By Ahmed El Adl, Ph.D.
December 7, 2016
Overall Vision, Categories, Applications and Reference Architecture Framework (Part 1)
Disclaimer: This is an ongoing and partially published work aiming to understand the overall concept of Cognitive Digital Twins (CDT) as the foundation for the next true-smart generation of machines, systems and businesses. It introduces the first definition of CDT and the required system-level cognitive computing architecture. It also summarizes the key categories and relationships of the cognitive digital twins and swarms.
I'm sharing this work here for your own education and hopefully inspiration. Most importantly, as you'll figure out after reading this "long" article, CDTs are a multidiscipline and very complex topic yet very inspiring and promising. Therefore, once you read the article in its entirety, please share it, share your comments and share whatever opinion you might have either online or with me directly.
Being Digital (by Nicholas Negroponte, 1996) and When Things Start to Think (by Neil Gershenfeld, 2000) as well as many R&D efforts done by many teams around the globe over the last decades introduced into the public psyche the potential emergence and the rise of smart machines. Recently, some companies adopted these ideas in their marketing campaign claiming an imminent change to a future where fully integrated and inherently intelligent self-organizing systems, subsystems, and components shall define the next generation of intelligent machines.
Additionally, the massive advances and major breakthroughs occurred in different areas of technology and science gave us a lot of optimism. However, this optimism is faced with the hurdles of removing the dead weight of old technologies and changing our current way of thinking to pave the path for new theories and concepts in the engineering and design of the future systems, which may lead to intelligent machines. An even greater challenge is integrating cognition and evolution capabilities in the design of such machines and systems.
Recently, the discussions about the IoT/IoE, smart machines, and cognitive systems created a lot of motivation, hope, and confusion. Therefore, some companies started different initiatives to discover and understand the possible implications and values of these new technologies to their current and future business. However, without major breakthrough results.
Unfortunately, many of these companies are afraid to delve deeper to be able to envision their future. Instead, they started retrofitting existing machines to designate them as “connected” and attach sensors to collect data in order to call them “smart”. They run workflows on steroids to claim “intelligence” in their analytics. Others are haphazardly collecting and feeding big (volume) data sets to existing software systems and voila – one has “cognitive software systems” listed as an attribute to post their sales numbers forgetting that the harsh reality will soon prove them wrong; the customer experience and opinion.
One reason for the current confusion, perhaps, is our general inability to ask correct questions. Let us step back and pose a few key questions. What machines, devices, and systems could be built with the tools and technologies at hand today and without further inventions? How should we design, build and use them? Do we really want to just connect everything and haphazardly collect large volumes of data? Is it all about the data? How can we enable smart machines to achieve specific tasks while learning to achieve even more and complex tasks over time?
Once we understood and answered those questions, we’ll be able put a plan for relevant innovation and drive effective transformation which will not only help us transform what we’ve to where we want it to be but also, we'll be able to envision and build the right systems, machines and businesses we need in the future.
“We should build smart systems, devices, and machines that can collaborate with us to augment our current physical and cognitive capabilities across and beyond our lifetime and the space we can physically exist in today”
We might agree about this ultimate goal. However, the debate rages on about answers to these and other related questions, which may be cryptic in bio-inspired designs and how nature is evolving to adapt and enhance the physical and cognitive capabilities of creators including humans.
The current breakthroughs in key areas such as “Digital Biology” coupled with Bio-mimicry (https://biomimicry.org/), cybernetics, and deep learning are elements, which when converged may offer completely new dimensions and approaches for real neuromorphic computing and bio-inspired systems and machines that can intelligently sense, learn, reason, act and evolve. This approach may be the Holy Grail.
The current advocacy to advance the principles and pervasive practice of digital twins calls for distributed cognitive and communication capabilities by design where systems can inherit, grow and share intelligence across different sub-systems as well as multiple generations of systems and machines.
Designing, building and managing of such bio-inspired systems and machines may require a new form of hardware-software design, architecture and integration paradigms we haven’t yet encountered. To do so, we’ve to adopt “Cognitive Digital First” way of thinking. This would require us to first design and build cognitive digital twins, which will digitally represent, augment and accompany a new generation of machines (The Physical Twins). Both the digital and physical twins will work in tandem to achieve the excepted tasks and functionalities.
“Cognitive Digital Physical Twins (CDPT) will continue optimizing their cognitive, digital and physical design and capabilities over time based on the data they’ll collect and experience they'll gain, not only based on models and data they we gave them or they inherited”
In this article, while I’ll try to avoid going into technical details and not to give you time-wasting financial predictions, I’ll try to explain my in-progress overall vision, definition, key categories as well as provide an initial reference architecture framework for the Cognitive Digital Twins (CDT) as I see today.
2- The case for Cognitive Digital Twins
2-1 The Noise, confusion and promises of IoT and Digital Transformation
Today, you can’t go to a conference, a meeting or even having a discussion with anybody without having to discuss or hear about the IoT and Digital Transformation. Both are important topics, however as you might have already experienced yourself, most of the discussions end nearly where it started; what is the IoT? Didn’t we already go digital since decades?
This is distracting many people from the real issues and exhausting valuable resources. Therefore, let us get things clearly defined that we can focus on real relevant innovation and challenges.
Today, IoT is being defined as the next generation of digital networking technologies and protocols, which are essentially required to connect a massive number of digital devices and transfer an unlimited amount of data in real time. This is, by all means, not a complete definition.
"The IoT/IoE should also provide the core technologies, platforms, and services required to build the future “Digital Ecology” where smart digital Things can be created, live, smartly act and interact as well as evolve in a manageable and secure way"
And what about Digital Transformation? Recently, companies are asked to digitally transform their business and finally start adopting digital technologies. Really? Didn’t we start digitizing the enterprise tasks, processes and functions many decades ago? And what about the large population of CNC machines and robots adding real values every day and everywhere in many industries?
“The current wave of technology-driven transformation should not be just a technology upgrade (app modernization) or adding more software to what we already have”
Over the past few decades, we went through different waves of technology-driven transformation as follows:
"The required transformation is not only digital, it is a digital cognitive transformation"
To do that, we should understand what does the concept of “Cognitive Digital Enterprise” mean. Cognitive Digital Transformation is way more than adding more analytics tools and gathering more data. Having this as the compass and way of thinking while defining and building the new cognitive enterprise around new smart products and digital services will enable a non-destructive yet efficient transformation to the next generation of smart digitally enabled, represented and augmented business.
2-2 The current approach
Some companies got it right and are being able so far to avoid getting stuck and sucked in the wrong and short- sighted terms and discussions about IoT, Digital Transformation, app modernization, Big Data ... etc. However, they’re starting to understand that retrofitting the current physical world as it is today by adding some sensors in and around existing products and haphazardly collecting and analyzing big amount of Data is just a temporary solution that didn’t prove its commercial viability yet and possibly never.
Additionally, it is clear that the current approach of transforming businesses and machines to digitally connected, created major challenges to many organizations without offering a viable proven solution. Some of these challenges are:
- Strategy: What is the right strategy to define and implement a technology-driven new digital business without disrupting the current business?
- Approach: Is the digital twin the right way to go? What does digital twin mean? Is it all about collecting some data?
- Platform: What are the required technology platforms, standards, protocols, and architecture?
- Mist vs. Fog vs. Cloud computing: What about edgeless distributed cognitive computing (EDCC)?
"Distributed Cognitive Architecture will soon end the dilemma of cloud vs. edge vs. mist computing"
- Cognitive capabilities: Do we need to add more data analytics tools or move to the new generation of real cognitive systems that can understand, reason and learn.
- Cyber-physical security: How are we going to proactively identify and prevent the cyber-physical security threats and risks during and after the transformation?
"The current approach of retrofitting machines and tweaking processes is not a feasible and risky approach especially as a long-term solution"
Therefore, many business and technology leaders are looking for a completely new approach to transform their current business and create new ones that they can stay relevant and lead in the era of cognitive business and smart machines.
2-3 The Cognitive Digital Twin (CDT): Background
Cyber-Physical Systems (CPS) are heterogeneous blends that combine digital computation, communication and physical world dynamics. They form the foundation of embedded systems (http://leeseshia.org/). The concept of digital twins was first advocated by NASA and became a key engineering concept of its space exploration programs. Advancing the concept of cognitive digital twins in practice must draw heavily from the advances in CPS reengineered using cognitive computing architecture and capabilities.
While cyber-physical systems (CPS) added a lot of values, they produced mainly digitally controlled machines with some embedded software, which can control some functions and collect and analyze little amount of data.
"The current efforts to create “Digital Twins” for existing machines have very limited vision if any. They're limited to a small set of functionalities with the main focus on operational effectivness and predictive maintenance"
"Digital Twins for enterprises are not just a couple of simple analytics cockpits applications"
This is not what a Cognitive Digital Twin of a Physical Twin should be. To get out of the current stagnation and confusing situation, we should start building physical systems, which will be by-design an integral part of intelligent Digital Twins that will accompany and augment them. The physical twin and the digital twin will construct the Cognitive Digital Physical Twin (CDPT).
This mindset and engineering approach are not only about implementing solutions around existing machines or processes to increase productivity or revenue. It is all about building a completely new generation of smart machines, cognitive software systems, as well as digitally connected services, which can be consumed by machines and humans.
2-4 The Cognitive Digital Twin (CDT): Definition
2-5 key characteristics and architectural principals of CDTs are:
- CDTs are highly interconnected distributed cognitive systems and in some cases, are very large complex systems of systems (SoSs).
- CDTs exist in the digital space and will evolve over time as their physical Twins evolve.
- CDTs will span physical and digital systems and soon us, the humans.
- They’ll be able to act, interact and collaborate across domains, physical and virtual worlds
- CDTs will continuously evolve to be able to autonomously take contextual decisions and execute more complex tasks in the digital as well as physical worlds (experience-driven behavior)
- CDTs and their physical twins will learn over time to identify, create and provide new services, which their early immature versions couldn’t offer.
- Cognitive digital twins may or may not have physical twins:
- Cognitive Digital Twins will have the abilities of physical and digital self-diagnostic and self-healing. For instance,
"CDTs would use techniques such as additive manufacturing or similar future technologies to autonomously design, manufacture and replace some defective parts of its own physical twin."
- CDTs will create a new massive economy around semi or fully automated digital smart services defined and offered by the CDTs themselves in collaboration with the physical twin(s) and possibly humans partners.
- The early generations of cognitive digital twins will be architected to do no mistakes. Therefore, they’ll have less intelligence and do a lot of mistakes. However, the following generations will be smarter by allowing them to try new things, do mistakes and autonomously learn out of it. Aren’t we so?
“The Cognitive Digital Twin will possess valuable knowledge and experiences gained and optimized over its lifetime. Therefore, it shall not vanish nor be destroyed once the life of the physical twin ended – The power of Mind Transfer and Evolution.”
3- The Cognitive Digital Twin: Architectural Framework
3-1 The new design and architecture mindset
CDTs are massive smart modular yet highly integrated and collaborative systems, where biologically-inspired architectures, autonomous cognition, and controlled evolution will be fundamental characteristics and capabilities.
"Inspired by the 11 billion years long brain and the neocortex evolution, Distributed Cognitive Architecture (DCA) is the future of smart systems and machines"
The design, implementation, and operation of cognitive digital twins will not be an easy task at least over the next few years. Nevertheless, the current systems and system-of-systems (SoSs) engineering theories and frameworks will fail short and can’t efficiently help us in building such systems.
"Model-based Systems Engineering (MBSE) techniques and tools should gain cognitive and evaluation capabilities that they can support the semi or, in some cases, full autonomous evolution of the digital and physical twins design and functionalities."
The advances in neuromorphic computing, which replaces the older emphasis on separate modules for input, output, instruction-processing and memory, showed us that machine intelligence should be addressed by both the physical as well as the digital design and architecture.
"A combination of traditional and neuromorphic computing would be soon the dominating computing architecture until a fully biologically-inspired computing architecture, hardware and software is mature enough"
Keeping this concept in mind while designing the physical and digital systems and machines will solve many problems we currently have in AI / ML. It'll also accelerate its patchy progress we’ve since decades. You can’t write couple of algorithms that you think are capable of doing smart things, train them with large set of data then upload them to a machine and expect that this machine will suddenly be smart. Therefore, a major shift in how we envision, architect and build systems and machines is required.
“We should abandon the Von Neumann’s model and principles of designing and building binary machines that can just compute. We should also free up ourselves from the mentality of Isaac Asimov of building robots that can do repetitive tasks for us (salves). Instead, we should start building biologically-inspired smart machines that will be our future counterparts, colleagues and possibly our adversaries”
However, over the next few years, some will be trying to stitch existing technologies together, extend protocols and standards that they can quickly implement workarounds and get the first generation of cognitive digital Twins designed and implemented. That is fine as a temporary approach as long as it doesn’t distract us from shifting toward the new approach of building such cognitive digital physical twins.
3-2 Cognitive Digital Twins : Key architectural building blocks
For the first wave of Cognitive Digital Twins, the following key architectural building blocks will be required:
3-2-1 Cognitive Digital Twin Core (CDTC) – The Core
The digital core would be the initial digital representation of the “Physical Twin” including its main initial states “as-designed”, “as-built”, “as-sold” and “as-configured”. Also, it’ll contain the initial states and core capabilities of the digital twin itself including the required systems and tools.
"The CDTC will have different metadata, core self-defense mechanisms as well as self governing rules to guarantee that the whole CDPT will function, evolve and used as intended"
The initial core will usually be kept unchanged over time. However, to enable continuous evolution of both physical and digital twins, minor additions or updates will be required and allowed based on specific sets of predefined rules.
3-2-2 Cognitive Digital Twin Anchors (CDTA) – The Data Workers
Real-time, historical and extrapolated data will drive the actions and the evolution of the CDPTs. Anchors will continually monitor and collect specific parameters, statuses and contents of interest from different local as well as external distributed data sources. They'll use data mining techniques to initially prepare the collected data. CDTA will use different cognitive capabilities (AI/ML …) and techniques to dynamically define the data structures and detect suitable sources.
"CDTA will use different techniques to extrapolate and generate own version of the reality based on varieties of parameters and rules such as; time, experience, context, situation, and self and/or environmental awareness - machine perception"
CDTA will be able to adapt over time that they can effectively deal with changes, which might happen to data structure, contents as well as the sources. They should use local and cross-systems capabilities to evolve its data models in a non-destructive way over time that the right data will be collected, structured, enriched, possibly converted to useful information and made available for usage.
CDTA are required for neuromorphic computing. Our current computing systems collect and store data based on predefined formats and rules. This data will be made available to different processes and tools on request. On the other hand, CDTA will collect data either based on predefined rules, dynamically defined rules or triggered by specific events. Usually, data will be sent directly to the destination(s) in a format that will enable faster reasoning and if needed immediate actions. This key architecture principal is a dominating architecture in the biological species. It is essential for cognitive smart systems and machines and will be made possible by CDTA - The Observing Machines.
3-2-3 Cognitive Digital Twin Surrogates (CDTS) – The knowledge Workers
Smart “Things” will have functions to be performed, characteristics to be maintained and interactions with digital and physical worlds to be made.
"Based on situational & context-aware cognitive rules, CDT surrogates are experts in a specific domain and will continuously create and update their knowledge to keep up with the evolution of the overall CDPT and its environment"
To do so, they’ll apply different knowledge discover and machine learning techniques on the data and information available to the CDPT from different sources. This up-to-date knowledge will enable the CDT to take more complex decisions and evolve the cognitive capabilities of the overall CDPT over time.
Additionally, CDTS will communicate their knowledge with different systems and subsystems of the CDT, its physical twin as well as other CDTs (e.g. within its digital Swarm). Complex sets of cognitive rules and skills will determine what, when and how to share knowledge and with whom. CDTS will continuously work with other CDT’s subsystems to update the rules used to gather, create and share knowledge across the lifetime of the CDPT.
3-2-4 Cognitive Digital Twin Bots (CDTB) – The Makers
CDTBs are creative highly specialized digital workers that can carry out complex and hybrid tasks either in the digital space (e.g. software algorithms) or in the physical space (e.g. to control a Humanoid on another planet or a machine on a smart factory floor).
"CDTBs are smart digital or digital-physical sub-systems designed and continuously learning to do specific tasks repetitively and intelligently. They will leverage the knowledge they gained to get smarter and share it back with their Cognitive Digital Twin"
Those CDTBs will evolve over time through learning by doing as well as the knowledge made available by the surrogates (CDTS). CDPTs will be able to autonomously define, create and train new CDTBs as needed.
3-2-5 Cognitive Digital Twin Perspectives (CDTP) – The interfaces
CDT perspectives will be responsible for multi-directional multi-channel communications and interfaces including communications with the physical Twin, other Digital Twins as well as Humans or non-human subjects and objects. A fundamental redesign of some of the current software engineering concepts such as APIs is needed.
"The current APIs have to be redesigned and extended to be able to support CognitiveDigital Physical Twin ProgrammingInterface (CDPTPI or simply TPI)"
TPIs will create one of the major new economies of the 21st century. They'll be the main interface to smart digital and physical systems and machines. To do so, we’ll also have to redefine M2M and M2H interfaces. This is mainly to compensate for the weakest point in such new smart digital world, the Humans, who can lack attention or mental clarity or just bored or biased for example.
"CDPTs will learn to adapt and evolve their communications capabilities, techniques, and styles with humans, other machines, as well as processes"
3-2-6 Cognitive Digital Twin Self-Management (CDTSM) – The Administrator
Cognitive digital physical twins will usually be large complex and distributed systems. Some digital components will be embedded in the physical twins and some physical components will be controlled by the digital twin. Managing the life cycle of such systems will be too complex and near impossible to do for humans. Therefore, a smart self-management system should be in place to manage the digital physical twins.
Managing the lifecycle phases of CDPTs will require a combination of advanced sets of software systems and cyber-physical management capabilities. In addition, they’ll at least partially manage the physical Twin as well. CDTSM will apply its cognitive capabilities to develop sophisticated project and program management skills similar to what humans possess today. Self-monitoring, proactive and event-driven self-diagnostic as well as robust digital and if possible physical self-healing should be key capabilities of these systems.
"CDTSM will manage the functions and evolution of both digital and physical twins to guarantee compliant actions and purposeful evolution"
CDTSM systems will evolve and be able to define, implement and enforce new self-management rules and tasks. The metadata and core functions embedded in the core of the CDT would define some fixed boundaries and rules for the self-management as well as self-evolution.
3-2-7 Cognitive Digital Twin Defense System (CDTDS) – The Guardians
Every Digital twin will introduce unprecedented vulnerability and risks to both Digital as well as physical worlds. Because of such possible devastating consequences, the current cyber security techniques such as intrusions detection and response are not enough to secure Cognitive Digital and Physical Twins.
Therefore, CDPTs should be designed so that danger and even serious intents of intrusions will be proactively detected and blocked through a bottom-up digitally and physically secure design. It should be able to use intelligent digital and physical techniques and tools to define and implement self-defense plans aiming to protect itself against any kind of harm, misuse or unauthorized use.
Context and environmental awareness will play crucial roles as well. Therefore, CDTDS will be able to override any external control including human control if needed, especially in massive digital or physical attacks situation with high-risk consequences where humans could be slow to comprehend and react appropriately on time.
"CDPTs will use advanced cognitive techniques to develop and evolve their self-defense plans and capabilities including reasonable preemptive actions against other CDPT(s) if needed"
4- The Cognitive Digital Swarm (CDS)
CDTs would socialize, collaborate and partner with another CDTs, which for example share the same interest or provide specific services they need. Such relationships and interests will make it beneficial for the CDTs to create Digital Swarms using specific rules and requirements defined by each individual CDT. Such rules will help the CDTs to identify, find, join and as needed leave digital swarm(s) on-time safely and efficiently. This should be part of the CDT’s core capabilities and be refined over time through continuous learning and balanced evolution.
“Cognitive Digital Twins will be like humans, they’re smarter, safer and more efficient if they communicate, share and collaborate with others”
Cognitive Digital Swarms will be able to create and share their collective intelligence and capabilities based on specific rules defined by every individual member as well as by the swarm collectively. “Swarm Intelligence” will make every swarm member capable of taking smarter decisions and carrying out more sophisticated tasks efficiently and in a more secure way.
"The cognitive digital swarms will use their collective cognitive and situational awareness capabilities to define own rules and identify new swarm members across the whole accessible IoE digital ecosystem and possibly invite them to join the swarm as needed"
Once created, the digital swarms will have their own sets of governance and collaboration rules, which will manage their joint activities together. The accessibility to the physical twins of digital swarm members will be in many cases exposed to more strict rules than the rules used to access the joint digital resources.
CDTs will be allowed to have simultaneous relationships with different digital swarms. However, rules should exist to guarantee that conflict of interests will be avoided and risks to the members will be minimized or preferably eliminated.
In some situations, digital swarms will need to join capabilities and abilities with other swarms to achieve larger common goals. Therefore, swarms will create “Digital Clusters” under specific circumstances. Imagine some digital swarms within a smart city joining capabilities and resources to enable the expected higher quality of life for its residents and visitors.
4-2 Key categories of cognitive digital swarms
For the first waves of digital swarms, I’m proposing 4 major categories, which will be helpful in increasing the values, stability, resilience as well as the security of Cognitive Digital Physical Twins and their Swarms as follows:
4-2-1- Strategic Digital Swarms
The participating CDTs will dynamically share the relevant digital and physical resources, take over tasks on behalf of the swarm or each other. They’ll make specific experiences available to each other that they can jointly achieve their individual and collective goals.
"Strategic digital swarms will not have detailed predefined specific goals. However, they’ll have common causes such as keeping the traffic flowing in a city or protecting the airports of a country or even run a company"
They’ll potentially define specific goals over time and driven by the current situation they're dealing with. The collective cognitive and physical capabilities, as well as the requirements of the swarm, will play a major role in defining and implementing the short and long term common goals.
For example, all the safety-related Cognitive Digital Twins of some or even all the US Airports will be by default and continuously a member of the national aviation safety strategic digital swarm. While every member will do its individual tasks of monitoring and securing its own airport, they’ll share security and safety relevant information instantaneously and in a smart way so that the unexpected security situations will be dealt with appropriately and proactively.
The DS members will also be able to carry out tasks on behalf of the whole DS or specific member such as accessing the physical twin, taking over control over specific equipment, whole building or soon commanding Robotic Security Guards (RSG), which are in fact CDTs themselves, to deal with a security situation in an airport or a school.
4-2-2 Joint Venture Digital Swarms
Under some conditions, two or more cognitive digital twins will collaborate to achieve a common predefined goal(s). They will work together to put a plan together as they go. For example, several smart factories are assembling the components and systems required to build a specific aircraft model based on the conditions specified in suppliers’ contracts. The different interdependencies between those factories such as What? When? Where and How? will dictate a temporary joint venture relationship between the CDTs of those involved factories across different vendors and geographies. They will work together to fulfill the contract conditions and deliver on time, budget, quantity, and quality. A swarm of the involved supply chain management systems will assist this manufacturing swarm.
"JV swarms would extremely streamline the manufacturing processes and lead to unprecedented levels of manufacturing automation, quality of products and cost reduction"
Once goals have been achieved, JV swarms will not be needed anymore. However, the collective experience should be shared and possibly used to jump start and optimize another joint venture to produce same product or even other products by the same JV swarm or the CDTs themselves within another swarm.
"CDTs will evolve through doing that they can provide higher efficiency, learn to do smarter and more complex tasks in smarter ways over time - continues unsupervised machine learning"
4-2-3 Outsourcing Digital Swarms
Every Cognitive Digital Twin and its physical Twin will have its strengths, weaknesses, and limitations by design. However, to guarantee focus and optimal use of the digital and physical resources, some limitations will continue to persist or new ones might occur temporary or even permanently due to different circumstances.
"CDTs will be able to learn by doing and even get rid of some of the design weaknesses and limitations"
To make Digital Twins as efficient as possible; outsourcing or crowdsourcing of some tasks will be essential capabilities for the digital twins as well as digital swarms. The relationship between the members of this type of digital swarms will be weak and temporary. Sharing information as well as physical resources will be limited to the bare- minimum required to do the common tasks.
4-2-4 Spatial Digital Swarms
The spatial locations of some or all elements of Cognitive Digital Physical Twins will make it beneficial in specific cases to establish a spontaneous or planned digital swarm based on current location or spatial requirements. In some cases, the spatial locations of the physical twins will not have to be near to each other for them to be part of a spatial swarm.
For instance, the CDT of my car will be continuously in a strategic alliance with my Human Cognitive Digital Twin and my smart Home Cognitive Digital Twin. Those Twins will construct my Personal Cognitive Digital Swarm. My PCDS will be the foundation for my Personal Cognitive Digital Assistant - CDA. My CDA will dynamically join spatial swarms with the relevant Public Cognitive Digital Twins and swarms to deliver the best and safest experience to me on the road, at home, at work or anywhere else all the time.
4-2-5 Anonymous Digital Swarms
Like humans, some CDTs will anonymously be a part of a digital swarm for a limited time until they achieve specific short-term goal(s). In this case, not much of information nor physical resources will be shared or at least it should be optional.
For example, the Cognitive Digital Twins of all cars at a specific traffic light will temporary and anonymously join a spatial DS including the CDT of the traffic lights controller itself as well as other related smart city public CDTs. They will work together to optimally and instantly control the traffic flow around this specific spatial location. This will be done within the larger context of optimal traffic management of the nearby areas as well as the whole smart city.
"Anonymous Digital Swarms will play a major role in the era of Cognitive Digital Physical Twins (CDPTs) especially because of the much-needed extra safety and security layers they provide by design."
The short-term goal(s) will be achieved without future commitments or sharing knowledge and experience. Also, access to the Physical Twins should be limited or completely avoided. However, for instance, in the above example, in some situations it would make sense that the swarm controller will be granted access to the breaking systems of one or more cars to avoid collisions or guarantee compliance with current traffic rules.
5- Key Categories of Cognitive Digital Twins
To effectively design cognitive digital twins, which will digitally represent and augment the physical world, we’ve to start with defining the “purpose of Life” of a cognitive digital twin in the context of the "purpose of life" of its physical twin and the environment in which the CDPT will have to fulfill its purpose of life. This will help us get a clear understanding of not only the initial roles and functions of the CDT but also define and enable the evaluation process for this specific CDPT which will enable it to achieve the expected purposes of life within its new digital ecological system while adding values to our life.
To make the first generation of CDTs as successful as possible, we should identify and define the major categories of cognitive digital twins based on mainly the categories of their physical twins. This approach will help us precisely identify the required existing and future technologies we need, focus the next innovation cycles on filling the gaps and accelerate the creation of the right CDTs.
Currently, I’m recommending to start with the following main categories for Cognitive Digital Twins:
5-1 Machines Cognitive Digital Twins (MCDT) – The Digital Physical Twin
This category of CDTs will be the most dominating category over the next years and will have a great impact on everything around us. MCDTs will help us rethink the way we design, build, use, maintain and operate machines, appliances, and devices.
"Creating MCDTs for existing machines will be our first exercise to better understand what smart machines are and how to design and build them"
MCDTs are not just an add-on or add-in. They go beyond IoT, Big Data Analytics, Ml/AI … It is a completely new way of design thinking and engineering approaches in designing, building and using machines and systems.
“Soon, our buying decisions as individuals and enterprises will be greatly influenced by the availability and the quality of a cognitive digital Twin for the specific machines, devices or appliances we would like to buy at and work“
We can see this happening today in different industries such as aviation, industrial machinery, and some consumer devices. Even offering simple data collection and predictive analytics capabilities around the operation of an aircraft or locomotive engine decides winners and losers today.
5-2 Human Cognitive Digital Twin (HCDT) – The Digital Avatar
The Human Cognitive Digital Twin will completely change us, our life and the way we live it. Imagine that our digital brain replica, medical record, education, social and work experience, as well as other information are combined together and stored in a Cognitive Digital Twin. This could create a limitless number of opportunities for us.
"Soon, we'll be able to use our HCDT to control our Robotic Avatar(s) not only on earth but also virtually anywhere in the universe. Are we the Avatars of other creators?"
HCDTs will make it possible to finally create the Bio-digital species, where our physical and cognitive capabilities will be truly augmented and freed up from many biological weaknesses and limitations. Our biological evolution will be accelerated and extended by the cognitive digital evolution.
Even the early versions of HCDTs would immediately have a tremendous positive impact on the quality of our life. For example, they’ll help us solve many health problems in cost effective and highly personalized way adding great values to our daily work and private life instantly.
HCDTs will help integrate us even more and efficiently with each other as well as into the physical world around us. A seamless collaboration between different CDTs of machines and objects at home, at work and everywhere in between will extremely increase our capabilities and enhance every aspect of our life.
“Human Cognitive Digital Twins are going to accelerate the rise of Cognitive Digital Assistants (CDA), which I do believe will be one of the major technological breakthrough over the next years and decades to come”
Additionally, HCDTs will be able to socialize, act and collaborate on our behalf. For instance, the HCDTs of a group of people who have the same disease would be bale to collaborate and share the right information in real time within a digital swarm of themselves, their doctors, scientists, and other medical services providers that the whole group can get the best medical care and highly personalized life assistance.
5-3 Objects Cognitive Digital Twin (OCDT) - Smart Things
The Objects Cognitive Digital Twins will enable and accelerate the digitization, digital representation, and augmentation of a large number of objects in the physical space. Those objects are not humans nor individual smart machines.
"The size and the level of complexity of OCDTs will vary dramatically based on the nature of the physical object they represent."
In many cases, machines, devices or other complex physical objects will be built out of a digital swarm of a very large number of OCDTs rather having just one MCDT.
For example, OCDTs of smart streets sensors within a smart City would dynamically join many other OCDTs and MCDTs of cars, traffic management systems, sensors, parking areas identifiers … to create a Digital Swarm representing a smart city. OCDTs might be soon the largest population of cognitive digital twins.
5-4 Enterprise Cognitive Digital Twin (ECDT) – The Cognitive Enterprise
Companies of different sizes and industries should understand that rethinking and integrating their current IT and OT landscape as well as their business models is NOT enough to survive and stay relevant in the era of Cognitive Digital Twins.
"Companies should rethink the very nature of their business models, the products they build as well as the services they provide to be relevant in the era of "Smart Everything"
Today, creating an overarching Cognitive Digital Twin representing the new digital core of the enterprise is partially possible. Soon, building a complete ECDT for the whole enterprise will be possible.
"ECDT-focused transformation would help define, guide and accelerate the creation of its future cognitive digital business, where products, solutions, services, processes, and people are intelligently connected and digitally represented and augmented"
Doing so will require a new organizational structure and business models, where automated cognitive business decisions will be taken by different CDTs and DSs and most probably in collaboration with counterparts of limited intelligence and data processing capacity and speed, the humans.
"Imagine a day, where the CEO, CFO or even the board of a company would be just a bunch of HCDTs, ECDTs, and MCDTs leading the new cognitive digital businesses"
The first generation ECDTs will mainly represent and augment own company core business. However, soon enterprise cognitive digital swarms will be created out of different CDTs:
- ECDTs of partners, suppliers and customers companies or functional area,
- MCDTs of own machines in their own factories, suppliers' machines or
machines they manufactured on customer's sites,
- HCDTs of own employees and in many cases their customers.
This category of CDTs represents the way I understand the “Cognitive Digital Enterprise” and how we should define and implement “Cognitive Digital Transformation”.
5-5 Special category: The Cognitive Digital Assistant (CDA) - The Digital Experts
Cognitive Digital Assistants are special category of CDT. CDAs are highly specialized digital experts that can learn and evolve to carry out complex cognitive tasks in the digital world. They’re digital twins without physical twins associated directly to them.
They would be able to help other categories of CDTs as well. For example, they would collaborate with HCDT to augment the mental and physical capabilities of a human. Also, they would be able to provide different cognitive digital services to CDTs as well as their associated physical Twins.
Soon, CDA would span and affect every aspect of our life and reshape every industry we’ve today. They’ve the potential to create a massive new economy; the economy of intelligent digital assistants.
"Like many new major technologies, CDAs will have even more serious social impacts and legal liability than other categories of cognitive digital twins. CDAs could be easily used to mislead people and even nations even before they realized that they exist"
CDAs started to create new categories of economy and jobs. However, they’ll take many white-collar jobs away, possibly in a very short time, while not being able to create alternative jobs for the same group of people.
Some of us would think that creating such Cognitive Digital Twins for machines or humans is a kind of science fiction. Partially, it is. However, I do believe that the innovations, technologies and knowledge we’ve today would be sufficient to get the first generation of real cognitive digital twins designed and built.
“If at first, the idea is not absurd, then there is no hope for it.” - Albert Einstein.
However, to be able to create real and reliable CDTs, fundamental changes must happen such as creating new engineering paradigms and architecture concepts top be used for envisioning and designing smart businesses, systems, and machines. Over the next few years, we’re going to build digital twins for some of the existing machines and businesses.
However, the ultimate goal should be to first design and build the cognitive digital twin then augment it with the required physical twins, not vice versa (Cognitive-Digital-First). Many of the machines and devices we’ve today will be replaced by bodiless virtual digital yet smarter machines sooner than many of us would have expected.
Another major change would be shifting our approach from building computing machines to building cognitive smart systems and machines, which can autonomously evolve, learn, reason with and without purpose and interact in a natural yet smart way.
"Cognitive Digital Twins and systems will have profound positive economic and societal impact on our life. However, they’ll spur disruption and raise major issues including moral and ethical issues. Therefore, the underlying architectures and designs of such systems and machines should address that and give us smart tools to deal with such issues and their consequences even before they happen."
However, we shouldn’t forget that dumb machines have proven to be more dangerous to us and our physical environment than the smart ones. Therefore, for us to be able to envision and build such smart systems and machines, we should stop being frightened by the thoughts that smart machines will someday take away our jobs, have control over us and possibly eliminate us. This is given that yes, they did already took away a lot of jobs. In the same time, they created a lot of new jobs, but different jobs for different people. This is the main reason for justified fears and rejection from some groups of people, who felt the real impact.
Nevertheless, some of us will continue inventing and building such cognitive digital physical twins (CDPTs) whether the rest of us will agree or not. The engine of innovation will never stop. It is just a matter of time and the machine cognitive capabilities will outmaneuver ours. This will happen sooner than most of us would think. Didn’t many devices and machines do that already today?
This major opportunity would help us to transform ourselves and be capable of doing more tasks beyond our current physical and cognitive capabilities as well as even beyond the time and space, where we traditionally existed and lived so far.
Therefore, either we approach smart machines and machine intelligence with an open mind and less fear that we can seize this opportunity or we’ll have to deal with the profound consequences of being outsmarted, outdated or even irrelevant. Now, the choice is ours!