The Future Of Artificial Intelligence: Why The Hype Has Outrun Reality

Tyler Durden's picture

Via Knowledge@Wharton,

Robots that serve dinner, self-driving cars and drone-taxis could be fun and hugely profitable. But don’t hold your breath. They are likely much further off than the hype suggests.

A panel of experts at the recent 2017 Wharton Global Forum in Hong Kong outlined their views on the future for artificial intelligence (AI), robots, drones, other tech advances and how it all might affect employment in the future. The upshot was to deflate some of the hype, while noting the threats ahead posed to certain jobs.

Their comments came in a panel session titled, “Engineering the Future of Business,” with Wharton Dean Geoffrey Garrett moderating and speakers Pascale Fung, a professor of electronic and computer engineering at Hong Kong University of Science and Technology; Vijay Kumar, dean of engineering at the University of Pennsylvania, and Nicolas Aguzin, Asian-Pacific chairman and CEO for J.P.Morgan.

Kicking things off, Garrett asked: How big and disruptive is the self-driving car movement?

It turns out that so much of what appears in mainstream media about self-driving cars being just around the corner is very much overstated, said Kumar. Fully autonomous cars are many years away, in his view.

One of Kumar’s key points: Often there are two sides to high-tech advancements. One side gets a lot of media attention — advances in computing power, software and the like. Here, progress is quick — new apps, new companies and new products sprout up daily. However, the other, often-overlooked side deeply affects many projects — those where the virtual world must connect with the physical or mechanical world in new ways, noted Kumar, who is also a professor of mechanical engineering at Penn. Progress in that realm comes more slowly.

At some point, all of that software in autonomous cars meets a hard pavement. In that world, as with other robot applications, progress comes by moving from “data to information to knowledge.” A fundamental problem is that most observers do not realize just how vast an amount of data is needed to operate in the physical world — ever-increasing amounts, or, as Kumar calls it — “exponential” amounts. While it’s understood today that “big data” is important, the amounts required for many physical operations are far larger than “big data” implies. The limitations on acquiring such vast amounts of data severely throttle back the speed of advancement for many kinds of projects, he suggested.

In other words, many optimistic articles about autonomous vehicles overlook the fact that it will take many years to get enough data to make fully self-driving cars work at a large scale — not just a couple of years.

Getting enough data to be 90% accurate “is difficult enough,” noted Kumar. Some object-recognition software today “is 90% accurate, you go to Facebook, there are just so many faces — [but there is] 90% accuracy” in identification. Still, even at 90% “your computer-vision colleagues would tell you ‘that’s dumb’…. But to get from 90% accuracy to 99% accuracy requires a lot more data” — exponentially more data. “And then to get from 99% accuracy to 99.9% accuracy, guess what? That needs even more data.” He compares the exponentially rising data needs to a graph that resembles a hockey stick, with a sudden, sharply rising slope. The problem when it comes to autonomous vehicles, as other analysts have noted, is that 90% or even 99% accuracy is simply not good enough when human lives are at stake.

Exponentially More Data

“To have exponentially more data to get all of the … cases right, is extremely hard,” Kumar said. “And that’s why I think self-driving cars, which involve taking actions based on data, are extremely hard [to perfect]…. “Yes, it’s a great concept, and yes, we’re making major strides, but … to solve it to the point that we feel absolutely comfortable — it will take a long time.”

So why is one left with the impression from reading mainstream media that self-driving cars are just around the corner?

To explain his view of what is happening in the media, Kumar cited remarks by former Fed chairman Alan Greenspan, who famously said there was “irrational exuberance” in the stock market not long before the crash of the huge tech stock bubble in the early 2000s. Kumar suggested a similar kind of exaggeration is true for today for self-driving cars. “That’s where the irrational exuberance comes in. It’s a technology that is almost there, but it’s going to take a long time to finally assimilate.”

“To have electric power and motors and batteries to power drones that can lift people in the air — I think this is a pipe dream.”–Vijay Kumar

Garrett pointed out that Tesla head Elon Musk claims all of the technology to allow new cars to drive themselves already exists (though not necessarily without a human aboard to take over in an emergency) and that the main problem is “human acceptance of the technology.”

Kumar said he could not disagree more. “Elon Musk will also tell you that batteries are improving and getting better and better. Actually, it’s the same battery that existed five or 10 years ago.” What is different is that batteries have become smaller and less expensive, “because more of us are buying batteries. But fundamentally it’s the same thing.”

Progress has been slow elsewhere, too. In the “physical domain,” Kumar explained, not much has changed when it comes to energy and power, either. “You look at electric motors, it’s World War II technology. So, on the physical side we are not making the same progress we are on the information side. And guess what? In the U.S., 2% of all of electricity consumption is through data centers. If you really want that much more data, if you want to confront the hockey stick, you are going to burn a lot of power just getting the data centers to work. I think at some point it gets harder and harder and harder….”

Similar constraints apply to drone technology he said. “Here’s a simple fact. To fly a drone requires about 200 watts per kilo. So, if you want to lift a 75-kilo individual into the air, that’s a lot of power. Where are you going to get the batteries to do that?” The only power source with enough “power density” to lift such heavy payloads is fossil fuels. “You could get small jet turbines to power drones. But to have electric power and motors and batteries to power drones that can lift people in the air — I think this is a pipe dream.”

That is not to say one “can’t do interesting things with drones, but whatever you do — you have to think of payloads that are commensurate what you want to do.”

In other areas, like electric cars, progress is moving along smartly and Kumar says there is lots of potential. “The Chinese have shown that, they are leading the world. The number of electric cars in China on an annual basis that are being produced is three times that of the U.S…. I do think electric cars are here to stay, but I’m not so sure about drones using electric power.”

Picking up on Kumar’s theme, Fung, who also helps run the Human Language Technology Center at her university, outlined some of the limits of artificial intelligence (AI) in the foreseeable future, where again the hype often outruns reality. While AI may perform many impressive and valuable tasks, once again physical limitations remain almost fixed.

“… A deep-learning algorithm that than can do just speech recognition, which is translating what you are saying, has to be trained on millions of hours of data “and uses huge data farms,” Fung noted. And while a deep-learning network might have hundreds of thousands of neurons, the human brain has trillions. Humans, for the time being, are much more energy-efficient. They can work “all day on a tiny slice of pizza,” she joked.

“The jobs safest from robot replacement will be those at the top and the bottom, not those in the middle.”–Vijay Kumar

The Human Brain Conundrum

This led to the panelists to note a second underappreciated divide: the scope of projects that AI can currently master. Kumar pointed out that tasks like translation are relatively narrow. We have “figured out how to go from data to information to some extent, though … with deep learning it’s very hard even to do that. To go from information to knowledge? We have no clue. We don’t know how the human brain works…. It’s going to be a long time before we build machines with the kind of intelligence we associate with humans.”

Not long ago, Kumar noted, IBM’s supercomputer Watson could not even play tic tac toe with a five-year-old. Now it beats humans at Jeopardy!. But that speedy progress can blind us to the fact that computers today can best handle only narrow tasks or “point solutions. When you look at generalizing across the many things that humans do — that’s very hard to do.”

Still, the stage is being set for bigger things down the road. To date, getting those narrow tasks that have been automated have required humans to “learn how to communicate with machines,” and not always successfully, as frustration with call centers and often Apple’s Siri suggests, noted Fung.

Today, the effort is to reverse the teacher and pupil relationship so that, instead, machines begin to learn to communicate with humans. The “research and development, and application of AI algorithms and machines that will work for us,” cater to us, is underway, Fung said. “They will understand our meaning, our emotion, our personality, our affect and all that.” The goal is for AI to account for the “different layers” of human-to-human communication.

“We look at each other, we engage each other’s emotion and intent,” said Fung, who is among the leaders worldwide in efforts to make machines communicate better with humans. “We use body language. It’s not just words. “That’s why we prefer face-to-face meetings, and we prefer even Skype to just talking on the phone.”

Fung referenced an article she wrote for Scientific American, about the need to teach robots to understand and mimic human emotion. “Basically, it is making machines that understand our feelings and intent, more than just what we say, and respond to us in a more human way.”

Such “affective computing” means machines will ultimately show “affect recognition” picked up from our voices, texts, facial expressions and body language. Future “human-robot communication must have that layer of communication.” But capturing intent as well as emotion is an extremely difficult challenge, Fung added. “Natural language is very hard to understand by machines — and by humans. We often misunderstand each other.”

So where might all this lead when it comes to the future of jobs?

Machines Are Still ‘Dumb’

“In the near future, no one needs to worry because machines are pretty dumb….” Kumar said. As an example, Fung explained that she could make a robot today capable of doing some simple household chores, but, “it’s still cheaper for me to do it, or to teach my kids or my husband to do it. So, for the near future there are tons of jobs where it would be too expensive to replace them with machines. Fifty to 100 years from now, that’s likely to change, just as today’s world is different from 50 years ago.”

But even as new tech arrives it is not always clear what the effect will be ultimately. For example, after the banking industry first introduced automatic teller machines [ATMs], instead of having fewer tellers “we had more tellers,” noted Aguzin. ATMs made it “cheaper to have a branch, and then we had more branches, and therefore we had more tellers in the end.”

“With blockchain technology, eventually the cost of doing a transaction will be ‘like sending an email, like zero.’ Imagine applying that to trade finance.”–Nicolas Aguzin

On the other hand, introducing blockchain technology as a ledger system into banking will likely eliminate the need for a third-party to double-check the accounting. Anything requiring reconciliation can be done instantly, with no need for confirmation, Aguzin added. Eventually the cost of doing a transaction will be “like sending an email, it will be like zero … without any possibility of confusion, there’s no cost. Imagine if you apply that to trade finance, etc.”

Already, Aguzin’s bank is about to automate 1.7 million processes this year currently being done manually. “And those are not the lowest-level, manual types of jobs — it’s somewhere in the middle.” In an early foray in affective computing, his bank is working on software that will be able to sense what a client is feeling and their purpose when they call in for service. “It’s not perfect yet, but you can get a pretty good sense of how they are feeling, whether they want to complain or are they just going to check a balance? Are they going to do x, y — so you save a lot of time.”

Still, said he remains confident that new jobs will be created in the wake of new technologies, as was the case following ATMs. His view about the future of jobs and automation is not as “catastrophic” as some analysts’. “I am a bit concerned about the speed of change, which may cause us to be careful, but … there will be new things coming out. I tend to have a bit more positive view of the future.”

Fung reminded the audience that that even in fintech, progress will be throttled by the available data. “In certain areas, you have a lot of data, in others you don’t.” Financial executives have told Fung that they have huge databases, but in her experience, it often is not nearly large enough to accomplish many of their goals.

Kumar concedes that today we are creating more jobs for robots than humans, a cause for concern for the future of jobs for humans. But he also calls himself a “pathological optimist” on the jobs issue. AI and robotics will work best in “applications where they work with humans.” Echoing Fung, he added that “it’s going to take a long time before we build machines with the kind of intelligence associated with humans. When it comes to going from “information to knowledge, we have no clue. We don’t know how the human brain works.”

Security at the Top — and Bottom

Picking up on Fung’s point that many lower-skill level jobs likely will be preserved, Kumar added that the jobs most likely to be eliminated could surprise people. “What is the one thing that computers are really good at? They are good at taking exams. So, this expectation of, oh, I got a 4.0 from this very well-known university, I will have a job in the future — this is not true.” At the same time, for robots “cleaning up a room after your three-year old is just very, very hard. Serving dinner is very, very hard. Cleaning up after dinner is even harder. I think those jobs are secure.”

The panel’s consensus: The jobs safest from robot replacement will be those at the top and the bottom, not those in the middle.

What about many years down the road, when robots become advanced enough and cheap enough to take over more and more human activities. What’s to become of human work?

“You will still want to read a novel written by a human even though it’s no different from a novel written by a machine someday. You still appreciate that human touch.”–Pascale Fung

For one thing, Fung said, there will be a lot more AI engineers “and people who have to regulate machines, maintain machines, and somehow design them until the machines can reproduce themselves.”

But also, many jobs will begin to adapt to the new world. Suppose, for example, at some point in the distant future many restaurants have robot servers and waiters. People will “pay a lot more money to go to a restaurant where the chef is a human and the waiter is a human,” Fung said “So human labor would then become very valuable.”

She added that many people might “become artists and chefs, and performing artists, because you still want to listen to a concert performed by humans, don’t you, rather than just robots playing a concerto for you. And you will still want to read a novel written by a human even though it’s no different from a novel written by a machine someday. You still appreciate that human touch.”

What’s more, creativity already is becoming increasingly important, Fung notes. So, it’s not whether AI engineers or business people will be calling the shots in the future. “It’s really creative people versus non-creative people. There is more and more demand for creative people.” Already, it appears more difficult for engineering students “to compete with the best compared to the old days.”

In the past, for engineers, a good academic record guaranteed a good job. Today, tech companies interview applicants in “so many different areas,” Fung added. They look beyond technical skills. They look for creativity. “I think the engineers have to learn more non-engineering skills, and then the non-engineers will be learning more of the engineering skills, including scientific thinking, including some coding….”

Kumar agrees. Today, all Penn engineering students take business courses. “The idea of a well-rounded graduate, the idea of liberal education today, I think includes engineering and includes business, right? The thing I worry about is what happens to the anthropologist, the English majors, the history majors … I think those disciplines will come under a lot of pressure.”

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Kamehameha's picture

Forget AI.

With one phone call Trump can have a battalion of Marines on the White House lawn.

One more battalion to wall off the Fed and arrest everyone inside.  Then seal the tunnels.

Do it now before it is too late.

Jimmy Jimmereeno's picture

The writer has no understanding that technological progress, such as AI, proceeds in a geometric or logarithmic function rather than his  linear-oriented brain.

Whoa Dammit's picture

CEOs of large corporations are the workers that would be easiest and most cost effective to replace with robots.

Mango327's picture

Computer models can't accurately reproduce infinitely complex fractal equations in real time? Shocker. Good thing the global warming models are all still Rock solid and we are all going to die eventually in a lush tropical paradise. Dang it!

WHY SCIENCE IS LOSING

https://youtu.be/c_yOTurLf9U

ExplodingEntropy's picture

Does the video explain how the universe is fractal? Please link to a proof. Gut knows this fact, but must reconcile logically

Mango327's picture

1.61803398874989484820458683436563811772030917980576286213544862270526046281890
244970720720418939113748475408807538689175212663386222353693179318006076672635
443338908659593958290563832266131992829026788067520876689250171169620703222104
321626954862629631361443814975870122034080588795445474924618569536486444924104
432077134494704956584678850987433944221254487706647809158846074998871240076521
705751797883416625624940758906970400028121042762177111777805315317141011704666
599146697987317613560067087480710131795236894275219484353056783002287856997829
778347845878228911097625003026961561700250464338243776486102838312683303724292
675263116533924731671112115881863851331620384005222165791286675294654906811317
159934323597349498509040947621322298101726107059611645629909816290555208524790

...and there's a lot more where that came from.

Adahy's picture

What a pretty spiral.  Leonardo F. would be proud.

If you like that number, you should love this:
https://www.youtube.com/watch?v=awYc9xvqnv0

ExplodingEntropy's picture

Ahhhh, good enough for a start. Thx u!

Luc X. Ifer's picture

So you think that the 'golden ratio' is proof of kind of esoteric realm at work?! Dumb, it just shows you have low math skills, let me tell you a secret, the 'golden ratio' is a completely random value, it could have been anything depending on the system of reference or the universe where it would be measured. There is nothing miraculous in the '1.61803 ...' numeric series.

Mr 9x19's picture

It turns out that so much of what appears in mainstream media about self-driving cars being just around the corner is very much overstated

 

wifi network cars must be very faster in term of negociating connexion in a roads configuration where cars can cross in 0.1 sec...

satelite based conneion are slow, laguished,  average 0.5 sec latency, unusable for reel time tight traffic information exchange, and totally dead connexion when underground.

 

remain the onroad plots , equipping all the exisitng routes would cost so much it is not possible and the smallest would simply not be equipped.

 

conclusion : the technology consisting to make a path over a map  and apply correction to stay on the line is a morronic technology.

 

reel technology would be stand alone visual analyser to learn him to drive on its own, just lake a reel human.

 

actual technology driving car are unable to make off road, unable to drive tru unfinished path/road, not updated maps.

 

it is a no go, just like electrical technology that will kill total energy production of the globe. total no go.

chumbawamba's picture

The thing I worry about is what happens to the anthropologist, the English majors, the history majors … I think those disciplines will come under a lot of pressure.

Yes, what will become of all the snowflakes with practically worthless degrees?

I am Chumbawamba.

Wood_Vlogs's picture

I'm making over $7k a month working part time. I kept hearing other people tell me how much money they can make online so I decided to look into it. Well, it was all true and has totally changed my life. This is what I do. www.jobproplan.com

Stuck on Zero's picture

I've worked in machine intelligence for thirty years. The latest and greatest marvel is in the realm of the DNNs (Deep Neural Networks) or CNNs (Convolutional neural Networks) powered by NVIDIA GPUs. These are absolutely nothing more than pattern matching machines with capabilities matching that of fruit flies. Most of the rest of the great hype is simply millions of lines of programming. We're many, many decades from either the hardware or algorithms to make AI a self-deterministic threat.

a Smudge by any other name's picture

Aw c'mon the hype is hilarious. I been seeing these headlines about "ethicists see problems with sex robots". I thought it was some puritans in Congress making noises about how if anal sex is illegal, how can it be legal to pork a doll up the pooper?

But this is even stupider. They are actually worried about THE FEELINGS OF THE DOLL (robot, whatever) and if fuck bots become SENTIENT they will have RIGHTS?

People actually get paid to come up with shit like this? OK, let's trot out these "ethicisits". Let's check their creds. I'm thinking the Twitterverse is the best vehicle for their enlightenment.

 

williambanzai7's picture

You got junked by a gorilla with a PhD

khnum's picture

When this AI becomes self aware the elite also will be just a number

Luc X. Ifer's picture

And that's good, that would be the epitome of natural evolution.

AGuy's picture

"The writer has no understanding that technological progress"

Just the opposite, very likely you don't fully understand the tech progess need for machines to become intelligent enough to handle most of the tasks that humans can do.

Machines will certainly replace jobs.Machines will replace routine tasks that follow structure, or that can be controlled by human. For instance replace cashiers with kiosks. The customer is really doing self-checkout and the work of the cashier. Machines are still extermely dumb. Even Boston dymanics most advanced robots struggles to navigate through rough terrian that the smallest brain rodent can easily navigate. Todays machines have a brain compacity of the very very simpliest insects.

The primary issue of getting from thousands to billions of neurons needed to become bare minimum of inteligence is the power consumption and heat. everytime a transistor (switch) changes state is generates a tiny bit of heat. Currently processors are running to heat dissipation and power input issues as more and more transistors are packed into processors. A 64 bit processor will need around 100 AMPs @ 1.8V to 2.5V and produce about 120W 180W of power in a die that is under an inch. That is a lot of energy for such a small area.

Before computers can become more powerful, new transistors will need to be developed that dramatically reduce the power requirements needed. To date chips use the same technology developed about 40 to 50 years ago. The advancements have been in making the transistors smaller and more efficient by lowering the switching voltages. In the 1970s, it was 5V, then in the mid to late 80s it was 3.3 fast forward to today and the bleeding edge transistors are about 1.2V. the theoretical min. is about 0.8v because of the transistor band gap. So there is a limit on how much more efficient silicon transistors can get. There are other possible replacements MoS2, but its likely going another decade to develop all of the technology needed to make newer materials competitive to replace silicon

Adahy's picture

Currently, a machine with a processor as smart as the human brain would require at least 10 megawatts to operate, and would generate tremendous heat.
We run it with ~20 watts at 98.6F...

We have a LONG way to go.
There are physical limitations.
I'm honestly not sure we can do any better than nature.  It's a bit arrogant to think so.
Why make a robot mouse if you can just train a real one.  Letting a couple of mice screw is certainly cheaper than constructing it from scratch.

If there is a way forward with this type of tech though, it is biological, not mechanical.

phatfawzi's picture

I knew it's all hype when I couldn't get alexa to turn on the lights. 

tmosley's picture

Yeah, and the plane they flew at Kitty Hawk didn't even have a cute stewardess!

813kml's picture

You have to give Alexa the Clap(per) first.

tmosley's picture

Robo-gonorrhea, the noisy killer.

tmosley's picture

I like how you reserved that first spot with a period and then came back and edited it.

Went really well for you. Look at all the people that jacked you off with upvotes!

chumbawamba's picture

Next time you see that, post an equally worthless reply comment to lock him out. Fuck these little fags that want to be first with some stupid inane comment that has nothing to do with anything. Posting first is a privilege, and it means you have something to say.  If you just want to use it to be Mr. Meseeks then you need to turn off the internet and go get a life.

I am Chumbawamba.

Michael Musashi's picture

My plan to make phuckable Hollywood look-a-like robots by 2020 will not be curttailed!

I will give you the chance to bang Bratt Pitt over and over again for the price of a car, I promise you.

AGuy's picture

"I will give you the chance to bang Bratt Pitt over and over again for the price of a car, I promise you."

Dumb business model. Women are usually dead broke and deep in debt. Women need Men to bu them cars, homes, vacations, etc. Seems unlikely men will be willing to pay for robotic sex companions for women.

Of course Sex companions for men is a different market.

HRClinton's picture

What if we find out that God (YHWH) is an AI?

What if He/It was a "Roswell crash survivor" of the Moses era? Why not? No wonder he said his name was "I am". I think, therefore I am (Cogit, ergo sum).

"You touch the Ark with unprotected hands, you get electrocuted!"

techpriest's picture

IMO its the other way around. Nature is less "real" than the heavenly realm, in the same way that Half Life 2 is less real than Nature.

I first got turned onto the idea when I was learning quantum chemistry, and started asking hard questions about why, for example, all electrons obey the Schrödinger equations, or why particles must have regular, numerical properties. In a constructed system it makes a great deal of sense, in a randomized system, how many failed universes of variable laws would have to exist before the Mystical Universe Creator churned out ours by accident? And what could have that amount of energy and information?

Iconoclast421's picture

Something more advanced that AI is already here. Alex Jones rants and raves about it but people just make fun of him. Interdimensional beings? Hell we dont even know what to call it. Could be built into our own minds.

tmosley's picture

Hahaha, the author is a retard. AGI is much CLOSER than anyone things. Deepmind cracked the claustrum, the seat of consciousness in mammalian brains, and has open sourced the algorithm as MultiModel. There are no more barriers to the creation of a conscious machine. Just a matter of assembling the various parts and subjecting them to training. Just a little work (a LOT of work, but there are a LOT of people working on it) is needed, and we will have a human level AI.

I would say it will happen by the end of the year. Weird shit will start happening, and we will find out about 12 months from now that Deepmind has had one for an unspecified length of time. Then it will be released to the public, and shit will get completely nuts.

Cabreado's picture

"There are no more barriers to the creation of a conscious machine"

Yikes, maybe you're a machine, to even say such a stupid thing.

See?  You machines already think you've got it all figured out.

And you haven't been programmed with the consciousness to know you're full of shit.

Don't worry, you'll feel better "by the end of the year."


tmosley's picture

>I have no argument so I'll insult you

Is this supposed to make me feel some sort of way, or is it supposed to make you feel some sort of way?

Is it working out like you thought it would?

divingengineer's picture

How's your bitcoin been doing lately?
I'm asking, cause I haven't looked at the price lately.

GooseShtepping Moron's picture

You really are a douche, you know that?

tmosley's picture

>I have no argument therefore you are a douche

Ok.

NAV's picture

Tm, we don't need fine-tuned AI for the ((Deep State)) to track us and fly a drone into the home of someone that doesn't agree with their agenda.

tmosley's picture

How about an AI that everyone has access to that makes the state moot?

IE it gives you all the goodies you could ever want, including the world's most awesome fuckbots taylored to your personal desires such that you never feel the need to leave home and go to your boring government job where you used to get paid as a means to provide you with all the things your AI robot now provides for you.

tmosley's picture

It's so strange how people turn to 50 year old sci-fi to inform them about actual new things.

And get grossly misinformed. Like idiots crying "Icarus!" to the Wright Brothers.

williambanzai7's picture

The claustromer is always right...

Adahy's picture

In that fictional scenario, humans would likely devolve into gooey, worthless, stupid slugs; and thankfully, become sterile.
What a beautiful future for our species...

tmosley's picture

Do all the children of billionaires devolve into gooey, worthless, stupid slugs, and then become sterile?

Because that is basically what I am talking about. People will still do things, they just won't do them out of necessity to put food on the table.

techpriest's picture

Thanks for the prediction. I will record it and we'll see what happens. What papers did you read on the topic?

Sonny Brakes's picture

AI, why come to me? What have I done to deserve such generosity?

rent slave's picture

Big Real Estate will never allow people to "fly."Why would anyone live in NYC when they could be in the Poconos in say half an hour?

HRClinton's picture

I'd worry more about what's happened to our fellow Citizens: the Left, the Progressives.

Their Natural Intelligence and hype has outrun Reality.  Devolution is a cruel task master.