Data-in-Motion Capability

Torch.AI Launches CARBON. Enhanced Data-in-Motion Capability for the NEXUS EDO platform.

Leawood, Kansas— October 22, 2019 —Torch.AI announced today that it has launched a new machine learning library, Carbon™ to further enhance data handling capabilities for clients with complex data and data handling workflows.  Carbon™ is included in Torch.AI’s flagship machine learning framework, the NEXUS EDO™ (Enterprise Data Orchestration) platform. The new Carbon™ library will begin being rolled out to clients at no additional cost during the first quarter of 2020.

“Data in motion is data generated continuously by an ever increasing number of data sources.  We saw an opportunity to help customers evolve from processing this deluge of data in a sequential record-by-record basis.  With Carbon™, we have a specialized library of business rules common to our enterprise and public sector clients that can be applied inline to enrich the data while it is in-motion, saving money, time and improving the ability to scale trust across systems, data, and people” said Jae Cha, Founder and Chief Technologist.

“One example that is pretty fun is with a client that needed to detect, flag, and obfuscate personally identifiable information (PII) with low latency. Because Carbon™ already has business rules defining PII, we can rapidly deploy agents to solve the problem with just a few clicks. For them, Carbon™ enables real-time PII detection and routing in the most complex data environments. It will easily save hundreds of thousands of dollars in the first year alone, exclusive of the risk mitigation” added Jon Kramer, Partner and Director of Engineering.

With the recent passing of California’s Consumer Privacy Act (CCPA) and the EU’s General Data Protection Regulation (GDPR), as well as impending US Federal law, identifying, protecting, and responsibly actioning on PII has never been more important. But beyond PII, the Carbon™ advantage is the ability to identify sensitive data in motion, as it is entering or leaving customer environments, enabling on the fly processing and protection based on popular business rules including legal, compliance, security, and privileged access needs.

Torch.AI’s NEXUS EDO™ is a next-generation Enterprise Data Orchestration solution optimized for extremely complex data environments for customers making critical decisions. The software enables advanced integrations, enrichment of data-in-motion, and analytics.  Nexus is designed to ingest both structured and unstructured data while providing a streaming “smart data pipe” optimized for advanced applications of machine learning. The system is uniquely scalable and extensible, able to support most BPM, CRM, ERP, and analytics applications.


About Torch.AI

Torch.AI is on a mission to enable machine augmented trust at scale. The platform offers rapidly deployable augmented intelligence technologies that use unique data ingestion technologies and advanced techniques to provide an automation and judgement solution within a convenient framework.

Through the lens of network-centric intelligence, variable detection and change are illuminated and displayed in real-time, facilitating opportunities for improved decisioning with outputs needed to measure and optimize performance. With built-in connections for entity search, classification and investigation modules, Torch.AI can quickly and dynamically surface out-of-range variables without manual intervention. Learn more at

john wasko

John Wasko, PhD Joins Torch.AI, Leads Federal Mission Sector

Washington, D.C.—September 16, 2019—Torch.AI today announced that John Wasko, PhD has joined our team, serving as a Managing Principal, Federal Mission Sector Lead.

John brings near 30 years of experience as a member of and then directly supporting the Department of Defense (DoD). Prior to joining Torch.AI, Dr. Wasko worked at Deloitte Consulting as a Specialist Executive/Leader focused on mission growth within their Federal Defense, Security and Justice practice. In that capacity, John led delivery in net new engagements supporting DoD clients in data visualization, cyber analytics, cognitive automation, and operational strategy. He was instrumental in recruiting both senior and junior talent whose mission experience accelerated the quality and scale of client delivery. He led the firm’s capture efforts resulting in a 10-year $7B IDIQ (Indefinite Delivery/Indefinite Quantity) award focused on Technology and Innovation.

Prior to joining Deloitte, John served over a quarter century on active duty (Army) achieving the rank of Colonel.  He is a multi-tour combat veteran recognized on multiple occasions for outstanding performance including a below-the-zone promotion, course honor graduate, and 1st time selections to the Command & General Staff and Senior Service Colleges. Tactical assignments over his career included Airborne and Air Assault units at the company through brigade level. At a strategic level, John has served on the Army Staff, multiple Combat Support Agencies, and as a principal staff member in a functional Combatant Command.

John’s educational background is equally noteworthy; an engineering degree from West Point, operations research MS from Georgia Tech, and culminating with a doctorate in design, measurement, and statistics from the University of Maryland at College Park. He has been published in multiple refereed journals and been an assistant professor on the United States Military Academy and North Carolina State University faculty. John has applied that education to address critical operational challenges at the National Security Agency, Defense Information Systems Agency, and the United States Cyber Command.

Torch.AI is currently on a hiring spree, adding additional team members in both Kansas City and in a new Washington, D.C. office near Dupont Circle to better serve public sector clientele.


About Torch.AI

Torch.AI is on a mission to enable machine augmented trust at scale. The platform offers rapidly deployable augmented intelligence technologies that use unique data ingestion technologies and advanced techniques to provide an automation and judgement solution within a convenient framework.

Through the lens of network centric intelligence, variable detection and change are illuminated and displayed in real-time, facilitating opportunities for improved decisioning with outputs needed to measure and optimize performance. With built-in connections for entity search, classification and investigation modules, Torch can quickly and dynamically surface out-of-range variables without manual intervention. Learn more at

Supplier Integrity

Torch.AI and Deloitte Partner to Improve Supplier Integrity for Australian Army Aviation

Washington, D.C. – September 13, 2019 – Torch.AI, the leading machine learning and enterprise data orchestration platform to scale trust, announced today that it has agreed to partner with Deloitte Consulting Pty Ltd to deliver machine enabled product-trace-ability solutions to the Australian Department of Defence. The program will enhance the client’s ability to improve supplier integrity through the illumination of complex supplier networks, data discovery, ingestion, orchestration and risk analytics.  Uniquely, the platform offers continuous vetting and monitoring through the use of two Torch.AI products, NEXUS EDO and the company’s ILLUMINATION application.

Torch.AI has pioneered an evolved the approach to identifying, assessing, and neutralizing risks associated with the global and distributed nature of product and service supply chains. The global economy presents unique and complex challenges when applying risk methodologies with the goal of safeguarding government and large commercial supply chains from emerging threats and vulnerabilities. The presence and influence of adversarial foreign governments, poor manufacturing and/or development practices, counterfeit products, tampering, theft, malicious software, etc., are examples of supply chain risks that must be mitigated. Federal agencies, government contractors, suppliers, and integrators use varied and non-standardized practices, making it difficult to consistently evaluate, measure, and neutralize threats to a particular supply chain.

Torch.AI has developed several specialized software solutions that autonomously interrogate complex networks that can be concurrently persistent and ad-hoc, solving several challenges in the Supply Chain Risk Management sector.


About Deloitte Australia

The Australian partnership of Deloitte Touche Tohmatsu is committed to growth, client service and its people – 790 partners and more than 8000 people located in 14 offices across the country, plus Papua New Guinea and Timor-Leste.

To sustain its momentum, Deloitte continues to invest in innovative new services, products and people, while expanding its business through acquisitions, alliances and organic growth.

Learn more about Deloitte in Australia.


About Torch.AI

Torch.AI is on a mission to enable machine augmented trust at scale. The platform offers rapidly deployable augmented intelligence technologies that use unique data ingestion technologies and advanced techniques to provide an automation and judgement solution within a convenient framework.

Through the lens of network-centric intelligence, variable detection and change are illuminated and displayed in real-time, facilitating opportunities for improved decisioning with outputs needed to measure and optimize performance. With built-in connections for entity search, classification and investigation modules, Torch can quickly and dynamically surface out-of-range variables without manual intervention. Learn more at

Security Clearance Vetting

Torch.AI to Support New $75 Million U.S. Department of Defense Program to Modernize Security Clearance Vetting

Chantilly, Va.— May 28, 2019—Perspecta Inc. (NYSE: PRSP), a leading U.S. government services provider, announced today that it has been awarded an Other Transaction Agreement  (OTA) from the Defense Security Service (DSS) and Defense Information Systems Agency (DISA), to support the continued reform and modernization strategy for the National Background Investigation Service (NBIS). The two-year award represents new work for the company and has a potential ceiling value of nearly $75 million.

Under the agreement, Perspecta will work to update and rebuild the Department of Defense (DoD) personnel security vetting and adjudication technology apparatus. The goal of the program is to make the personnel security clearance process faster, scalable and more secure through an innovative delivery model. Specifically, the company plans to leverage commercial-off-the-shelf solutions combined with its advanced data analytics capabilities and expertise in emerging technology areas such as big data, cloud, artificial intelligence and machine learning, to deliver a new, more agile process to support DSS’ rapidly evolving needs.

“Perspecta is a leading DoD mission partner in supporting the development of a trusted workforce model that can meet evolving national security demands and better support the dedicated personnel involved in background investigations and adjudication,” said Mac Curtis, president and chief executive officer of Perspecta. “We applaud DoD’s efforts to drive bold, transformational change in technology and will provide an unmatched combination of proven innovation and intellectual property (IP), scalable agile development/security/operations (DevSecOps) expertise and intimate knowledge of the security clearance vetting process to our DSS customer.”

To deliver the DSS OTA program, Perspecta has partnered with Torch.AI; C3 IoT; Pegasystems, Inc.; CA Technologies (A Broadcom Company); Accenture Federal Services, LLC; Prime Technical Services, Inc.; and Next Tier Concepts, Inc.

Additional information can be found here:  Defense Security Service & Defense Information Systems Agency : Partnering with Industry to Protect National Security

About Torch.AI

Torch.AI is on a mission to enable machine augmented trust at scale. The platform offers rapidly deployable augmented intelligence technologies that use unique data ingestion technologies and advanced techniques to provide an automation and judgement solution within a convenient framework.

Through the lens of network-centric intelligence, variable detection and change are illuminated and displayed in real-time, facilitating opportunities for improved decisioning with outputs needed to measure and optimize performance. With built-in connections for entity search, classification and investigation modules, Torch can quickly and dynamically surface out-of-range variables without manual intervention. Learn more at

About Perspecta Inc.

At Perspecta (NYSE: PRSP), we question, we seek and we solve. Perspecta brings a diverse set of capabilities to our U.S. government customers in defense, intelligence, civilian, health care and state and local markets. Our 260+ issued, licensed and pending patents are more than just pieces of paper, they tell the story of our innovation. With offerings in mission services, digital transformation and enterprise operations, our team of 14,000 engineers, analysts, investigators and architects work tirelessly to not only execute the mission, but build and support the backbone that enables it. Perspecta was formed to take on big challenges. We are an engine for growth and success and we enable our customers to build a better nation.

William Beyer

William Beyer Joins Torch.AI’s Board of Directors

LEAWOOD, Kansas—May 17, 2019—Torch.AI today announced that William Beyer, founding partner of Deloitte’s federal practice, has been elected to Torch.AI’s board of directors.

Mr. Beyer brings more than 30 years of direct experience in the Federal marketplace to Torch.AI.  “Bill is widely regarded as one of the most effective professionals in the Federal arena, especially within the National Security and the Intelligence Communities,” said Brian Weaver, Chairman of the Board.  “He is already engaged with our teams in both D.C. and Kansas City to continue to evolve how we select and support key mission areas.”

Before joining Torch.AI, Mr. Beyer was one of four partners to establish Deloitte’s Federal consulting practice which today boasts more than $3 billion in annual revenue. He was responsible for clients across both the civilian and defense landscape.  Bill personally led the top 12 strategic accounts for the firm.  In his most recent role, he led the Deloitte’s West Coast innovation group and established Deloitte’s Space practice. In just the past year Bill has been interviewed by Fed Radio, Politico, and ABC for his insights on Space and innovation.

Bill brings expertise in scaling enterprises in professional services and technology.  Prior to Deloitte, he led the Federal Health practice at Booz, Allen and Hamilton, growing the unit into the largest professional services practice for that sector in the world.  He sat on the UN’s Council for Aids Relief in Geneva and worked with top global health organizations and countries to combat epidemics across the globe.

Early on, his entrepreneurial talents became evident when Bill led Xerox Corporation’s entry into China, establishing a robust base of operations in the emerging economy.  He lived in Shanghai and served as General Manager and Director of China Operations responsible for all aspects of sales, service and manufacturing.  Bill was the youngest senior manager in the company’s history.  In less than two years, Xerox became the largest document management company in the continent.

“I am excited to be joining the board of a company that is squarely on the forefront of evolution through AI.  Many companies talk a big game and label themselves as AI firms.  Torch has done what most dream of, actually implementing mission critical solutions across the commercial and Federal landscape”, said Mr. Beyer. “Brian Weaver is a true entrepreneur with a unique creative spirit. He leads with consistency of execution, focus and vision.   It’s a privilege to work with him and Torch.AI to protect our homeland and furthering the use of software and data to help humanity, the enterprise, our world.”


Torch.AI is currently on a hiring spree, adding additional team members in both Kansas City and in a new Washington, D.C. office near Dupont Circle to better serve public sector clientele.


About Torch.AI

Torch.AI is on a mission to enable machine augmented trust at scale. The platform offers rapidly deployable augmented intelligence technologies that use unique data ingestion technologies and advanced techniques to provide an automation and judgement solution within a convenient framework.

Through the lens of network centric intelligence, variable detection and change are illuminated and displayed in real-time, facilitating opportunities for improved decisioning with outputs needed to measure and optimize performance. With built-in connections for entity search, classification and investigation modules, Torch can quickly and dynamically surface out-of-range variables without manual intervention. Learn more at

blockchain legislation

Malta’s Blockchain Legislation: A Modern Approach to Tech Law, Ethics

On July 4th, 2018, The Republic of Malta adopted three bills establishing a robust regulatory framework for DLT (Distributed Ledger Technology), blockchain and cryptocurrency. The country, known as “blockchain” island, believes establishing clear rules and guidelines around these emerging technologies will attract entrepreneurs, innovation and technology companies. Regardless of Malta’s motives, the bills and dialogue surrounding the new legislation highlight the magnitude of the legal and ethical challenges created by technology, specifically those born out of DLT, blockchain, cryptocurrency, and artificial intelligence.

While the capabilities of robots and artificial intelligence is far from the Hollywood headlines of killer-bots wiping out humanity based on some self-generated ethics, technology is stressing our current legal frameworks and it’s time to evolve. In Rachel Wither’s Slate Article, The EU Is Trying to Decide Whether to Grant Robots Personhood, she recounts the story of a Dutch citizen whose artificial intelligent twitter-bot tweeted “at” a fashion show, “I seriously want to kill people.“ Despite the AI not liking fashion, and its response being a little freaky, it also brings up a plethora of legal questions that our current system isn’t equipped to handle. Was a crime committed? By who? Was there intent? Is anyone liable if public resources were used to respond to the threat? What if somehow the AI was able to harm people at the event, then what? I won’t go down the rabbit hole, but this real event scratches the surface of the challenges the legal industry faces resulting from disruptive technologies like blockchain and AI.



Perhaps of more immediate relevance, legal scholars now believe that autonomous artificial intelligence are close (if not already capable) of independently creating legal entities, like Limited Liability Companies (“LLC”) . Do we want legal status and rights given to organizations created by algorithms? Even if we don’t, can we stop them from having rights under current law? If AI’s are left unchecked to create, winddown, and transfer assets between entities, what stress does that place on anti-money laundering efforts, or on establishing liability in the event of a breach of contract or negligence? Even if you can establish an AI owned entity is liable, if they can quickly create new organizations in favorable jurisdictions and transfer funds electronically, how would judgements be enforced and carried out? The complexity of these challenges is not unique to AI and are shared by DLT and blockchain. The magnitude of the legal and ethical issues caused by these disruptive technologies are dizzying, leaving many scholars throwing up their arms uncertain of where to begin. However, as the issues above illuminate, we potentially risk significant disruption of our global economy if laws and ethics don’t catch up to technology, and we are long past the time for serious action.

While Malta’s legislation may lead to more questions than solutions, the effort should be commended for grappling with some of these issues and moving the conversation forward. Additionally, Malta’s legislative action creates a much-needed environment for legitimate and ethical utilizations of cutting-edge technologies to flourish and differentiate themselves from illegitimate solutions and outright fraudsters. While it remains to be seen if Malta’s efforts will stimulate significant economic activity, their efforts coupled with industry self-regulatory initiatives are critical to creating an environment where consumers and businesses can better identify those services and organizations committed to creating trust and legitimacy. Further, Malta’s leadership will force other jurisdictions across the globe to consider whether they want to participate in creating an ecosystem for legitimate modern business or operate in a grey economy. We should keep a close eye on the continued debates and discussions coming out of Malta as they just might foreshadow global debates and challenges to come.


Bayern, Shawn J., The Implications of Modern Business-Entity Law for the Regulation of Autonomous Systems (October 31, 2015). 19 Stanford Technology Law Review 93 (2015); FSU College of Law, Public Law Research Paper No. 797; FSU College of Law, Law, Business & Economics Paper No. 797. Available at SSRN:


Contributions to This Article Were Made by Clayton Pummill. Clayton is a Principal at Torch.AI focusing on legal, privacy, and cyber solutions for federal and corporate clients.  

Blockchain Technology

The Risk Blockchain Technology Poses to Supply Chain Visibility

Most nations are competing for economic stability, military superiority, and improved living standards among other reasons. Increased technological advancement has contributed to the increased rivalry between countries with China and the US being the best example of two states that are competing for superiority. In this paper, the risks posed by Blockchain technology to supply chain visibility will be addressed. As the name suggests, Blockchain technology is an economic transaction digital ledger programmed to record financial transactions and others valuable information which is linked using cryptography (Iansiti and Lakhani 04). Supply chain visibility is the availability of components, parts, or commodities in transit to be traced from the producer to the final destination with the aim of strengthening and improving the supply chain by making information readily accessible to all involved parties.

Although the blockchain technology poses numerous benefits, some of these advantages such as anonymous trust, streamlined and fast transactions may make it hard for states to track sales which possess different risks to countries. The first risk is the sale of sensitive data which may threaten the security of a nation. In most cases, attacks on a nation are mainly conspired by individuals who have support from the country’s citizens who have access to sensitive data and they sell this information on the black market which has been made easier through blockchain. Additionally, the sale of drugs and weapons has been made possible by this innovation, and it negatively affects a country’s stability.

Blockchain also encourages illegal importation and exportation between countries since people can easily purchase or sell products anonymously and effectively (Fincham 01). The first disadvantage of this move is the reduced tax for the affected states since most people who use this method evade from paying taxes which in return reduces a government’s earnings. Governments depend on taxes to finance its projects, which means that reduced taxation will hinder project implementation. For instance, if China fails to collect enough revenue to fund its mega-project, then it might be forced to seek other sources of finance which might be expensive or extend the time limit for completing the project.

Moreover, such illegal exportation through blockchain technology may harm a state’s internal market in cases where imported goods are cheaper compared to those offered internally. In such cases, most firms are forced out of business since they are unable to compete over those that have imported products to the market illegally. Additionally, those firms that use this technology to acquire cheap raw materials can produce and sell their products and services at a lower price. This move puts some firms at a disadvantage and are forced to take up measures such as shut down some of their branches, reduce wages, or lay off employees which in the long-run affect a country’s economy. In other cases, customers can use this technology to directly purchase cheap products globally a move that reduces local firms’ sales and revenues. Additionally, blockchain technology fails to specify standards to be followed during purchases which have adverse effects on a state’s economy (Palamariu).

In conclusion, it is evident that blockchain may significantly affect several logistic activities which at the long-run jeopardize a country’s economy. It is therefore essential for different stakeholders such as government, suppliers, investors, and customers among others to develop ways to regulate the use of blockchain technology with the aim of enhancing a fair and competitive market. Different states should come together to moderate the use of blockchain technology and prevent instances of illegal trade. They should implement strict international policies aimed at curbing the risks mentioned above.

Supply Chain Risk

Advancements in Battery Technologies and their Impact on Supply Chain Risk

The market for Lithium-ion batteries was 67GWh in 2016 and expected to increase in 2019 to 75GWh, which is an increase from the 5.7GWh a decade ago in the United States. The growth is due to the increased demand for the Li-Ion battery fueled by the ever-expanding areas of applications and the tremendous profits gained over the years. From the early 1990s to 2010, the battery market was dominated with the portable electronic consumers. However, the field of application expounded with the introduction of smartphones and mobile phones. More recently, the acceleration of the growth is based on the urge to revolutionize the automotive industry venturing in clean energy for their products such as powertrains and electric cars. The need for clean energy and control of cobalt overexploitation, which results in environmental degradation, has facilitated the process of power innovation. The increased demand for sustainable batteries has led to advancements in technologies aimed at efficiency while escalating the supply chain risks.

Battery Technologies

Battery technologies have resulted in the invention of super-batteries with distinctive lives and performance. The major factors that have driven the technological integration in the battery sector are the need for reliable performance and efficiency. The efficiency is the measure of battery life by the type of application. The reliability is the power it supplies in a certain time. Due to the invention of portable power consumers such as mobile phones and iPads, the need for longer lasting batteries emerge. The embedding of battery technologies in automotive sectors also enhances further research on reliable energy sources. The electric cars and the electric trains demand powerful batteries able to sustain their performance over a period. Therefore, battery technological revolution tends to optimize the life and battery power to achieve better performance (Scrosati, Jürgen and Werner p.67).

Over the years, battery technological revolution has transpired all over the world. Researchers have invested in studies aimed at improving the performance of the batteries by charging in seconds and lasting for months. Surrey University has indulged in the production of energy and storage through contact. Their main idea is to generate power through contact between two elements and harvesting. The harvested power is stored and used later. The University of California has also invented the gold nanowire batteries. The batteries are 1000 times smaller than the human hair and withstand 200,000 times recharging without indication of degradation. The cracked nanowire batteries never die. Other battery technologies include the Grabat graphene batteries, which give the electronic cars a driving range of 500 miles without a recharge. The University of Rice has invented a laser-made micro-super-capacitators technology. The battery can recharge 50 times more than the current super-capacitators and discharge slower too. These technologies are aimed at improving the performance of batteries (Pistoia p.45).

Supply Chain Risk

The increased demand for better performing batteries results into overexploitation of cobalt affecting the rates of supply. The extraction escalates the exposure to environmental hazards. Overexploitation also leads to increased air pollution resulting from wastewater drainage into the rivers. Currently, considering these factors, the government of Congo has decided to shut down the Katanga Cobalt mines leading to low supply (Eichstaed p.43). Shutting down the mines renders people jobless leading to low living standards with raised cost of living. According to (Eichstaed p.56) the cost of living in Congo is 147% higher than in the United States. Since machines need batteries to operate, the government may have divided opinion on reinstating such mining activities considering their adverse effects on the environment. Therefore, the major Cobalt supply chain risk is overexploitation in contrary to the mining policies especially in Congo (Huggins p.23).

In conclusion, the demand for lithium-ion batteries has increased the in the United States in the past decade. Battery technologies aim at producing super-batteries with high-performance power and prolonged lives. The battery industry has undergone numerous technological revolution leading to the introduction of batteries such as the Grabat graphene batteries, which provides 500 miles drive for electronic cars without a recharge. The significant Cobalt supply chain risk is the overexploitation in contrary with the government policies, such as in Congo, leading to environmental degradation.


Scrosati, Bruno, Jürgen Garche, and Werner Tillmetz. Advances in Battery Technologies for Electric Vehicles. , 2015. Internet resource.

Pistoia, G. Lithium-ion Batteries: Advances and Applications. , 2014. Internet resource.

Huggins, Robert A. Advanced Batteries: Materials Science Aspects. New York: Springer, 2015. Internet resource.

Eichstaedt, Peter. Consuming the Congo: War and Conflict Minerals in the World’s Deadliest Place. Chicago: Lawrence Hill Books, 2018. Internet resource.

Network Economics

Network Economics in the Era of Artificial Intelligence

In its primary context, a network is a foundation upon which humans are interconnected to each other in what they do. In the globalized world, the primary issue is the consideration of the numerous choices that people and businesses have to undertake in the information era. The origin of the understanding of network economics is traced back to the classical work of Cournot (1838). The theorist was the first economist to explicitly state the relationship between the competitive price where there is an intersection of the demand and the supply curves. Another scholar who postulated the idea was Pigou (1920), who described it in the perspective of setting out a transportation network that comprised a system-optimized and a user-optimized solution.

In the present day, the emergence of artificial intelligence means that humans have awakened to the reality of machine learning where information is now perceived in a more computerized manner. One key area that has been of focus in the concept of the “strength of weak ties” was postulated by sociologist Mark Granovetter in 1973. It is the primary basis in the analysis of social networks, especially in the process of linking the micro and macro entities in the sociological theory (Granovetter 1360). A more challenging theme that has come up with the emergence of network economics in AI is connected by six degrees of separation. The model postulates that anyone on the planet can link up to another person in six steps. It follows that when one is connected in a given dimension, there is a chance that there is more linkage than they can perceive.

The process of networking requires that the elements of strong and weak ties are both factored because even though they perform varying functions, they extend the potential beyond the reasonable reach. When formulating the theory, Mark Granovetter describes that there are various interpersonal theories that exist between disparate groups and that these ties constitute what holds different units of the society. Humans thus tend to multiplex relationships so that they represent weak ties to some of their connections and strong ties when they link with others. It is, therefore, comparable to a network multiplexer that has varying relations and that constitutes diverse types of signals.

According to the theorist, the relevance of these ties is perceived in social networking.  A strong link is thus viewed in economics as a group of geeks who are conversant with what is expected of them in a given field, such as clinical or science. They are always abreast of the information as it comes and is informed of what information is happening and going in the given field that they have specialized in. The subject of weak ties thus results from the apprehension that it is tenuous forms of relationship where they do not seem to be much conversant in clinical or on the particular scientific field that is being discussed. Despite being on the edges of influence, they are not informed of the advances in health and clinical science issues. It is worth noting that according to the theorist, these characters are crucial because they form the building of strong ties group together through the effect of bringing circles of contact in a central place and the process strengthening the existing relationships. They are important because as a result of their presence, it is possible to share the information on clinical issues and scientific trends between the different groups.

The other application of the theme of network economics is in the concepts of Artificial Intelligence (AI). The pertinent example is the case of Artificial Neural Networks (ANNs) where it is described as the powerful relation through the use of multivariate tools for dependence analysis. They have initially been applied in the neuroscience, but have recently gained media attention especially, in economics and finance. The significance of ANN therefore is that it can be used for modeling purposes and in the prediction of outcomes, because it uses machine language. These associations are relevant, because while the goal has always been to improve and replace the use of manual processes through automation, much had not been explored on the possibility of designing machines that demonstrate intelligence comparable to that of humans’. The realization that humans could as well multiply their human intelligence through artificial means has thus ended in major advancements in the civilized world. The concept of strength and weak ties is especially important in ensuring that bindings relationships are established that are long-lasting as it is the principle of this form of network. Thus, artificial intelligence has been of great advantage, because it has been possible to bring out the emotional quotient into machines with many appreciating the advancements. With the far-reaching applications that have been witnessed, it is intriguing to think of how much impact there will be in the coming decades and years.


Granovetter, Mark S. “The Strength of ‘Weak’ Ties.” American Journal of Sociology, 78, no. 6, 1973, pp. 1360–1380.

Applied Behavioral Modeling

Machine Learning in Applied Behavioral Modeling


After researchers had done specific studies to understand the human action and patterns of life including their environments, lives, behaviors, and motivations, they need to know how to present the obtained information and create a design that will result in successful representation. Individuals act differently from one another; thus, it is possible to collect different conversations and observations from various people to access human behavior and action. The user profiling and modeling are some of the examples that have been used as an evaluating system to predict the user’s behaviors for a given period. In user profiling, the personas represent various types and groups of the subject to enable the designers to develop appropriate solutions in reiterative processes. Although clear guidelines for using computer derive ad-hoc dynamic persona-types to classify life patterns and behaviors has not been established, an idea can be developed to guide on the same. The paper aims to reflect on the concept of using computer derived ad-hoc dynamic persona-types that relate to social networking, experience, and human actions.

Applied Behavioral Modeling

The construction of the profile and applied behavioral modeling for the users is based on studying their behavior patterns, cognitive features, and demographic data. Such features help provide a practical approach to represent the user’s interests and preferences. The focus of such an ad hoc dynamic involves assessing the interactions of the user with a system and do not deal with complex social networking like educational hypermedia or focus in serious games. Most of the computer-derived models are created to describe market behaviors, and they use personas or user models for representation. The model users provide a precise way to think and communicate about how the persona think, behave, what they wish to achieve and why (Fernandez-Llatas et al. 15434). The motivations and behaviors of the persona are observed and represented throughout the design process of a computer-derived model. The persona must be regarded with a considerable sophistication because using their stereotypes or generalization would not be enough to produce a clear representation. Besides, discretion and vigor have to be applied to identify the meaningful and significant patterns in the user’s behaviors and utilize the acquired information represent a broad cross-section of the persona. The dynamic information modeling focuses on personality and diverse computing experiences.

Further, utilizing the dynamic information of the user could be used to create a system that can adapt to the user dynamically. The ability of the system to adapt to the user is essential in identifying and highlighting potential users as well as predicting their behaviors. Thus, it is significant to understand that dynamics in modeling deals with lifestyles, ages, IT consumption, and space. The dynamic information is substantial, especially in the studies involving ceremonies interactions and social activities involving teenagers (Fernandez-Llatas et al. 15436). Ceremonies, especially the traditional ones provide typical social activities that enhance the sense of belonging to the members of the family, which are passed through generations. Thus, the custom is inheritable, meaning it will be predictable in the future as the young people grow up to become the target audience of such traditional ceremonies. Therefore, if the designers of the computer-derived ad-hoc dynamic can identify such potential from the users and derive data from the right source, they can support some observations like cultural heritage.

Another suitable example used in computer-derived models is the social interactions among teenagers, mainly through technology usage. Studies have established that although the youths are actively using technology to look for new friends on social media platforms, the economic status can limit their modes of communication. Generally, teenagers have limited finances, and most of the IT products or media platforms offer such services at a certain fee (Fernandez-Llatas et al. 15434). However, the older teenagers can find financial freedom later in life and develop heightened attentiveness and dependence on the Internet; thus, making them the primary target audience of the IT products and consumption, which is a concept that can be applied to predict the near future.

Benefits of technologies such as graph database in sociology

Technological advances have developed beneficial programs that do not require static patterns to process event data, particularly that of human behaviors and actions. For instance, the graph database has been used for data storage and representation. The key concept of this database is the graph, edge or a relationship of the observations and behaviors that relate the data items in storage directly. The relationship represented in the graph database allows the stored data to be linked or combined it to create a successful representation (Huang et al. 3). Besides, process mining technology enable the sociologists to facilitate workflow interpretation from certain event records and reports while conducting studies. This technology interprets graphs that are understandable by the experts studying human behavior patterns using the routine actions recorder by ambient intelligence environments. Thus, it is easier for the experts to comprehend the process of human action as well as deduce a comparison using the previous inferences to identify particular behavior patterns or changes.


The process of analyzing human behavior patterns is extensively used for several research fields, especially in sociology. Most sociologists consider the use of IT and age as dynamic attributes of the user’s profile while conducting a study to classify behaviors and pattern of life. The applied user’ profiles and applied behavioral modeling should reflect their changes in hypermedia experience as well as behavioral changes based on demographic settings and interests. Thus, the research design using computer derived ad-hoc dynamic persona-types to classify behaviors and pattern of life has to consider the anticipated changes in lifestyle, age, IT consumption, and economic status of the user.


Fernández-Llatas, Carlos, et al. “Process mining for individualized behavior modeling using wireless tracking in nursing homes.” Sensors 13.11 (2013): 15434-15451.

Huang, Ko-Hsun, Yi-Shin Deng, and Ming-Chuen Chuang. “Static and dynamic user portraits.” Advances in Human-Computer Interaction 2012 (2012): 2.