The Next Wave
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"What worries me about the future of Silicon Valley, is that one-dimensionality, that it's not a Renaissance culture, it's an engineering culture. It's an engineering culture that believes that it's revolutionary, but it's actually not that revolutionary. The Valley has, for a long time, mined a couple of big ideas."
You can really see how he is referring to the some of the earlier generation that was more influenced by the 60's counterculture movement. For myself I'm not so sure, because I think there is a danger in being nostalgic when comparing the accomplishments of the past with today. But again I think he's a great writer and I loved the quote from Kahneman about "the robots are going to come just in time"
- Alan Kay
Easy money makes for laziness. When google hit big they entered a tight market during an economic downturn. That's also when amazon started hitting its stride. But there is so much potential right now for easy money in tech that I suspect it'll be a long time, if ever, before economic pressures force a serious drive for innovation.
But there's also a huge need for real innovation. Mobile devices are still largely consumption rather than creation devices, for example, though they have no shortage of capability. And there's a huge need for fundamental research into programming languages, operating systems, and especially software development as an activity (what works, what doesn't, in which situations and circumstances, and why, etc.) Consider, for example, how utterly lacking in universally acknowledge best practices is the development of firmware with potential safety implications.
Engineering cultures can be revolutionary even if the core ideas are the revolution. The startup community knows this well as it is repeated ad naseum - ideas are worthless (mostly), and its largely about the execution. Calling a cab from a phone is not new or original. Uber didn't think of it nor did they execute it first or probably even technically best. But their combination of technical execution and business acumen allowed them to raise shit tons of money, aggressive loss lead into users and grow internationally rapidly. And Taxis drivers in France are lighting cars on fire. Engineering itself can be revolutionary.
Second, and more pedestrian I suppose - It seems odd in the time of intelligence being move to the cloud, Waze and autonomous cars, to predict that the 101 will be a parking lot and investing in yesteryears mass transit is the right move. It would seem that autonomous fleets will be optimized to move people with less resources including energy, roadways, and vehicles. If anything one could argue that we should be pumping money and engineering into vehicle autonomy as its likely a better long term (something he should be able to get behind) investment than more lanes and asphalt. Sure we need to maintain roadways, but I would rather plan for more efficient and safer transport.
the problem is that autonomous driving and services like the high class busses will still take a lot of money out of the public transportation system, and if then they need to raise their prices, some people would loose their only means of transportation
I'm not qualified, but I'm guessing that the money will mainly be moved from private car transportation to these new transportation services.
and the other argument is that new "high class" bus services take money out of public transportation, which is badly needed there, but as you said, this may not add up to much. (However I could see myself switching from public transport to self driving cars, so they can also be included in this argument)
But both arguments go in the same direction - that public transport is definitely necessary and will remain necessary in the future but is often neglected and in a really bad condition.
It's hard to legitimately say which is cheaper. Buses don't need their own infrastructure, but they do need roads and these are often funded by various car taxes. Still, they often need subsidies to run. Many also have subsidized rates for poorer people on top of that.
Transport is generally expensive. I don't think it can be taken as plain fact that driving cars is the most expensive method, especially outside of dense urban areas. If you gave those same subsidies to poor drivers, many would be able to afford to drive.
Excluding taxes, driving a low cost vehicle has a fairly decent cost per-km. A litter of petrol can take you 15-20 km in an efficient, small car. Untaxed, that's <$1. If you travel 500km per month, that's about $30. Add $110 for purchase and repairs (cheap car), $40 for insurance and we are at $170 per month. $5.50 per day. Pretty close to the price of public transport in many European cities, maybe less.
This is driving relatively little, but most car owners just consume more transport (travel more/farther) that public transport users. Also, more than one person can ride.
It also doesn't take into account for infrastructure costs though, but public transport's purchase price often doesn't' either.
I'm not saying cars are better/cheaper, just that it's not a clear win for either mode. Transport is expensive. If you have no money, you can't afford much of it. We subsidize public transport for poor people and could do the same with cars.
Also most cities would not have the road-space to replace subways and busses by individual cars
The thing about robots is that even though very few of them even made it through the challenges some of them did and the ones that did now serves as the baseline for every other robot.
And so contrary to human where each individual have to learn a skill in the time it takes them to learn it, once one robot get it right this is instantly transferable to all other robots.
This is the big insight with robotics and not so much how good humans are at making robots do what they want them to. The steps they do take in the right direction is instantly applicable to all other robots.
Automation could impact a few lots-of-employees job functions (such as driving cars, receptionist, and, err, my crystal ball has gone cloudy) and then stall. Researchers will have good ideas for how to automate job functions, but be unable to get the funding because only a few thousand humans do that particular job and it is cheaper to pay to train humans (times a few thousand) than it is to fund AI research (once).
There are precedents for stalls. Think about garments. The sewing machine automates the process of passing the needle through the cloth. That is a big deal and causes a dramatic step change in productivity. Then what? Not much. For a hundred years and perhaps a little longer yet garment making remains at the same level of automation, with huge numbers of persons working in factories using the same old tool.
That is why my crystal ball is cloudy. The penetration of robots into job functions that have non-huge numbers of employees depends on coming up with clever hacks analogous to the invention of the sewing machine. Without a clever trick, AI researchers might still be able to brute force things (imagine an industrial robot programmed to hold a manual needle, sewing needle-and-thread human style) but it will be too expensive and not replace human workers.
I imagine the clever tricks trickling in a few per decade, dragging out the automation of the economy over a century or two (or three).
Keep in mind that once image recognition is done properly it's applicable to all jobs that require image recognition. Ex. a radiologist AND a quality control function.
So it's much much worse for humans ability to compete in the long and short run.
This is true - but then where do you think ideas come from? They aren't woven from thin air, they come from experimenting with existing ideas. I see it as a positive that so many people are experimenting with dumb-on-the-face-of-it apps... maybe instead of the latest messaging app one of them will make a real innovation.
Oh bugger.
The OP does a great job of explaining why Silicon Valley won't be involved in much of a meaningful way. I think that the biggest problem is that the balance of power between connections guys and talent has fallen into a state of irreversible moral calamity. In their time, Steve Jobs and Steve Wozniak were approximate equals. The business partner wasn't innately taken to be superior to the engineering partner. That changed somewhere between 1995 and 2005. Now, the connections guys are the only people who really matter and engineers (even up to the CTO level) are largely viewed as interchangeable. And they probably are interchangeable given that these businesses are all built to be dumped on a buyer inside of 3 years, and the consequences of mediocre engineering generally don't have business-macroscopic effects (beyond "throw more money at it" problems) until 5 or 6 years have passed.
I don't know where, when, or how the positive-sum mentality of the old Silicon Valley will reconstitute itself. I do think that it will be at least 500 miles away from the current one, because the current tech hub has "Future Detroit, But With Less Architectural Character" written all over it.
One is that we'll finally get a leg up on software development. This is more likely to be the result of lots of incremental improvements. We've made huge strides since the '60s, we have tons and tons of tools that we've built and use, but still at the end of the day software development is a crude endeavor. More often than not projects end up with "big ball of mud" architectures. And we lack the fundamental models and terminology to even talk about software design and architecture at a reasonable level most of the time. We have all these tools like TDD, static analysis, and so on, all of which is more or less bolted on to our other tools. And I can't help but be reminded of both the pre-structured programming era and the pre-OOP era, when there was a transition from a kludgy mess of useful components bolted on to existing paradigms that congealed into a cohesive design that became a universal standard. In, say, 30 years programmers will not only have better tools they'll have better techniques, better standards, and better models. They'd be able to look at the software projects of today and go "oh, well, here you have a classic example of X common architecture design anti-pattern, which you can fix using techniques U, V, W, and Z" and so forth. I think that alone will unleash a tremendous amount of potential in the use of computing systems and result in an inflection point in the effectiveness of software development projects.
The other is fully automated and configurable manufacturing. We have almost all of the necessary components in place for that today, but nobody's put them all together yet, but it'll be transformative. Imagine being able to upload a handful of files to some service somewhere and then those files would be used to produce PCBs; mechanical components and structures built from various materials (plastics, metals, composites, etc.) using 3D printing, injection molding, CNC milling, etc; and then having all of that assembled into a final device then shipped off to you. Imagine how that changes the economy we have today, how much it could accelerate innovation, how it could result in un-serviced economic niches finding satisfaction, and so on. Think about how many thousands of kickstarter projects would translate into simply designing something then making use of such a service. Also imagine how much things change if you can have a completely automated factory pumping out parts and goods 24/7. Imagine if you could bootstrap an industrial economy anywhere on Earth, or off, with a few shipping containers of machine tools set up the right way. And then you get into idea like self-replicating factories. Think about how all of this changes the economy into something that we would scarcely recognize today? What if manufacturing an automobile in 2100 was economically equivalent to manufacturing a diecast hot wheels toy today?
I think this is true if you define "the work" as building on top of the infrastructure we have today. I believe we're capable of building conceptually clean, non-ball-of-mud architectures, but the need to interoperate with piles and piles of legacy systems forces compromises into the design. Just look at a typical web application stack; you've got layers and layers of cruft, and nobody is able to pull off a bold move that tears layers off; the best we can do is add more layers on the top.
Every other programmer and scientist in the entire fucking world should be working on AI.
Or we can work on techniques to improve our ability. Our collective IQ improved a lot when we dropped roman numerals in favor of arabic/hindi numerals.
In programming we have know of better techniques for a long time[1]. Sadly, as a community we just haven't put understanding as a priority. We follow "Move fast and break things." instead of "Elegance is not a dispensable luxury but a factor that decides between success and failure.".
Software is a complex subject, but is it so much different than chemistry, physics, mathematics? Each of which took hundreds of years to progress through multiple stages of advancement. Is functional flavored OOP with bolted on TDD the grand unified theory of programming? That seems unlikely to me. I suspect there are further conceptual breakthroughs on the horizon. And there is still a tremendous amount of improvement available just in getting everyone up to the level of adhering to known best-practices.