmm -- my old Chevy S-10 Blazer has a 20 gallon tank for gasoline, and I can fill it in a few minutes.

But if only want to zip, the fantastic acceleration, around Manhattan a little during the week and take a 2 hour round trip to the Hamptons on weekends, then it appears that a Tesla will work!

IIRC, the time I used my Firebird to blast overnight from my place in Maryland to my fiance in Indiana, the whole trip was about 9 hours. At the speeds I was driving, I might have been using 100 HP. So, the Tesla battery might have lasted a little over an hour. On that trip, even with gasoline, I had to stop a few times. A Tesla would have been a bummer, make me late to get to my fiance, in particular, truncate my manhood -- OUCH!

Car was a Firebird 400 4 speed with, sadly, a 3.23 rear axle ratio. The first gear was 2.52, and fourth was 1.0. Bummer. Now, wisely, much wider ratios are common and more gears, e.g., in the Corvette automatic 8 gears. So, can try to compete with a Tesla for standing start acceleration but on a highway in one of the higher gears cruise along at maybe 1200 RPM and get maybe 28 MPG. Gasoline powered cars have been improving, too!

It just hit me: Maybe a Tesla is using the electric motors also for braking and, then, also charging the battery! Nice.

Trains and big boats commonly have a Diesel engine driving a generator and the generator driving electric motors -- "Look, Ma, no or a perfect transmission!". Could also have a battery in there! Use the battery around town, and charge the battery with the engine.

fully refundable deposits, whose quantity hasn't been disclosed since very early on

Unfortunately, the reality is that.... sorry... it's mostly just statistical algorithms based around regression and intermediate calculus. State-of-the-art "deep" neural networks are not really anything like the absurdly parallel, asynchronous biological networks that power our neo-cortex - rather, they're basically an application of matrix multiplication designed to "learn" a function by iteratively minimizing an error value using gradient descent. It's still very unclear what, if anything, this algorithm has in common with how a human brain actually operates. It turns out that these kind of statistical algorithms can work pretty well when you have petabytes of data to learn from. But we're still not anywhere near the unsupervised learning capabilities demonstrated by a human infant.

Not very much at all. Most psychological evidence shows that human beings seem to operate off composable, hierarchical generative models and probabilistic inference. Deep neural networks are basically just huge continuous circuit approximators.

These two things are not mutually exclusive.

8600 hours of 4k video at 60fps (i would say this is lower quality then the human eye) is 2.657 petabytes.

Thats not including the sense of touch or smell, which i am sure are comparable in the amount of data processed by a human.

We're looking at 5+ petabytes of data that a human has to learn from by age 3 - Whats wrong with taking petabytes of data in order to learn meaningful things?

They won a bunch of awards for them but most of the technologies, if they came to be, were brought to you by people other than AT&T.

Same thing with the next steps in AI. They might happen, but they aren't going to come from the companies who currently have large marketing departments looking for something to hype.

- Machine learning: "Oh, neat, what are you working on?"

- Artificial intelligence: "What do you think about the singularity?" or [rolls eyes]

- Computational statistics: "That's nice. So, how was your weekend?"

AlphaGo would be an example. It was trained by self play.

From what is really going on, nearly all of it looks like (1) in some cases a lot of new data, (2) some new, faster processor hardware, e.g., based on graphical processor units although the x86 processors are astoundingly fast anyway, able to manipulate the new data, (3) for what manipulations to do on the data, some tweaks of some of the work of L. Breiman and his CART -- Classification and Regression Trees, (4) fitting with S-shaped (neural) sigmoid functions, and (5) the radar, etc. engineering of autonomous vehicles. E.g., the neural networks might be able to simulate the operation of a neuron in a worm.

What I don't see is (A) much progress in better methods for how to manipulate the data, that is, the basic applied math and (B) progress in working with concepts and causality -- in the history of science, progress with concepts and causality did well where the new methods would need Nevada full of disk drives of data. E.g., space flight navigation is based, first, on Newton's law of gravity and second law of motion, not on fitting massive of data via deep learning.

Uh, when the AI people use classic regression analysis as in Draper and Smith, etc. and the IBM Scientific Subroutine Package, SPSS, SAS, R, etc. to find some regression coefficients, they claim that their machine learned the coefficients. Gee, I didn't see that in, say,

C. Radhakrishna Rao, Linear Statistical Inference and Its Applications: Second Edition, ISBN 0-471-70823-2, John Wiley and Sons, New York, 1967.

or Breiman's CART.

Again, the rest I see looks like hype.

E.g., it appears that there is a basic, clever, publicity, hype idea: Whenever do some technical work, give it a catchy name. Then just use the name in the hype and ignore what is really going on in any math or science.

E.g., a while back I published some work in statistical hypothesis testing that is both multi-dimensional and distribution-free. The intended use was for high quality hypothesis testing of zero day problems in computer networks and server farms. Alas, I neglected to give the work a catchy name!

The OP seemed surprised that a big, famous company might say things where they know better. Why not? Just assume that they are trying to sell something to some people with money.

Similarly for the news media: They want eyeballs for the ad revenue. That the newsies are willing to write junk to get eyeballs goes back at least to Jefferson's remarks as in

http://press-pubs.uchicago.edu/founders/documents/amendI_spe...

and are not nearly new.

We have long had a good filter to apply to the writing of the newsies: Does the writing meet common high school term paper writing standards for solid references and primary sources? Rarely is the answer yes.

My view of the printed news is that it can't compete with Charmin, not even with cheap, house-brand paper towels. For the electronic versions, they are not useful even as fire starter, shredding for cat litter, or wrapping dead fish heads -- that is, are useless.

So, don't read them.

And don't debunk them, either -- debunking wastes your time and is something the newsies long since have ignored. The newsies have no shame.

Ignore the newsies. They ignore the debunking efforts.

My startup manipulates some data, and how is from some applied math I derived. From what I've seen of AI, my work would qualify as quite good and innovative AI -- besides the work is solid theorems and proofs. Still, I see no good reason to give my work a catchy name or call it AI. E.g., I'm not trying to fool anyone. Or, why would I want to associate my good work with a lot of hype to fool people?

Besides, I'm a solo founder with a meager burn rate so that by the time I have the traction the VCs want, I will be nicely profitable with plenty of cash for growth just from retained earnings.

Or, my back of the envelope arithmetic is that with common ad rates from ad networks, a $1000 server kept half busy 24 by 7 would generate $250,000 a month in revenue. For just one server, a cheap Internet connection, just one employee, that's a heck of a profit margin and plenty of cash for 10 more servers. Half fill those, say, in two spare bedrooms I have, with some window A/C units, some emergency power supplies and an emergency generator, and I will have annual revenue more than a VC seed or Series A equity check. And, "Look, Ma, 100% owner of just an LLC and no BoD!".

Sure, once I have the traction, VCs will call me, and then I will check and tell them about all the times I sent them e-mail they ignored and explain that my plane has already left the ground, has altitude, and is climbing quickly and it's too late to buy a ticket.

Sure, I typed in all the 25,000 programming language statements myself and implemented my math derivations in 100,000 lines of typing -- lots of in-line comments! The code is all in just Microsoft's Visual Basic .NET with ADO.NET for getting to SQL Server and ASP.NET for the Web pages with IIS for the Web server plus a little open source C called with Microsoft's platform invoke.

I wrote my own Web page session state store using two collection classes and some TCP/IP sockets with class de/serialization -- sure, could have used REDIS, but my code is so short and simple writing my own was likely easier. Besides, now I'm about to copy that code, rip out most of it, and get a log file server that I will like a lot better than what I'm using now from Microsoft.

Otherwise the code looks ready for at least first production, to, say, well past $250,000 a month in revenue. At IBM's Watson lab, I wrote AI code that shipped as a commercial IBM Program Product, and what I've written for my startup is more solid (got an IBM award for some of the code I wrote in an all night session -- let one of our programmers be done in the next afternoon instead of two weeks and got a MUCH nicer result for the customers -- trick was to do some things with entry variables to keep some run-time code on the stack of dynamic descendancy).

My project needs data, and I have a lot but need to get more.

Curiously, there's some good news: My development computer was crashing about five times a day, apparently a hardware problem, maybe on the motherboard. I did mud wrestling with it and, then, shopping for parts for a new computer. But my old computer now, for no good reason, is no longer crashing! The computer has plenty of free disk space for some more data. So, for now I get to set aside all the system management mud wrestling of getting a new computer and getting all the software moved to it and running, can review the most critical parts of my code a third time, write the log server, write some code to make working with SQL Server easier, get some more data, and do an alpha test, a beta test, and get some publicity. Maybe I will even go live with my development computer, get some revenue, and get a really nice first server.

The problem is important; the math is solid; the code is solid; I suspect a lot, at least enough, people will like the results (it's intended to please essentially everyone on the Internet), etc., but no VC in the country wants anything to do with my work now. Nothing. Zip, zilch, zero.

Lesson: To VCs, nothing but nothing matters but traction.

So, the flip side of that lesson is an

Opportunity: Be a solo founder where the traction the VCs want is enough for profitability and plenty of cash for organic growth.

The founder of Plenty of Fish was a solo founder who eventually sold out for $500+ million. Some old remarks by A16Z confirm the possibility of a one engineer unicorn -- at

http://a16z.com/2014/07/30/the-happy-demise-of-the-10x-engin...

with in part

"This is the new normal: fewer engineers and dollars to ship code to more users than ever before. The potential impact of the lone software engineer is soaring. How long before we have a billion-dollar acquisition offer for a one-engineer startup? "

I agree!

I saw the need -- obvious enough. I cooked up a new solution with a new UI, UX, and some new data to be just what some new math I derived needed. Easy enough -- I've worked harder single exercises in Rudin, Principles of Mathematical Analysis. The work was easier than my Master's paper, my Ph.D., and any of the papers I've published. I wrote the code for the math and checked it various ways including with programming those calculations again in another language to check. I designed the data base tables, the Web pages, and wrote the code for the Web pages. Then the code for the session state store. Then I got sick, then got well, then my computer got sick and got well, now I'm back to progress. So far, being a solo founder, nothing particularly difficult. No reason to need a co-founder.

What is going on in such cases -- learning, neural -- is at best some applied math, but the learning, neural, and intelligence are trying to suggest, hint, hint, that the math is somehow close to what intelligent humans with biological brains do.

The effects of the hints are strong enough to give lots of newsies another of their favorite means of getting eyeballs and clicks, that is, there are big threats, the sky is falling, nearly all humans will lose their jobs, and the robots might take over as in some movies.

Yes, somewhere in a buried paragraph there maybe an admission that the learning is likely nothing like what humans, kitty cats, puppy dogs, whales, or crows do, but that disclaimter, if want to call it that, is hardly a drop of water on the hype inferno.

At one time some IBM publicity got some housewives to believe that iBM's computers were "gigantic electronic human brains".

I know; I know; such hype is not the worst problem in the world and, really, is affecting me hardly at all. But when I was in an AI group at IBM's Watson lab, still I was embarrassed to say artificial intelligence. I knew, yes, that the meaning was supposed to be just a computer doing something that would require human intelligence if a human did it, e.g., play chess well, but that the approach of the AI chess, a big tree search with alpha-beta pruning, etc., was nothing like what humans did playing chess. But with this definition some 0-1 integer linear programming for scheduling at an airline should be far above merely intelligent since it is far above what an unaided human could do -- although humans invented the applied math that is 0-1 integer linear programming.

I call the crucial core technology for my startup not AI but just some applied math. The world is awash in good applied math -- statistical hypothesis testing, the fast Fourier transform, numerically exact matrix inversion (number theory techniques), Wiener filtering, deterministic optimal control, and hundreds more -- all without a single claim of anything intelligent in any of the books, papers, courses, etc.

From what I currently understand in the CNN/deep learning arena, sigmoids are avoided in favor of RELU, due to a number of reasons, chiefly that of avoiding gradient fade during backprop.

I'm surprised that you don't mention this (or don't seem to be aware of it), though? Is this intentional, or is there another reason?

Still, my point is that I think IRRESPECTIVE of how we present it or what we do THEY will always jump to that conclusion. Remember that these are people that think vanilla programming is the work of a "computer" as opposed to it being an echo of the mind of a software engineer.

If you're thinking about conceptual reasoning vs. purely data-driven reasoning, you'd really get a lot of value from reading Ayn Rand's theory of concepts. Yes, she's very unpopular amongst modern philosophers, so all I'll say is you should read her writings and judge for yourself.

https://www.amazon.com/Introduction-Objectivist-Epistemology...

Two people used her philosophy as a basis for a book on induction and the history of the scientific method:

https://www.amazon.com/Logical-Leap-Induction-Physics-ebook/...

Here's a free taster: http://aynrandlexicon.com/book/conceptual.html

Simple economics. Volume pays more than quality.

Oh really? Where?

In more established field it tends to be that people outside the field exaggerate things because the can't put them into the context of the field i.e. they lack domain knowledge. In "tech" it seem like it's the people in the field that exaggerate things because they can't put them into the context of the world.

So the issue is not that it's getting misinterpreted due to lack of understanding. The issue there is that it's getting unscientific and politicised purposefully.

As just one simple example, good old Hekscher-Olin trade theory (a neat general equilibrium model with 2 countries, 2 goods, and 2 factors of production, capital and labor) "shows" that free trade is a good thing, leading to a Pareto improvement.

But of course, that's predicated on a whole host of assumptions that might or might not hold, and furthermore predicated on the assumption that the "winners" compensate the "losers", through redistribution.

So, the economic case for free trade more or less includes the case for redistribution and compensation of those negatively affected by it - but that's often conveniently left out by proponents.

It's not like economists don't know there are problems in distribution of wealth -- one of the most discussed papers last year (see these podcasts [1] [2]) talks about the effects of China massively expanding trade with the US in early 2000s on some parts of the country.

Pretty much everyone has known for half a century what trade does, there's a political and logistical problem in redistribution, though (counties tend to get devastated, and people don't like to move).

Interestingly, trade has extremely similar labor market effects to automation.

[1] http://www.econtalk.org/archives/2016/03/david_autor_on_1.ht...

[2] http://freakonomics.com/podcast/china-eat-americas-jobs/

Sure, the economics profession and its popularisers might be a little more incentivised by political aims and AI research and AI's hypers and commercialisers a little more by money, but both fields suffer from the fact whilst researchers agonise over tradeoffs between tractability and predictive accuracy and fitting and overfitting and wonder whether the class of problem they're looking at is even soluble, the people with the most confidence in their assertions tend to get the column inches, even if they barely know what they're talking about.

I only wonder whether it will ultimately lead to similarly widespread middlebrow dismissals[1] of the entire field of AI...

[1]for the avoidance of doubt, not an accusation I'm levelling at the poster above

The people who say economics "became religion" are usually those whose only exposure to economics is through secondhand knowledge (ie. they read about it in media) or took a handful of undergraduate classes.

Take a look at what modern economics research looks like [1]. Seriously, read __any__ of those articles and come tell me with a straight face it's not doing normal science (come up with theory, test with empirical data).

Economics is the most scientific it's ever been, most graduate curriculum, and even some undergrad, are veering towards the applied statistics arm of economics because it's what's been most successful in the last 20 years. Granted there are empirical problems in, say, macro, but that's mainly due to lack of data.

Economics is also probably the most politicized it's been in a long time at the moment, I agree with you in that. Apart from a few venues like Planet Money or Freakonomics, there isn't much pop-economics like there is pop-science in other fields like physics. Moreover, the incentive to politicize economics is much greater than other sciences.

[1] http://www.nber.org/new.html is a good place for free versions of upcoming papers.

"B. Calibration

To quantitatively decompose the contribution of different factors to the growth of shadow banks and fintech firms, we first have to calibrate the model to the conforming loan market data."

I can tell you with a straight face that is not normal science. Economists themselves increasingly recognize so-called "calibration" is a farce.

Also, by the way, you see pretty much the same type of thing in a ton of fMRI neuroscience, medical and psychology studies (even the ones you'll later see on NPR or ted talks). You shouldn't ever believe any one empirical result in basically anything except maybe CERN particle physics type work.

You should start with 'calibration' in economics. No, it is not quite what you (seem to) think it is. No, it is not quite "the same type of thing" as p-hacking and low-powered studies in psychology. (Whose poor reliability, by the way, is almost common knowledge by now.)

Look it up, and see how the sausage is made.

Because it's so easy to check those things (assuming the data is not proprietary or whatnot) I'd argue it's a much lesser problem than the "garden of forking paths" in lab experiments where it's much harder to test robustness of the result.

Moreover, I don't think anyone intelligent is foolish enough to take the coefficients in an econometric study literally; at least I would hope not.

Math checks out. No questions about that (Although there's always stories about reproducibility of results). But after that there's huge gap, when you try to extrapolate the conclusions of the model to the real world precisely due to assumptions/limitations of the model.

I am rather sceptical about this approach - it's formal to the point where "my model of my virtual world totally works due to ideal nature of this world and mathematical logic", or "we managed to fit our model to carefully selected dataset". Yes, it's formal 'scientific methodology', yes small scope research is the practical way to publish paper after paper (the only real 'currency' in scientific world), but again it seems just to be 'safe haven' for economists, when they are abstracted from real world enough to not interfere with real politics. As with biology in Darwin times, when it was fine to be clergyman and study biology (but mainly in taxonomy sense - listing all 'god creatures' and not thinking about origin of species)

Also, "The people who say economics "became religion" are usually those whose only exposure to economics is through secondhand knowledge (ie. they read about it in media) or took a handful of undergraduate classes." - yup, the same as some nobel laureates like Krugman or Hayek.

Can we agree that the state of the scientific field is as good as a decisions taken based on the achievements in this field?

Certainly not, or else climate science would still be in thorough disagreement about whether or not there's climate change and/or how anthropogenic it is.

Even if you have massive amounts of evidence pointing to something, if it goes against entrenched interests, nothing is going to be done.

Also, you need to differentiate Krugman the political commentator and Krugman the economist. He's much more of the former these days, posts labeled "wonkish" are generally from the latter. The fault is on him, though, for discrediting himself that way.

Looking at Europe - I see the decisions, policies and agreement. Looking at USA I see conscious decision to ignore the science predictions when it suits some political goals in short term and not to ignore when it's vital - like when planning military strategy in Middle East.

So I think my point still stands.

[1] http://euracoal2.org/download/Public-Archive/Library/Charts-... [2] https://www.bloomberg.com/news/articles/2016-05-16/germany-j...

Your point being?

Europe doesn't have those specific problems, but it has others.

Politicians will do whatever has political benefits to them. Economic benefits, or even reality, are purely secondary. You might get the occasional exceptionally altruistic politician, but the average one will act on his incentives.

This is why you see stuff like the Reinhart & Rogoff paper, which never passed peer review, touted for austerity politics even long after it was retracted. Austerity is popular with a part of the population and politicians will use whatever to justify whatever they're trying to do.

Judging anything on its political success is nonsense

(mind you, this was before the term "UX design" got diluted to "graphic design for webpages and buttons on touch interfaces")

The things that matter to someone who spent a lot of time in any given field are rarely the important things to anyone else.

Edit: And no it's not pronounced with a hard g but with a soft g.

(ps. I'm not a native german speaker, so sorry if I misrepresented the phrase, but this is how it was explained to me)

Steve Keene, Debunking Economics. Ignore everything but the actual arguments.

Richard Thaler, Misbehaving.

Either do something or don't. Don't waste other peoples time publishing your grandiose plans. If you want accountability, tell people you actually know, not the internet.

Not so much his fault really, but I'm a bit disappointed that this got upvoted so much.

1950-2020 (70 years) will take us much less distance.

Almost everything we're developing seems to be about information processing. If you look at the technologies that actually do things in the physical world, it seems like almost nothing has changed since the 60's. Cars, trains, bridges, rockets, sewers... all more or less the same.

- that our language about the ‘developed' vs ‘developing' world is excessively bullish about globalization while implicitly pessimistic about technology.

- that government has changed from thinking that progress can be achieved via planning, into thinking that it's more just there to watch random forces & statistics evolve the world. This change in mindset away from planning for innovation has made it impossible to achieve grandiose mission like the Apollo space missions. As a result if there is going to be a government role in getting innovation started, people have to philosophically believe again that it’s possible to plan.

- that environmentalism has induced a deep skepticism about anything involving the manipulation of nature or material objects in the real world. This skepticism explains why computer tech has been able to advance so much but not physical technology like transportation.

- that peer review and grant approval processes are too political, science has suffered because it is hard to find scientists who excel at both science and politics.

- that a shift from manufacturing to non-tradeable services has led to a political class (such as lawyers) that is weirdly immune to globalization and mostly oblivious to it.

in this podcast http://www.talkhouse.com/comedian-tim-heidecker-talks-with-a... Adam Curtis argues that we no longer subscribe to grand visions and as a result we're floundering as our internet-induced bubbles send us into every more fragmented echo-chambers

We're never going to achieve anything great again...it's the beginning of the heat-death of human progress! I think that the recent idolatry of the individual has weakened our ability to act en-mass. Previous generations were more cohesive.

WRT skepticism of modification of the natural world - it's so stupid. There is no "natural state" of things. Everything is modifying everything else. We probably even got the ideas to modify ourselves and our environment as early humans from other animals (ants & termites - cities, beavers - dams etc).

Wikipedia, the open source, and even massive online communities such as reddit are great things.

The only way to really evolve a complex system is to make a lot of small gradual changes, constantly course correcting as you go.

Case in point, all the CEOs and big-money managers who benefit from the mining and extracting businesses buy their (big) residences in pretty "natural" places, surrounded by water and lots of greenery. I'm pretty sure they and their kids don't live in the areas affected by their companies' non-natural dealings.

I disagree with that. The majority of opinions in previous generations were discounted. A small percentage of people in power said: "We want this, therefore we will have it, and the rest will be damned".

We look more at the negative effects that our overreaching plans have on groups in the minority and on the environment itself. There is no such thing as a grand vision that doesn't have an unwanted effect on some group. It's much harder to unilaterally enforce a vision when everybody gets to voice their opinion.

It's pretty bloody ironic to hear Peter Thiel say we need state planning.

A thesis like that isn't exactly career-making pop sci blockbuster material though.

While any of these is "not perfect", it's tough (at least for me) to come with something conceptually better right now.

And also, I think we have to rememeber that many of these were possible because of oil. So, I think that if we don't find a significantly better energy source, the material world will just evolve very slowly.

When I think about it, it's obvious that new stuff happens in knowledge/information space : it has a very strong innovation/energy ratio...

Cheap, safe, non-polluting, no maintenance car?

Self-driving, self-cleaning car?

Automated horse with roof and luggage compartment - no need for paved roads, muscles are quieter than engines?

That was the world before cars - it's cars and access to good infrastructure that changed the world to its current state where local businesses can't compete anymore.

We've made tremendous progress in that direction since 1960. What's your point?

> A world where you could walk to the things you need because they're close?

That's not a technology problem; much of the developed world is like that and more of the world is getting to be like it with progressive urbanization. The US made a deliberate social choice to focus on auto-centric development that inhibits that a bit in the US, but that's a social problem, not a technical one.

That it's easy to imagine things being better...

I think Elon also asked the question of what could be better than a train and threw out one possible answer: Hyperloop

Sewer? It doesn't take a lot of creativity to see how a sewer could be better. How about micro waste treatment directly inline with the sewer so now it is not carrying waste, but clean water, and just pipe it directly back in.

Whether or not it's likely we'll see AGI any time soon is, IMO, a matter of wild-ass-guessing more than anything else. There are no experts in AGI right now, only philosophers, because the field doesn't even exist. So nobody has any remotely educated guess about what algorithmic discoveries need to happen and whether they're in reach for human understanding, or when we'd have the computational power to exploit such algorithms if discovered.

All we can really say is that it's theoretically possible, we're living proof of that. Also that there must be a lot of intelligent needles in the algorithmic haystack if evolution was able to stumble across one without a clear fitness mandate to do so (most of the creatures that thrive don't have what we consider intelligence, so it's not that evolutionarily important). I'd probably bet on it being more a matter of "when?" than "if?", but I wouldn't make any assumptions about timescale other than "not this year, probably not next".

Consider things like SOAR - that was explicitly an architecture for general intelligence. Whether it was any good or not is another question - but there was an active good-old-fashioned AGI field back then.

Mind you - one of the reasons I left AI research to do web stuff from '92/'93 onwards was I was pretty sure the symbolic approaches in favour back then wouldn't scale up and that there really was only intelligence on one side of a computer screen.

1934 was a turning point in this respect, by the 1940's it wasn't a question any more of whether or not atom bombs could be created, it was more a question of 'how' than 'if'.

I dispute that this is because they don't poses intelligence. Whenever we find an animal displaying some ability we had said required intelligence — language, tool use, self-awareness, solving abstract puzzles, driving a car — we seem to change our definition of intelligence. Just like we have done with A.I., although probably because we want to eat the former and make slave labour of the latter. ;)

(Am vegetarian, please don't eat me, oh robot overlords!)

I'm in the bottom 15% of my country (UK) by income and I have access to things like: near-instantaneous hot water at all times, affordable next-day delivery services from a pocket-sized device I carry around with me, international air travel that is affordable for me, efficient fridge/freezer technology, fresh groceries from around the world at every local convenience store.

And yes things look a lot less impressive if you filter out information-technology related things. But advancements will always look less impressive if you filter out the most impressive advancements. The fact that we are close to permanently connected across geographical boundaries now isn't something to be dismissed out of hand. The level of effectiveness and miniaturisation of communications devices (e.g. 'true wireless' earphones with mobile internet) is really approaching the point of being practical telepathy insofar as it can be used.

Dude, no offense, but you're talking about the center of an empire that's literally the biggest that the world has ever seen.

That your country is wealthy and can provide for your basic necessities has more to do with this little historical fact than it does with technological advances.

That being that achieving 'technological progress' with a milestone that applies only to the super wealthy is only one part of technological progress. Bringing it to millions of people at an affordable cost is also something worth considering.

For the rest of the world… In the last 70 years, Ebloa and HIV were not only discovered but so were partial treatments; Smallpox has gone from "a vaccine exists" to "wiped out"; Rinderpest didn't have a vaccine and has been wiped out; Polio has gone from no-vaccination-possible to almost eradicated (37 cases in 2016); Guinea worm — mostly affecting the poor — has gone from multiple millions of cases per year to 25 individual cases.

For wider medicine: the first organ transplants were kidney in 1950, pancreas in 1966, heart and liver both in 1967, ovary in 2005, penis in 2014; DNA has gone from "???" to fully readable and partially editable; ultrasound, pacemakers and IVF were invented, and antidepressants have improved.

In industry, robotics relies on computer power, so I disagree with anyone who dismisses the development of computing power; likewise, telecommunications have gone from "phone calls within your town are expensive" to "let's have a live video chat across 8-time zones".

The entirety of high-temperature superconductors happened after I was born, never mind going back as far as 70 years; Kevlar, Nomex, and carbon nanomaterials were all made for the first time in the last 70 years.

The poor of the world don't have everything we have, with the exception of vaccines for illnesses we wish to eliminate, but even the stuff we discard often contains things that could not be bought at any price 70 years ago.

Step back and forget about informational technology. Look at the world of atoms, not at the world of bits.

Since the decommissioning of the Concorde, our fastest commercial means of transportation has actually been getting slower, not faster. Man hasn't reached farther out in space than the moon missions of the 1960s. The first half the of the 20th century brought us: antibiotics, electricity, automobiles, air travel, rockets, space travel, satellites, radio, reliable clean drinking water, indoor heating, laundry machines, diswashers, widespread indoor plumbing, and massive improvements in sanitation / literacy.

The second half of the 20th can't even come close to this level of technological growth.

Recent decades might a disappointment compared with the millenialist interpretation of exponential curves, but that's only the same as the disappointment a Victorian idealist might feel with the lack of stuff that happened in the twentieth century as a whole given that neither utopian socialism nor the Second Coming has occurred yet.

Not sure anybody told you to consider that.

What they did ask you to consider is that technological progress, outside of the digital realm, has been slowed down.

While 'slowed down' or 'sped up' are difficult to quantify, the fact that 3 billion human beings have gained access to smartphone technology over the last decade seems to support the idea that technological progress has in fact sped up.

Increasing air transportation speed is a very narrow application of technology and hardly constitutes a meaningful gauge of technical innovation.

No, it's just a clear indication of market efficiencies and/or better engineering.

It doesn't say anything about what the grandparent asked for: the rate and magnitude of new scientific/technologic discoveries.

That said, I would argue that medicine too has made some pretty significant advances in the 2nd half of the 20th century... mostly in surgery techniques (transplants are 2nd half 20th century), scanning techniques (NMR and CT both were 2nd half 20th century), and pharmaceuticals. Significant vaccines (polio, measles, mumps) were 2nd half of the 20th century developments. Genetic science has made huge gains as of late. Etc.

Consider the efficiencies generated by Amazon's highly automated warehouses; their level of automation wouldn't have been feasible in, say, the 60's. Substantial technological progress on multiple fronts has been required.

One reason we have stagnated can be revealed in the bias of our new language. Where we once used the terms "1st World" and "3rd World" we now use "Developed" and "Developing" -- language that is excessively bullish about globalization while implicitly pessimistic about technology.

Edit: I should be less combative and provide some actual content. Take a look at semiconductors from the 60s vs now. They are clearly related to 'the digital realm' but are purely physical technology. The fast computers we have now (which enable our digital realm) are at the tip of a screaming bullet train of physical technological progress.

Battery tech has gotten so advanced you're literally carrying around a firestorm's worth of energy in your pocket and only notice in the rare case that things go spectacularly wrong; compare that to the heavy inefficient NiCds of your parent's age.

Semiconductors are 14nm. That's not for scientists, that's not for researchers, that's for any joe that has 300 bucks. 70 years ago the idea that a pace described by Moore's law could even exist was seen with skepticism (remember it's a marketing "law" not a physical one).

We have rockets that can land themselves, cars that weigh half as much as they did 70 years ago and are twice as safe, a logistic network such that exotic foods are available year round world wide.

It just kills me to watch people post on the Internet using more than likely their mobile super computers, saying tech clearly has slown down because "they've got a feeling".

2. Technological progress is based on the outcomes they bring with them. Easy or hard to achieve -- doesn't matter in terms of this measurement. Insane advancements in physics is not technological progress unless it enables us to vastly improve our existing capabilities to do things as humans.

Thiel argues this by pointing to a tech were all excited about: self-driving cars.

Thiel argues the original invention of the car was still a bigger innovation.

electricity -> cars -> airplanes -> rockets -> space travel

radio -> tv

laundry machines -> dishwashers

antibiotics -> vaccines

^^^All first 3/4 of 20th century. Self-driving cars would be merely a close match to any one of them. For the next 50 years to match what we saw in the start of the 20th century, we are going to need at least 4 or 5 other technological revolutions in the world of atoms for the comparison to be even similar.

And that's fine. I don't think anyone is complaining today about timepieces not keeping even more accurate time. Clocks today (in whatever device they are embedded in), while not 100% accurate are pretty good. The ROI in improving them further just isn't there -- in part because the good they'd serve humanity isn't there.

And so on. Toss in a few bullet points intended to flag totalitarian/authoritarian/fascist tendencies, worker exploitation, and the like and I think that while likely not a comprehensive blueprint that's more than enough to get started. Especially considering how poorly so many industrialized, first world, "democratic" countries in the world do on so many of these basics.

That said I agree there's no ROI on improving household items like clocks. The problem is there's also no obvious ROI on resolving homelessness.

Would you know a few VCs who have lost several million or more on an investment. Do it sometime and then express your optimism for the future.

The Green Revolution was a thing. Mass starvation was prevented by technical means.

Our means of travel have also gotten vastly more efficient.

Prioritizing progress in average efficiency over speed of a showpiece that is used for a very small share of actual travel isn't the end of progress, and it is very much change in the world of atoms, not bits.

Hardly vastly. At best within an order of magnitude better, but not even close to that.

So from point of view of affordability and mobility for general public - it's good progress.

[1] https://en.wikipedia.org/wiki/Supersonic_transport#/media/Fi...

Which is consistent with the gp's point that progress has slowed down.

It had gotten 100 to 1000 times cheaper, faster, more efficient to e.g. travel intercontinentally between the 1900 to 1970 that it has between 1970 to now.

For efficiency to be considered a huge leap in progress, it needs to be a change on the order of magnitudes....

For aerospace, how about affordability of a ticket over time (Ryanair vs Concorde)? Space travel: number of journeys per vehicle or time astronauts are able to spend in space (was minutes in early space flight, unlimited now). Transportation speed is a straw-man, the industry optimises for cost not speed.

Game changer tech changes what can be imagined. Refinement tech changes what can be bought by consumers.

There's been plenty of refinement over the last few decades, but not nearly as much original game changer invention as in the previous decades.

Refinement is taking existing tech and moving it up (e.g. 10 to 30).

Thiel argues real game changer tech emerges when it brings us from 0 to 1. From nothing to something huge.

tl;dr: Indoor heating significantly predates 1900. Though relevant inventions largely predate 1900, widespread adoption was indeed between 1900 and 1950 for electrification, automobiles, air travel, radio, washing machines, and indoor plumbing. The years after 1950 include most of the developments and use of the Concorde, moon missions, antibiotics, rockets, and dishwashers. I can only describe the inclusion of "space travel" and "satellites" in a list of things from the "first half of the 20th century" as trolling. The remainder of my post is what I found for each topic.

The Concorde flew from 1969 to 2003. The last time humans traveled past low-Earth orbit was 1972. (Space exploration itself started in 1957, and since then unmanned space probes have explored no shortage of interesting targets.)

Penicillin was identified in 1928 but first made available to civilians in 1945. Of the ~50 antibiotics on the WHO Model List of Essential Medicines, I found 7 discovered before 1950: penicillin G, penicillin V, chloramphenicol, dapsone, 4-aminosalicylic acid, streptomycin, and pyrazinamide. The final one was not used until after 1950.

The basics of electricity, including arc lighting (1802), incandescent lightbulbs (1878), motors (1832 or even the 1740s?), telegraphs (1774), power stations, alternating current, etc were all invented and in use before 1900. Of course, the period of electrification in now-developed countries was roughly from the mid-1880s until around 1950.

The basics of automobiles also predate 1900, but mass production began around then. Many major developments in automobiles indeed happened between 1900 and 1950.

Air travel via balloons predates 1900 by more than a century, but both rigid airships and (controlled, powered) heaver-than-air flight developed between 1900 and 1950.

Rockets were first developed by the 13th century, and found significant and widespread military use before 1900 (eg, the Star-Spangled banner was written in 1814). Modern rocketry probably began in 1926 with the first liquid-fueled rocket launched by Goddard. Germany used the V-2 rocket throughout WWII, and this presumably is the reason for inclusion in "the first half of the 20th century".

As mentioned previously, the use of rockets for space exploration (and thus also satellites) did not begin until 1957 with the launch of Sputnik. Human spaceflight began in 1961.

Early radio predates 1900, but indeed radio largely developed between 1900 and 1950.

I had difficulty summarizing the history of water treatment; it seems that many inventions predated 1900 but indeed the period between 1900 and 1950 was the main significant period of development in the United States.

Indoor heating predates the invention of writing. Almost every development in the history and widespread use of heating predates 1900.

Washing machines predate 1900, but the development and widespread use of electric washing machines was indeed between 1900 and 1950.

Dishwashers also predate 1900. Significant aspects of their development happened between 1900 and 1950, but their widespread use was after 1950.

Indoor plumbing predated 1900 by millennia, but indeed the widespread period of adoption in the United States was between 1900 and 1950.

I do not know how to summarize the improvements in sanitation, but I would probably say that 1900 to 1950 did not feature particularly notable improvements in literacy.

The period of comparison is really the start of the industrial revolution until the 1970's. This 100 year period was dramatic, and arguably, we are not matching it right now with our rate of progress outside of information technology.

But only with two faucets.

We just can't consider them important new discoveries in the sense that the creation of things like steam engine, air travel, jet engines, etc were (to stay with transportation).

If you wish, the former are basically incremental engineering/efficiency improvements upon the latter.

What the parent observed as lacking/slowing was non-incremental improvements.

Would something like the Millau Viaduct have been possible in the 1960s?

That's two questions in one.

The crossing of large spans was a solved problem in Roman times (pillars and arches).

To do it exactly like that did not require anything new in terms of materials, but there would have been quite a problem getting such a design approved without the computational homework done that it would work well in all weather conditions. Which in turn would likely lead to it being overdesigned.

Computers are excellent at such simulations leading to a higher degree of confidence in designs that have never been tried before or that push the envelope in some manner.

I think it depends where you look at technology and how closely...

In your examples consider a modern turbofan blade, a single crystal of titanium grown in a xenon atmosphere and then heated white hot before being blown up like a balloon so as to allow refrigeration during operation! Another mind blowing sector is the change in medical scanning, ct, pet, mri - all new since 1970

For much more than half of the 20th century, nations were at war with each other, the British Empire was declining (and there had to be a replacement fitting for the times), etc. Man's taste for blood has not necessarily gone away with the 20th century, it only found expression in soft power and other psychological means of domination (e.g., Hollywood movies whose central theme is American? Exceptionalism). This fresh awareness that actionable information is what may determine the fate of nations has also polarized technological progress in favour of advancements in understanding data and processing large volumes of it in the most efficient way possible. To be fair, Claude Shannon and Alan Turing made outsized contributions to this space.

Just as there were Economic Consequences of the Peace (thanks, J.M. Keynes), I think we will also have to chronicle the The Effects of Peacetime on Technological Progress.

But a smartphone to someone from 1950? It would seem pretty fancy, but not impossible to imagine. The guy from 1950 already knows the basic tech behind it - it has a screen, it uses wireless data, and is powered by computers.

Now, we would find flying cars "nearly magical" (myself included, having been recently amazed by modern vertical takeoff fighter jets) but apparently aren't impressed by smartphones (myself not included, even before having recently learned about semiconductor fabrication techniques).

But then one day I had a profound insight: For nearly all of human history, the ONLY agent of change has been software. That is, our bodies have remained exactly the same for the last 80,000 years and the only thing that's changed is our culture, knowledge, languages, etc. We've used those changes in software and information to create new physical tools but the only thing that's taken us from the beginning to today is slow, steady improvements in software and "information processing".

I actually think that it is a high leverage phenomenon that most of our innovation is now focused much more significantly on pure information. It's hard to understand how this can't be causing acceleration in change.

You see the horses replaced with cars - what do you see of the advances in sewage management, or plastics recycling?

Also, an electric car is still a car, but it's still very different from a combustion engine, or a coal steam-engine, for that matter. Does the fact that a horse is so dissimilar to an electric/petrol car mean the two are relatively similar? That seems to be a fairly superficial distinction of change.

This is one reason why economic growth in the west is stagnant. Technological progress is what fuelled our strong growth half a century ago. Without it, politics becomes a zero sum game.

We may not be on the cusp of a singularity, but that's nothing to be ashamed of.

We should be proud we haven't seen a major world war in 70 years.

I certainly got more delta-value out of pre-web Internet (email, Usenet, chat) and Web 1.0 (online papers and libraries, nearly-free publishing) than Web 2.0 onwards (Facebook, etc). Maybe it's not accelerating constantly.

Even just the widespread use of SMS has helped medical teams assess and treat diseases in remote areas.

When people complain about some lack of technological advancements, it sounds to me like they're just not aware of what we have accomplished. And I am not surprised that Thiel is in this category. He has a JD, not a PhD

People that say that have no idea how hard it is to make a network large. The complexity of expanding connectivity is our modern feat.

but 'everyone can communicate with anyone' also meant everyone has access to FB, snapchat, worthless videos, and so on for distraction :(

Without our smartphones, spending hours tinkering would be how most people ended up spending their time. It sets one up much more so for a maker mindset over a consumer mindset.

Is it possible we just covered most of the low-hanging fruit in the 1800s and 1900s, and now the only remaining discoveries that are really ground-breaking are the really difficult ones, hence the slower rate?

More and more i feel that he PC and smartphone has just been about recreating the mainframe using smaller components.

The laser may well have been the last really new thing to come about.

For example: https://www.youtube.com/watch?v=gTAghAJcO1o

Excellent video. I highly recommend everyone working in or with IT to see it.

I think he is right.

PCs and smartphone are mostly recreating thing from the past, and not the best things either. However, this isn't because we invented everything there is to invent. It has more to do with how research in computing is currently funded and how companies approach invention and innovation.

What's "invention then"?

The mobile/tablet is truly the first "personal computer", which we've barely tapped yet. I am hopeful, but at the moment we haven't gone much beyond what we could do with very efficient punch card sorting.

I don't think this is foolproof, but it _is_ a tool and a perspective for analyzing history, and one that runs counter to the most common narrative of increasing acceleration in technological development. The physics way of saying this is that velocity is always positive (we're always going up or near-neutral) but the rate of acceleration isn't spectacularly greater than the new ones. If we really are talking about the rate of change of economic/tech growth (the rate of change of market size/capability), then we're talking about acceleration!

Anyway, this was a whole rant, but my personal take is that we tend to underestimate the amount of turbulence in history, leading us to believe that the past was a stable, peaceful and simpler time, while the present day is going nuts. This kind of thinking has fueled messianism, apocalyptic cults, futurism, dreams and nightmares for centuries, and will continue to if we don't blow ourselves up. We forget that even in places like Ancient Rome the rate of change in tech and human growth was still positive and rapid, that during the Dark Ages science and technology were still exploding in the Middle East, that the differences between 1650 and 1750 were vast in terms of human thought, that between 1850 and 1950 they were seemingly greater. There was no time of mythological stasis before the present day, and it's unlikely that there ever will be as long as we're still human.

[0] https://en.wikipedia.org/wiki/Kondratiev_wave

Here's some fruit that looks low-hanging today relative to its value: atomically precise manufacturing. http://www.foresight.org/roadmaps/Nanotech_Roadmap_2007_main...

And medicine, and materials, and semiconductors (this board in particular loves to forget that these computers we all use are built on top of something), and antennas; the list goes on. What was once highly theoretical phd knowledge is now a byline in a junior level microelectronics course; the cutting edge having evolved to be unrecognizable to a person 60 years ago. It took us 40 years to go from a computer that could play chess to a computer that could win; took less than twenty to go from winning chess to winning Go (and exponential jump in complexity). In the same amount of time we've gone from mapping the human genome to editing it. Rechargeable battery technology that could power a vacuum for 30 minutes to driving a car for 400 miles.

Never forget that exponential change looks linear on the small scale.

For instance, let's say you have a small circle with a small bump on it. The circle represents current technology, and the bump is a change in technology (i.e. innovation).

Now take a much larger circle that has many small bumps on it. The bumps look tiny in comparison, but in aggregate, they are much larger than the bump from the smaller circle. In fact, at some point, they will be bigger than the old circle, even though it just looks like an un-smoothed circle.

Further, 60 years ago we were coming out of wartime, which meant that many innovations were able to come to market in a short period of time (they had been held up do to wartime limitations like rationing, material shortages, etc.)

This is why I think Thiel is wrong.

http://matt.might.net/articles/phd-school-in-pictures/

Does this compare favorably to internal combustion or indoor plumbing? Seems to me that it does.

And AI is a huge force multiplier in all of these abilities.

That said, for most of the arguments that modern-day thinkers talk about, accelerating technological progress is totally irrelevant. You're most likely thinking of Kurzweil's school of thought around a singularity, which is nowadays far from the "norm".

If you're talking about the arguments around technological unemployment, it doesn't matter if tech is accelerating - we could, for example,, over the course of the next e.g. 30 years, replace 50% of human jobs. This might be "slower" in some sense than previous tech changes, but it doesn't change the bottom line. (note: these are made up numbers to illustrate a point, I have no good guess at the real numbers, but lots of smart people, including economists, think it's a problem we will face soon-ish).

If you're talking about the arguments around "unfriendly AI", then again, it is totally immaterial wether tech in general is accelerating. All that you need to believe in order to worry is that eventually, at some point, we will be able to create a machine that thinks, and it is not automatically guaranteed to share our values.

I wish this were true, but it's gotten a new lease on life with Nick Bostrom's book and the various high-profile people who have been influenced by it (like Elon Musk and Bill Gates), so there's a bit of a boomlet around singularity speculation again.

At a hackathon recently, someone pitched their app as an "ML-driven app" though the only ML in there was some 1-line language translation feature they were consuming off Watson REST services for a tangential feature on their app.

Meanwhile, my submission actually used a self-trained CNN on a custom dataset using TensorFlow and changes to start/end layers on the NN. The image classification features were the core of the app and it wasn't something that was just a wrapper over an Off-the-shelf API. We actually tried multiple networks and went thru the trouble of parameterizing everything.

At the end, I wonder how many judges actually understood the difference in effort/value to the two attempts at ML.

Difficulty level 2: Self-trained CNN on a custom dataset using TensorFlow and changes to start/end layers on the NN

Difficulty level 3: Custom rolled 12 layer CNN trained with with novel hand labeled data.

How many people to you think know the difference between these and the fact that each step is a magnitude or more harder than the last? That's not even getting into trying to apply research grade stuff.

talk about dreamland autoaim