AI is a hot topic currently; many investors are interested in the space but may not be interested in jumping on the band wagon with the top names discussed on the news every day. What are some other options to invest in AI? With the expansion of AI many have been discussing the differences between legacy digital simulation (static) vs. AI driven digital twin (real-time) technologies which are a virtual representation of a physical environment. These technologies are used in every industry, from manufacturing, healthcare, financial technology, aerospace etc. A brief background of the two is as follows:
Digital simulations are the traditional form of CAD (computer assisted design). These systems are static meaning that once the software is programed it does not automatically change or adapt based on behavioral or environmental changes. If there is a change to design, materials or supply chain those changes must be input/modified by the programmer. A digital simulation is useful to determine what could happen to a product or process.
Digital twin technology is more active than digital simulation meaning that it can learn and update itself throughout the product or process lifecycle. A digital twin replicates what is happening in real-time and has a much wider scope of use. A digital twin is only limited by the amount of data that can be processed and allows for real-time optimization basically meaning have it fix itself before an issue occurs.
Obviously, the AI optimized digital twin is the optimal technology but up to this point has been much more costly to implement as well as requiring much more computing power, hardware and chips. One company that is currently advancing the capabilities of digital twins is NVDIA, the following shows some industry examples of what they are currently capable of: 5 Steps to Get Started with Digital Twins (nvidia.com). One key theme associated with the abilities of digital twin technology is robotics and automation. Instead of programming the robot to do specific tasks following a static process, digital twin technology will allow the robot to actually think, monitor, learn and improve the process on its own.
Some entities are innovating the uses of AI driven digital twin technology are as follows:
Bio Digital Twin
Surgical Robotics – AI-DT technology used to virtually test new treatments/procedures and make recommendations specific to individual patient biological criteria. The ability to test new devices and procedures will decrease the FDA approval timeline. Companies such as Accuray (ARAY), Intuitive Surgical (ISRG) and Stereotaxis are currently implementing this technology.
Biotech/Pharma – AI-DT technology is also being used to develop new drugs based on a specific patient or set of patients. The additional data available real-time will both decrease FDA approval timelines for new drugs as well as monitor current drug efficiency even after approval. This is extremely helpful when it comes to oncology, Alzheimer’s, cardiology, neurology and rare diseases. We find companies in the rare disease space such as Recursion Pharmaceuticals (RXRX) and Bioxcel Therapeutics (BTAI). Automation based pharma distribution companies such as Omnicell (OMCL) can use this technology to precisely adapt the supply chain to changes in demand for different drugs in real-time.
Industrial Digital Twin
Manufacturing – AI-DT used in manufacturing is extremely important from the design phase to production phase. Having the ability to get real-time feedback from AI during the design process reduces if not eliminates the time back to the chalk board situations by providing real time feedback and recommendations during the design process. During the manufacturing process the automated manufacturing line can also update in real time if the digital twin realizes a more efficient procedure. Examples of companies in this space are Synopsys (SNPS), Cadence Design Systems (CDNS) and Rockwell Automation (ROK).
Smart Warehouse - AI-DT is used in smart warehousing to develop and maintain strategic storage and retrieval systems. With digital twin technology efficiencies to the supply chain can be tested and updated without physically rearranging the floor, robots or automation system. Examples of these companies are Symbotic (SYM), Kardex (KARN SW) and Daifuku (6383 JP).
The diversified uses of the digital twin technology are endless and not limited to the categories mentioned above and in fact will become a mainstay in all industries as the abilities of AI increase, chip production costs decrease with more competition and the cost of goods sold decrease in turn.