Seven years ago, in 2015, the UN released objectives that humanity wants to reach by 2030, the UN Sustainable Development Goals.
We are halfway through to 2030, and progress has been made, but it’s not enough. Part of the problem is that at least 15 of the 17 SDGs are full of engineering challenges — and engineering takes time — decades. Look at all the physical things around you and think about how they looked like 10, 20, 30, 40 years ago. You will find that many have not changed much. A car from the 1980s is a fine car, and if not for Tesla, we would be content with the century-old motor technology that has only been incrementally improved in the past decades.
However, there is one area that is disconnected from this linear progression of engineering: Information Technology (IT). A computer from 40 years ago is a curiosity. You would not use a 10-year-old cell phone. Yours is likely less than three years old.
Why is IT operating under Moore’s Law and following its own trajectory?
The answer is: software. IT, even the hardware side of it, operates under a software paradigm. Microchips are not created by human engineers drawing chip layouts on screen. They are created by smart algorithms that solve physical design challenges. Humans guide the algorithms on an abstract level. They are, however, not involved in the complexities of the blueprint that is generated — a human would be incapable of doing it.
We have to move all engineering to the same software paradigm to accelerate it to the level we need to reach the Sustainable Development Goals. This is our mission at Hyperganic with our approach to Algorithmic Engineering.
In Algorithmic Engineering, you create software code that designs physical objects based on input parameters. In Algorithmic Engineering, you can fail fast and iterate. You go beyond the breaking point and then step back until it works again. You innovate at a different speed. You move at the exponential curve of Moore’s Law.
Furthermore, once a robust algorithm is established that creates certain classes of physical objects, there is no reason for engineers to spend time on it anymore. They can move on to the next challenge and use their creativity to solve it. This is how you get exponential speed into your work: never do something twice, and never invent something that someone else has already created.
Climate change, zero hunger, access to clean water, to name a few — these are fundamentally all engineering challenges. The earlier we move engineering under Moore’s Law, using Algorithmic Engineering, the faster we can get back on track to solve these challenges by 2030.
