A New Way to Innovate: Innovation by Combination

Sharif Natheir
Jan 5 · 5 min read

Compartmentalization was a good strategy in the past. It allowed us to examine reality with different lenses, grasping one truthism per lens. However, applying such a reductionist approach in technology has made us blind to just how blurry the lines are between technologies. This made the concepts of artificial intelligence (AI) and 3D printing, for example, to be distinct in our minds. However, much overlap exists between these technologies and they may even complement one another perfectly. In fact, most technologies may be combined in one way or another, although it is true that some more readily lend themselves to combination (e.g. Big compute and AI, or cloud computing and blockchain).

Since this notion seems to have evaded most innovators, thus resulting in many unexplored paths, it seems to me that the easiest way to innovate nowadays is by combining various technologies together. Historically, innovation has been the application of a singular technology to a previous unexplored field. This sort of innovation is widespread in the modern day — as an example, one can think of the application of AI and Big Compute to molecular biology, creating Alphafold 2.0 and rendering X-ray crystallography useless. But imagine what may be possible with the application of AI and VR in neurosurgery, for instance. This sort of innovation may be encapsulated in the x and y in z form, where x and y are two technologies and z is a field. Whereas we have often limited ourselves to x in z, this new y dimension exponentializes the opportunities.

We don’t need to look far to demonstrate the power of this technique, since it has been perfected by the companies we know best: is Amazon not simply the combination of cloud computing (AWS), the web, robotics, and artificial intelligence (AI) to the retail business? Tesla, the combination of high capacity batteries and AI to the automotive business? Bitcoin, the application of blockchain, Big Compute, and the web to Fiat currency? Google, Apple, Facebook, and so many others follow a similar principle.

You may believe that waiting for the next big breakthrough is necessary to get started with such an approach; that all applications of modern technology have already been explored. However, even within the technology era, significant new advances in technology are not all that common. Rather, creative new applications of relatively old technology is what drives us forwards. As an example, despite much misconception about the novelty of artificial intelligence (AI), the groundwork for this field was laid out in the 1950s. Since then, most AI-related papers have been about novel applications of AI (applied AI), rather than theoretical advances in AI. And the theoretical advances are incremental at the very best.

Although conventional approaches to innovation preach that the would-be innovator should start with the market in mind, querying what needs exist and how they may be fulfilled, they make a significant assumption: that the market knows what it wants. And to this end, Henry Ford put forth that famous adage, that had he applied such a conventional approach, he would have come to realize that the market demanded faster horses. I note this here so as to juxtapose convention with the highlighted method — after all, innovation by combination, on the other hand, may fall into the antithetical extreme. Its application may result in the creation of products devoid of demand, or solutions where there exists no problems. And as so often is the case with contrary ideas, a balance may be stricken between the two extremes that may just nullify their drawbacks, leading the would-be innovator to attempt both methods. Nonetheless, with the convention being as ubiquitous as it is, an alternative approach may yield better results by generating unique ideas and therefore decreasing competition.

Of course, up until now I’ve limited my discussion to cutting-edge technologies, but you don’t have to stick to those; certainly, there are many unexplored applications of well-established technologies. The selection of which technology to ultimately devote your time to, however, is a grave one as it could result in countless years of wasted effort and depleted motivation if incorrect. As such, it is my belief that limiting ourselves to those that are just coming out, or have even moderately been established, is the right call as it maximizes the number of possibilities left unexplored.

In an effort to make this more of a practical exercise, here is an alphabetical list of a dozen technologies that have rose to prominence in recent years:

  1. 3D printing
  2. AI/ML
  3. Blockchain (cryptocurrency)
  4. Brain-computer interface
  5. Cloud computing/big data
  6. Drones
  7. Gene editing
  8. High capacity battery
  9. Micro satellites
  10. Quantum computing (may need more time to mature)
  11. Virtual reality
  12. Wearables (particularly smart glasses)

Using just the technologies listed here, a table can be made which displays all the possible binary combinations. This yields a total of 132 possibilities, ignoring the sole use of each of one. Keeping in mind that the order in which the technologies are combined may be significant, as illustrated in the biochemistry vs chemical biology example earlier, 264 different permutations of these technologies can be made. I encourage you to take on this exercise to see what possibilities you come up with. Multiple such tables can be made, each for a different field (e.g. one for the applications of x and y technology in neurosurgery, another for the applications of x and y technology in banking).

Here’s a sample table:

Image for post
Image for post
Sample combination table of the 12 suggested technologies.

If you’re feeling particularly creative, know that this exercise can be generalized to an arbitrary dimension (3D, 4D,…nD, etc. using tensors of 3, 4, or 5 dimensions). Naturally, such an approach significantly increases the complexity of the end product, but complex problems may necessitate complex solutions.

As a caveat, note that this combination of different technologies requires a more diverse skillset; it takes a certain level of expertise to effectively work in any one domain and thus ever the more skill to work in multiple. However, innovation is a team endeavor and a strong interdisciplinary team will solve this integral limitation of the approach. That being said, I recently wrote an article on why technology should be something that you pick up anyway, at the very least to be able to bridge the gap between the domain experts and the technology you propose to bring to their field.

Good luck!

The Startup

Sharif Natheir

Written by

MSc. (C) in Experimental Surgery (surgical innovation), McGill | Data analyst, Harvard | Interested in the applications of data science (AI/ML) in healthcare.

The Startup

Medium's largest active publication, followed by +771K people. Follow to join our community.

Sharif Natheir

Written by

MSc. (C) in Experimental Surgery (surgical innovation), McGill | Data analyst, Harvard | Interested in the applications of data science (AI/ML) in healthcare.

The Startup

Medium's largest active publication, followed by +771K people. Follow to join our community.

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