The world is changing. We are living in the Second Machine Age or Fourth Industrial Revolution. Whatever you want to call it, mechanical tasks are moving into the digital realm, and more of the physical world is becoming digitized. This is the essence of the ongoing digital transformation.
A world awash in data offers three implications. First, access to information and the speed at which it travels has ushered in the era of transparency. In business, research and medicine, much value is derived from maintaining an informational advantage. It is incumbent upon operators to stay ahead of the curve.
Second is the advent of artificial intelligence and its subset of machine learning. The principles of extracting insights from troves of information have long been established. Quantity and quality of data serve as the key to unlocking its potential. The third is automation and robotics. This is somewhat enabled by artificial intelligence but is a function of sophisticated dexterity and sensor sensitivity that define state-of-the-art robotics.
Access to information, artificial intelligence, and robotics are opportunities, but they define the new frontier of competition. Winners and losers will be created based on how they harness their power. These are tools and instruments of competition that can affect product quality, reputation management and cost structure.
There are three things that operators must do to stay ahead of the curve. First, maintain an informational advantage. If your partners and investors know relatively more about your operations, then you must know more about your operations. We can call this the WebMD effect. Second, leverage artificial intelligence as an opportunity to codify expertise into your digital systems. Third, digitise and automate in a scalable and reproducible manner. This will help drive down the marginal cost of production.
Whether you are a physician, agronomist or geoscientist, the highest value opportunity lies in the melding of the physical and digital worlds. This is not about more data, but to make better, fewer and earlier decisions. Ideally, researchers, clinicians, operators and robots would know the content of each and every object of interest in real-time automatically. In many ways, we can characterise the full set of digital innovation as a push to approach ever closer to that target.
Visibility is what matters. We can have as much or as little data, but visibility into the people, products and practices that define an operation is what matters. It is the sensors that bridge the gap between the physical and the digital. Artificial intelligence has existed in principle since 1952. The computer science was refreshed in the 1980s but fell into another dark period until recently. The unreliability and weak sensitivity of sensors, along with slow data processing, have limited the potential of machines for decades. But we have blown through to a new era of digitization to unleash the power of artificial intelligence and robotics. Consider, for example, the sensing capability of the 2008 Apple iPhone versus the 2021 Apple Watch, which has a tachymeter. This is enabling AI to monitor for heart attacks.
If artificial intelligence sets the potential, it’s the sensors that set the floor of what is possible. One of the more powerful sensing capabilities that will eventually become a default tool at farms, mines, clinics is hyperspectral imaging or imaging spectroscopy. Hyperspectral imaging offers improved breadth, depth and precision of visibility into the physical substances and objects that define and drive analysis and production.
In agriculture, this could be the plant or the field. In food processing, this is everything from individual coffee beans, to cheese samples to cookies moving through the process on conveyors. In geoscience, this is the terrain and the drill core samples. In medicine, this is human tissue. Hyperspectral cameras can see into these objects to measure and map parameters of interest beyond the potential of the human eye and without the destructive element of laboratory analysis.