Robert Chiu (Statistics New Zealand)
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Exponential Technology, Linear Progression
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Robert Chiu (Statistics New Zealand)
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- 5. 5 http://www.singularity.com/charts/page67.html https://en.wikipedia.org/wiki/FLOPS# Hardware_costs $0.08 per GFLOP X 12,500 gives us the GFLOP per $1000 (1000/.08 = 12,500) X 1,000,000,000 (to get us the number of FLOPS) = 12,500,000,000,000 FLOPS!
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- 24. 24 Minimise the total time it takes to go through the build, measure, learn cycle.
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- 33. 33 Thank you for your attention. Any questions? hello@robertchiu.co.nz
Editor's Notes
- I like to thank the crew at the AgileNZ conference for giving me the opportunity to speak to all you wonderful people today about a topic where I’m personally very passionate about, but also a topic that we, as professionals need to understand and adapt so we can all succeed in a time of consistent change from the impact of exponential technology.
- Sit back and relax, don’t stress too much on the note taking, since the presentation is being recorded, I have numbered the slights on the bottom corner. So make note of the slide number and then refer to the video. Easy!
- So lets begin with a question. This is WestpacTrust stadium, home of the current Super Rugby champions. It’s 1pm. Imagine you are sitting on the seat at the very top of the stadium, with the best overview of the whole stadium. Imagine the stadium is completely water-tight. If a drop of water is added to the stadium and then one minute later it doubles in size to two drops, and then one minute after that it doubles again to 4 drops, and so on.. doubling in size every minute, how much time do you have to leave your seat and get out of the stadium before the water reaches your seat at the very top? Think about it for a moment. Is it hours, days, weeks, months? The first drop of water lands right in the middle of the field, at 1pm. You have exactly until 1:49pm. It takes less than 50 minutes to fill a whole stadium with water! But it gets better: At what time do you think the stadium is still 93% empty? Take a guess. The answer: At 1:45pm. So, you sit and watch the drop growing, and after 45 minutes all you see is the playing field covered with water. And then, within four more minutes, the water fills the whole stadium. This means that you think you are safe because it seems that you have plenty of time left, whereas due to the exponential growth you really have to take immediate action if you want to have any chance of getting out of this situation.
- This is an example of an exponential curve, where the numbers increase very slowly in the beginning but then increase rapidly over time. Humans are pretty good at estimating linear functions, where there is a consistent increase over time, but we are remarkably bad at predicting exponential curves. Why am I showing you this? Well, let me introduce you to Moore’s Law.
- Gordon Moore, one of the co-founders of Intel observed that the number of transistors in circuits doubled every year and followed that of an exponential curve. This was followed by Ray Kurzweil (one of the worlds best futurist) adaptation of Moore’s Law to this graph, which shows the number of calculations performed per second that is available per $1000 over the past century also follows an exponential curve. In laymans terms, the amount of computing power available to us is growing to the point where we will have the computing power of a human brain in just a few years, and on top of that, its getting cheaper. Ray’s book was published in 2005. Just in case you were wondering, and thinking that the data points stop on the year 2000, this is where we are currently at. And just because I’m from stats, here is the Maths. Note that this is from a Desktop Computer in 2015, you now actually have that computing power on your Mobile phones if you have a Galaxy S6 or and iPhone 6 and this was released in early 2016. What does this mean?
- Well Kaila will be presenting on a lot more detail and examples in the presentation following mine. But I’ll give a brief overview and some specific examples for the purpose of this talk.
- If we have a quick look at our modern lifestyle more and more of it involves some form of digital technology. Such as communicating with friends and family over skype, and social media, Or using maps and navigation to help you find out how to get to your next destination, Or in health care where we use computing equipment to test how health levels, Or paying someone using EFTPOS, credit cards, or bitcoins, Or supply chain of food where companies can monitor stock levels for our modern ‘just in time’ services. Or word processing with our jobs. As technology is getting cheaper and more powerful, it means we can build better things leveraging off this increase in technological capability and capacity.
- Let’s look at a specific example. Lets look at energy and transportation, this is one industry that is primed for disruption. In Tony Seba’s Book Clean disruption, he argues that the combustion engines are about to be disrupted by that of electric vehicles, based on the technological advancements from exponential technology in energy. Now I want you to focus on that headline – obsolete by 2030, seems relatively unrealistic right? Well lets have a look at the numbers.
- The first is area of disruption is energy, where the cost of solar energy generation is decreasing every year. The cost of the photovoltaic cells or solar panels to generate the energy. Here we can see that back in 1977, where the cost per watt of energy was $76 US dollars, but this has dropped exponentially due to the improvements from technology. In 2015 it reached 30 cents per watt in the cost of the photovoltaic cells. So the cost of solar panels is falling.
- Let’s look at another graph, this shows the trend of increasing efficiency of converting solar into electricity. So the graph is very busy, so don’t focus on the detail to much, but what I want you to focus on is the general trend of the increasing efficiency of the energy generation of the cells. It is following that of an exponential curve.
- If the infrastructure is getting cheaper, and the generation is becoming more efficient. Then it would lead to cheaper overall cost of energy. We are now seeing solar energy plants in UAE generating energy at 2.41cents per kWH. That’s cheaper than most other forms of energy generation we current have available.
- So now we have cheap energy, the next part is about storage, because with solar the energy is only available during the day right. Well we are seeing falling cost in energy storage with the cost for Li-On battery and through economies of scale with the lights of Telsa’s gigafactories coming online. So with the price of electrical energy falling comparatively to fossil fuels, you’d think that is the only area of disruption in transportation right?
- Well it turns out that with electric vehicles, there is only 18 moving parts compared to the 2000+ in an internal combustion vehicle. This means from a supply chain standpoint, less parts to produce. From a maintenance standpoint, less things can go wrong, all of which means it’s cheaper to run. What about maintenance? Well I already showed you previously that the cost of electricity is now cheaper than that of fossil fuel, but if we compare moving parts there is 2000+ parts on the internal combustion engine, vs the 18 of the electric vehicle. Which means engineers spend less time on maintenance, which means it’s cheaper to run.
- So from a cost stand point, the electric vehicles are cheaper and better in almost every metric. Tony has an amazing video on youtube that goes into this into even more detail, and I highly recommend a watch when you get some time. But what about some other advantages of electric cars that we can’t compare? Lets look at some major social issues of New Zealand.
- There has been a lot of media attention on traffic congestion, with some really terrible commute times in the main centres of NZ. We have seen the ministry of transport try and reduce congestion. Here is a video by CGP Grey that explains our current approach to solving the traffic problem, and what gaps we have missed with this thinking.
- It turns out, another benefit of electric vehicles is that of autonomous cars, you can solve some very large social problems. Another couple social issues we can solve with autonomous vehicles are:
- The cost of vehicle accidents, Australia recently estimated that autonomous cars can save $27 billion a year. To give you a sense of how much that is, it’s 10% of NZ’s total GDP.
- How about housing unaffordability? The cost of real estate is reaching unprecedented levels, and this is due to people wanting to live closer to work and because of travel times. Unfortunately the supply isn’t there to meet the demand. But if traffic is no longer an issue due to autonomous vehicles as demonstrated by the video, then individuals can live further away from the city because of improvements to commute times, where there is a lot more supply of land and housing. This would reduce the cost of housing for all.
- Now I can talk for hours and hours on this topic, but remember this exponential curve? Like all exponential curves, the rate of change starts off very slow in the beginning, but increases rapidly with time. I believe we are currently here on the curve, and experts are projecting that we will see more and more major disruption in the not too distant future.
- Here is a simple graphic that shows some major technological events over the past 600 years. And as you can see, we have seen more major technological changes in the past 25 years that we have seen in the past 575. So what does all mean for us, the agile professionals and our businesses? Firstly we have seen plenty of successful case studies of organisations adopting agile, I would be very surprised if the consensus here isn’t that organisations should be Agile by default. But I also think that Agile alone isn’t the answer. Agile has been around for quite a long time, and if we think back to the exponential curve, the reason we saw such success with agile is because it matched up very well with the rate of change we were seeing. But in my opinion we are now reaching a point where we need to look at other frameworks to complement the existing Agile framework to help us understand, and thrive from this dynamic environment.
- This is David Roberts, who is one of the faculty members of singularity university. I had the pleasure of listening to him speak at the New Zealand Singularity Summit a couple of weeks ago and one thing he said that really stuck out. I think most organisations are trying to be innovative, as it what helps you sustain your market share and prolong the life of your business. However, with the cost of entry in technology continuously getting lower, small start ups now have the ability to compete with against large organisations. This is one of the factors why we are seeing massive growth in the start up space, where we see billion dollar companies like Uber and Airbnb appear almost over night, disrupting whole sectors. Much of our current methodologies and frameworks focuses on iterative development and continuous improvement, very rarely is this avenue for identifying truly disruptive innovation. So what can we do about it?
- First - Fight fire with fire! One of the key advantages that a small start up has over a large business is it’s ability to experiment and validate their business ideas with speed. Start ups have no pre-existing process, governance, politics, technology to slow it’s progress, it uses the minimal amount of effort required to validate an experiment.
- This is the key argument for Eric Ries’s book the Lean Start Up.
- Where the aim is to minimise the total time it takes to go through this cycle of build, measure, learn. Some smaller organisations can do this fairly well by ring fencing a small team within the organisation. But larger organisations typically have more red tape, and you may be required to take the teams out of the organisation and let them work independently in this way.
- Something we had to do at Stats.
- We are seeing this framework being applied on small scale weekend hacks, where organisations crowd source ideas to experiment and solve problems to local, industry sector and national scale. It speaks loudly when you see the public sector, whom historically have been one of the slowest sectors to adapt, embrace this framework.
- Google pioneered the 5 day design sprint sprints back in 2010 which follows a very similar approach.
- To full 3 month accelerator programmes, such as Y combinator out of the states (I highly suggest you have a look at their news stream, just google hackernews), or the New Zealand Equivalent in Lightning Lab. Or the Public sector R9 accelerator programme. To private internal programmes like Spark Ventures or Fonterra activate.
- We have seen some very successful case studies internationally and domestically from this methodology and framework. Dropbox is a file hosting platform that was recently valued at $10 billion dollars, it came out of the Y combinator, and the same can be said about Airbnb. Domestically we have companies like Wipster, a online video production application coming out of Lightning lab. Or Qrious and Morepork out of Spark Ventures and their internal accelerator programmes. This gives you the framework.
- Then the second part is keeping your company educated with the consistently changing technology. We have so many new tools that are available to us at such an exponential rate such as Artificial intelligence and machine learning, 3D printing, and Virtual reality to name a few. Kaila will give you more examples of exponential technologies right after this. But it’s up to us to combine the framework that is designed for rapid feedback through experimentation, with the exponential tools that are being created at a rate never seen in history, to create even better things.
- Here’s the first example. Everyone knows about uber and their rise as the poster child as a market leader in transportation. Well you might of heard that uber are now testing their own fleet of self driving cars. What you may not know is that this is made possible because telsa made available all their data and software for autonomous vehicles open source back in 2014, which is why we have seen this rapid rate of development in this space.
- Last example. Just think back to when Google first launch translate in 2006. Since then we have made giant strides in this space, with more languages being available, improve accuracy, voice recognition, all thanks to technological improvements. Well now we are at a new point in history. As a side note: I really like the invention was created out of love. Now think about this for a second, if language is no longer a barrier in communication, we have for the first time in history, potentially universal understand with all 7 billion of other individuals on the planet. What kinds of possibilities does that open up for you?
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