How Does One Engineer a Paradise?

I finished my first book, Engineering Paradise:  Are You Ready?, a book that illustrates how current trends in social thinking and technology is changing our society in a fundamental way, recently.  After I finished writing it, I had an interesting thought:  though I described the many technologies that are already affecting change, I didn’t give readers a clear idea of what an ideal world may looks like.  The reason why our world is still full of inequalities and violence is because we are currently mired in obsolete infrastructures, social systems, traditions and ideologies that hold us back.  These systems have been around for hundreds of years, slowly changing to adapt to different social, political and economical movements.  These are hard to change because they are all embedded into our society and into each other.  Not to mention most people are employed and depend on the survival of each one of those systems for their welfare and livelihoods.  Any significant change in social structures are therefore scary to most, because individuals are afraid of what they cannot understand or predict.

Under these conditions, suggesting how our world may function in 10 or 20 years would be incredibly naive and speculative.

However, I was thinking about the following:  what if, strictly as an intellectual exercise, we imagined that all traditions, social resistance to change, social systems and institutions were just swept out of the way and we just build something better.

Now, I know what you’re thinking.  It’s nice to dream about some sort of perfect world where we don’t need to care about how things really are.  That’s what science fiction is for, right?

That was the initial conclusion I had with the idea too.  But then it dawned on me.  Even though what paradisiac world we may build would be fantasy, at least it would be something we could shoot for.

 

One thing that I have learned as a serial entrepreneur is that if we want to achieve a project that seems too big to be doable, we still have a shot of achieving it if we have 3 things:

• A well-defined plan.
• Strong motivation.     
• A dedicated team of individuals that believe in the project and are willing to work towards it step by step.

So, I decided to write this book to paint a picture of how we could build the ideal future for ourselves.  Thus, I’ll prepare point #1 for us all.  At least I’ll be producing my version of it, supported by proper studies and professional knowledge from experts. 

Then, by publishing the book and directing other activities aligned with the goal of engineering a paradise, I hope to gather a large enough group of motivated people that believe in building an ideal world.  There are already several organizations that are working towards making the world a better place and I’m sure millions of individuals in the world wish they could contribute to such a great project. 

Are you one of these people?

Finally, with those two pieces in place, together, we can figure out a plan to engineer our current world and ultimately transform it to fit the end goal:  the ideal world.

I’m sure most of you have very different ideas of what the ideal world would look like and that’s fine, but in this case, we’ll want to build based on proper evidence.  Using proper research sociologists and other scientists have already documented over the years, I’ll illustrate what is fundamentally best for human beings.  Starting from that basis, I’ll elaborate on how nations could be ideally governed to ensure the people are in the best possible position to thrive.  After all, we have over 3,000 years of experimentation and trial and error under our belt as a society and now we’re supported by artificial intelligence to assist us, the Internet to connect us and sufficient comfort levels for at least half the world’s population to collaborate on our common goal.

Then, I’ll go into a full section detailing how such a governing system can be managed by the people and finally I’ll elaborate on how an ideal economy would work within this new innovative system.

I’m hoping this detailed plan on reformulating our society leveraging advanced technologies, will inspire many to work together, as a team, with me or in independent groups.  It’s all good.

Fundamental technologies 

If you haven’t read my first book, you may be a little bit lost in the next few chapters so here’s a bit of an update on certain technologies that will support most of what I’ll be discussing.

We have been playing around with artificial intelligence (AI) for the past couple years.  AI is not new.  In fact, it has been around for over 30 years but only recently has AI applications become part of our daily lives.  Not only toys used by large companies, research laboratories and governments but in our living rooms and on our smartphones.

It is like it was for computers in the 80’s.  For the first time families started buying them for their homes even though transistor computers had been around for at least 30 years.  Computers had become a commodity after years of companies improving the basis of the technology and finding ways to reduce costs enough to make the technology useful, small enough and cheap enough to be purchased by families.

Now, we have AI like Alexa, Siri, Cortana, Watson and Google Assistant, to name just the most popular AI in North-America, available to consumers.  They can understand native language and can connect to our smartphones, security systems, our digital information, home appliances, heating, lights and so on.  We can control these systems through our AI assistants, or by using our smartphones.  The AI assistants are intelligent enough to search the web for us, add items to our grocery lists, and learn who are proper family members or strangers in our homes or front doors. 

Today’s AI are learning AI, which means the more we use them, the better they can perform.  They are just like children learning about their environment and after a while, they don’t need as many explanations to achieve their tasks.

We’re also running automated devices and robots with AI brains.  The most obvious automated devices that will take the world by storm will be self-driven electric cars.  Most car manufacturers will start selling those on or around the year 2020[1], which is very, very soon.  These can be considered robots with an AI brain since they will recognize passenger voices, understand instructions and then be able to drive themselves on real roads, dealing with unpredictable road conditions and the public.  They just have wheels instead of limbs.

Self-driving cars will also likely be connected to the Internet, just like AI personal assistants, so they can access useful information and share with other AI-enabled robots and software in a networked fashion.  That will make them even more efficient and instantly learn from other self-driving cars on the roads, making them very good drivers and very safe faster than we can blink.  At the very least, they will be better drivers than any human can and keep improving 24-7 as we use them.

In the midst of these technologies supporting all industries from education, health, economy, government, manufacturing, and others, it is easier to imagine novel ways to structure our society than every before.  I think it’s a good time to give it a try.

Exponential thinking 

Here is something else to consider moving forward:  we must stop thinking in a linear way.  It is quite natural to do so since we are built to experience the world through our senses and our bodies are designed to seek balance (what biologists call homeostasis).  We are built to change, but change in our brain and bodies creates imbalances that our own biochemistry constantly tries to balance out.  The body’s rebalancing process takes time.  It never gets faster from generation to generation, so there are hard limits in how fast we can change our minds or adapt to physical situations. 

Socially, there are even more pressures towards linear thinking because everyone around us, ourselves included, measure time in the same small increments and we balance each other out at similar rates.  It is all tied into our biology as described above.

It’s no wonder when we start thinking about the future, we tend to see progress in a straight line, ergo if it took one generation to go from cell phones to smartphones, the natural thought is that it will take one generation to go from smartphone to the next generation of pocket communication device.

Unfortunately, technology is built following the Law of Accelerating Returns[2], a term coined by renowned futurist and inventor Ray Kurzweil.  The law describes how progress not only depends on our linear creative selves, but it also depends on the body of previously developed technologies.  This creates an exponential growth curve.

Kurzweil wrote in his 2005 book The Singularity Is Near, “Technology goes beyond mere tool making; it is a process of creating ever more powerful technology using the tools from the previous round of innovation.”  Kurzweil studied different tools in different industries and the trend in each industry is exponential because every industry is using better and better tools leveraging the previous generation and tools from other industries.

Thus, productivity keeps increasing exponentially in each industry[3].

If we look at high tech innovation on its own, people work on different aspects, namely software (AI, smart systems, application tools), computer hardware (smaller microprocessors, quantum computing, organic computing) and robotics (more efficient servo motors, new materials, gyroscopes, miniaturization).  Then each one of those aspects are used by people to develop the other in a cyclical manner.  Better hardware allows us to use create more sophisticated software leveraging more information that achieves results faster (see Moore’s Law)[4].  This software is used by engineers to design better robotics.  Then engineers use the improved robotics to create smaller transistors at a faster pace and integrate them into new better computer hardware. 

The advancement of each component, hardware, software and robotics, are then used in other industries where we could illustrate other similar cycles.

The truth is, the world we’re living in is changing at an exponential rate.  We must then learn to think exponentially.

So, if you think it is impossible to engineer a paradise in our society within a single generation, you may be surprised.  Methods of communication, production and collaboration have never been faster and better suited for massive change.  And they too will become better and allow connectivity at an accelerated rate.

In some ways, since human beings are biologically linear, we must get ourselves out of the way by allowing this accelerated ace of change to occur, supported by intelligent technologies that are in fact improving at an exponential rate:  artificial intelligence.

So, I suggest we expect things will change faster than we can possibly imagine.  It takes a measure of trust but I’m hoping you will continue to read this book and perhaps contact me to collaborate on projects that will help move things along.

Check my website for some projects that I have started or some that are already underway.  

I’m also available for any engagement that would allow me to educate.  I’m leaving it to you.

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[1] Moore’s Law.  Wikipedia, the free encyclopedia - https://en.wikipedia.org/wiki/Moore%27s_law

[2] The Law of Accelerating Returns.  Ray Kurzweil - http://www.kurzweilai.net/the-law-of-accelerating-returns

[3] Technology Feels Like It’s Accelerating – Because It Actually Is.  Alison E. Berman and Jason Dorrier - https://singularityhub.com/2016/03/22/technology-feels-like-its-accelerating-because-it-actually-is/

[4] Self-Driving car timeline for 11 top automakers.  Dan Fagella - https://venturebeat.com/2017/06/04/self-driving-car-timeline-for-11-top-automakers/

There is no Limit to Computing Power, or is There?

According to the current definition of Moore's Law, which was stated in 1965, computing power will keep doubling every 18-24 months.  So far, M. Moore's prediction has held true as seen in the graphic below.

Each transistor in traditional computers can represent either a "1" or a "0", which is the language of computers.  And the more transistors you can put on a chip working efficiently with others and other parts of the computer, the more calculations per second you can achieve within a single reasonable sized box.  Each transistor also needs minute amounts of electricity, which generates heat (hence why your laptop and desktop computers get warm), and too much heat would mean melting the system itself.

Thus making a computer that outperforms the last version and keep in line with progress (whether following Moore's Law, faster or slower) is a challenge in balance and design.

And since we're already at the 10nm per transistor scale today, this being the size of 100 hydrogen atoms across, there is not much room for improvement in size without one single atom in the manufacturing process ruining a transistor thus making manufacturing these less cost effective and unreliable to produce.  Some people think we won't be able to go much smaller than this.

However, thanks to new manufacturing techniques, we've been able to produce transistors at the 7nm and then 5nm scale recently (we won't see these before 2019 at least).  5nm is thus 50 hydrogen atoms wide.  Thus there are limits to how small you can go.

So in order to resolve issues and keep computers becoming more powerful all the time and retain reasonable size, we need to find other ways to do it than rendering transistors smaller in scale.

I discuss the implications of this in the video below:

In a nutshell though, we could do one of the following:

1. Find a way to work with subatomic particles to emulate "1" and "0" transistors.  This would mean us using single atoms in some ways to get discreet signals.  I haven't seen any research going in that direction since we 're not even sure how subatomic particles behave concretely within atoms to leverage them in this fashion.
2. Use quantum state bits, or qbits.  In this case, instead of using "1" and "0" transistors, we use extremely small transistors, roughly the same size as the ones described above, but instead of having only 2 possible states, the transistors would work with qbits capable of evaluating multiple states all at once.  Ex.  a traditional computer with 2 transistors has 4 states (00, 01, 10 and 11).  2 qbits in that scenario would be able to process all four states all at the same time.  The best quantum computer we have built so far is capable of operating with 16 qbits, which is equal to 65,536 traditional bits.  If we were to start using qbit-driven computers for processing, we could then increase the power of computers exponentially, further moving things forward, without sacrificing size at all.  A well-connected friend of mine to quantum computing has recently told me that quantum computers are going commercial as soon as 2018.
3. Change the computer architecture to make it more efficient and less energy hungry.  Usually, computer processing units have their own memories they interconnect with to work, called a core.  Typically we connect cores together to increase the amount of information processed simultaneously, but since each core has to process information using electricity with its own memory before spewing our results, there is a lot of back and forth within the core that takes extra time and heats up the system.  Hewlett Packard seem to have figured out a way to use a single shared memory block for all processors instead, and each processor would communicate with the memory using optics, which is faster, more energy efficient, and thus much cooler.  There is also less interconnection communications going on since all processors then use the same central memory system.  This simple architecture change can make machines cooler and also more modular, where we could add processors (or new cores) to the system without worrying about memory.  Less communication within the system with less energy consumed, and less heat.  This can increase significantly the speed of computing, and make them smaller, since there is way less need for empty ventilation space for devices..  Though improvements in this case are likely not going to be exponential, it is a great piece to the puzzle.  Combined with quantum computing for the processing parts, incredible speeds could be reached and an exponential increase in simultaneous computations per second could be reached too.
4. Last but not least, good research has been made on a brand new type of transistor that is meant to emulate biological neurons in the sense that they take inputs from different sources in a weighted fashion, learn from input's frequencies and is able to adapt and provide different outputs through "experience".  Though these would not fit very well within the frameworks of conventional computing like the advancements discussed in points #1 through #3, on can see the advantage of having transistors that learn on the fly and adapts based on usage, in particular for learning artificial intelligence systems.  We then get a system where the software is naturally able to learn but where the hardware itself also has a learning component that simulates experience.  

All in all, exciting stuff that should allow for Moore's Law to continue its exponential path towards the future for another while.  Can I say whether or not Moore's Law will eventually become untrue?  I really can't.  But taking into account our creativity to find new novel ways to keep computing power to increase, I can only assume for now that in the next few years, we'll just find new ways to make computers better, more efficient, faster, smaller and smarter.

All we need to do is keep encouraging creativity and we'll all reap the rewards of improved support for our personal and professional lives.