The R&D Tax Credit Aspects of Cognitive Computing

By , , and

        "Today we stand poised on the brink of a new era of computing in which technology is more consumable, insight-driven and cognitive", Ginni Rometty, IBM President and CEO .

        For decades, our interaction with machines has been dictated by the way they operate. People had to adapt to the manner computers work and not the other way around. Cognitive computing, however, is likely to put those days behind us. In this "new era of computing", the human brain becomes the model after which computer systems are designed.

        A growing number of companies are engaged in the once unimaginable task of re-engineering the world's most complex computer, the human brain. Activities within the field of cognitive computing are strong R&D Tax Credit candidates.

The Research & Development Tax Credit

        Enacted in 1981, the federal Research and Development (R&D) Tax Credit allows a credit of up to 13% of eligible spending for new and improved products and processes. Qualified research must meet the following four criteria:

  • New or improved products, processes, or software
  • Technological in nature
  • Elimination of uncertainty
  • Process of experimentation

        Eligible costs include employee wages, cost of supplies, cost of testing, contract research expenses, and costs associated with developing a patent. On January 2, 2013, President Obama signed the bill extending the R&D Tax Credit for 2012 and 2013 tax years.

Welcome to the Cognitive Era

        Manoj Saxena, business manager for IBM's Watson, says that 90% of the world's information was created within the last two years based on the volume of information created by computers and electronic sensors. The rise of "Big Data", defined as large data sets that are too large and complex to be analyzed by conventional means, calls for the development of new ways to process information. Traditional computing systems, limited by aspects such as processor speed and hardware scalability, are no longer good enough.

        In this context, a new generation of computing systems emerges, combining technology and biology and using the human brain as inspiration to build machines that are teachable, adaptable, and ultimately, intelligent. Cognitive computing incorporates the concept of neural network that, through the accumulation of knowledge and experience, allows for informed decision making and problem solving. In other words, the circuit of biological neurons of the human brain is reproduced in a series of non-linear statistical data modeling and decision making tools.

        General characteristics of this disruptive technology can be summarized as follows :

  1. Data-centric: ability to process an ever growing amount of data, both structured and unstructured (uncertain in nature).
  2. Designed for statistical analysis: ability to answer questions based on statistical raking and different levels of confidence.
  3. "Scale-in" architecture: performance improvements, including moving key components (storage, memory, etc.) closer to the data.
  4. Automated system and workload management: embedded with blocks of codes that communicate to each other and across different virtual machines.

IBM's Watson

        There has been considerable competition in the field of Big Data, involving both start-ups and major companies, such as Microsoft, Oracle, and SAP. IBM, however, has long been at the forefront of this race, particularly through its pioneering work on cognitive computing. According to the New York Times, the company's Big Data and analytics customers add up to more than 10,000 and its team is constituted of 9,000 business analytics consultants and 400 mathematicians .

        An early example of cognitive computing, IBM's Watson has marveled the world since its launching in 2011. Originally created to answer questions on the show Jeopardy!, Watson has consistently outperformed the quiz's former champions. Susan E. Feldman, author of the book "The Answer Machine", highlights four major breakthroughs brought forward by Watson. Firstly, the system integrates a Deep QA Technology, it "creates hypotheses to expand a question into hundreds of queries and then collects the evidence to support or destroy each hypothesis".

        Secondly, Watson is able to assimilate and analyze multiple sources of information (including unstructured data) at a scale no human being could ever match. Thirdly, the system presents an outstanding ability to integrate its more than 40 subsystems (such as natural language processing, categorization, search, logic, heuristics, knowledge, and machine learning) when performing its tasks. Lastly, Watson shows significant adaptability, which translates in the capacity to learn from its users and its body of knowledge.

        Potential applications and advancements for the Watson project are endless. An example is the use of human senses. IBM predicts that by 2018, computers will touch, see, hear, taste, and smell. For Bernard Meyerson, Vice President of innovation, computers will increasingly move from manipulating static data to exploring "the rich world of data processed by humans through the five senses". A few early examples include "smelling" computers that determine air pollution in human centers and image recognition software. Predictions point to a not-too-distant future when computers will be able to capture the so-called molecular biomarkers in human breath that identify health disorders, such as diabetes and epilepsy. They will also be able to listen to and interpret a baby's cry, identifying whether it is caused by hunger, pain, or tiredness, for instance.

How Cognitive Computing will change our lives

        IBM's Watson exemplifies how cognitive computing can change fundamental aspects of human life. In partnership with the Memorial Sloan-Kettering Cancer Center, IBM is developing a Watson-based decision support system for cancer research and treatment. The idea is to increase both the accuracy of diagnosis and the effectiveness of treatments through the use of evidence-based information. Watson's cumulated "knowledge" includes "more than 600,000 pieces of medical evidence, more than two million pages from medical journals and the further ability to search through up to 1.5 million patient records", an amount of data no human doctor's mind can match. When tested for lung cancer diagnoses, the computer's success rate was 90%, compared to an average of 50% for human doctors. One can only imagine how a wider deployment of similar technologies can revolutionize our health care system.

        Through the processing of unprecedented amounts of information, cognitive computing technology can not only change the face of medical diagnoses, but also contribute to monitoring and controlling disease transmission. This is particularly true in the case of new strains of highly drug resistant bacteria, the "superbugs". Cognitive computing can use predictive analysis to track and monitor disease transmission through hospitals, nursing homes, and the general population. Big Data multi agent computer modeling can also track a disease's geographic origins and match incidents against possible sources.

        Smart sensors, a fundamental aspect of cognitive computing, are another example. Such sensors differ from passive ones in their ability to process information and pick up on patterns that are used to efficiently control systematic operations . Current applications of smart sensors include multiple fields, such as smart building management and consumer technologies. Future advancements are very promising. A telling example is the development of nanobots (equipped with smart sensors), which will theoretically be capable of instantaneously sensing, diagnosing, and treating ailments within the body.

        Critical cognitive computing applications, however, go beyond health care. A good example is cyber security, one of the most serious economic and national security challenges we face as a nation, but according to President Obama, one that we as a government or as a country are not adequately prepared to counter. Cognitive systems represent a more efficient way to deal with challenges of ever growing complexity. The rising volume of data and the multiplication of mobile devices, social networks, and cloud environments make it impossible to face security threats through simple secure perimeters. In this context, Intelligence Security emerges as a means to prevent, detect, and address system breaches through continuous monitoring, diagnosing, and mitigation of threats.

Cognitive Wearable Technologies

        The decreasing size and mounting power of sensors have cleared the path to the development of wearable computerized devices. Smart watches, digital clothing, and eyewear are an emerging reality. Microsoft has recently joined Apple, Samsung, and LG in the race to develop wrist computers. Google's Glass Project, a wearable computer with a head-mounted display, has called the world's attention as it promises to make wearable gadgets mainstream.

        Some understand these new technologies as "cognitive prostheses". Similar to physical prostheses, which are created to replace, enhance, or correct certain capabilities, wearable gadgets offer the potential to improve human cognitive performance. In the case of smart spectacles, for instance, digitally augmented reality (that could be as simple as the artificial overlaying of labels and directional arrows) will enhance the user's view and understanding of the world. More generally speaking, internet-connected wearable devices can give people unprecedented capability in what comes to information, memory, data analysis, communication, among countless other fields. According to the research firm Gartner, wearable smart electronics are expected to be a $10 billion industry by 2016.


        The human brain is and will certainly remain an unchallengeable model for data processing. However, greatly beneficial advancements have been achieved by drawing inspiration from this complex biological machine. Future applications of cognitive computing are very promising and will most likely constitute a new technological era. Companies engaging in cognitive computing R&D activities may be entitled to significant Federal Tax Credits.

Article Citation List



Charles R Goulding Attorney/CPA, is the President of R&D Tax Savers.

Andressa Bonafé is a Tax Analyst with R&D Tax Savers.

Charles G Goulding is a practicing attorney with experience in R&D tax credit projects for a host of industries.

Similar Articles
The R&D Tax Credit Aspects of the 21st Century Cures Act
The R&D Tax Credit Aspects of Mechatronics
The R&D Tax Credit Aspects of Emotion-Recognition Technology
The R&D Tax Credit Aspects of Immunology
The R&D Tax Credit Aspects of Arthritis
The R&D Tax Credit Aspects of Asthma
The R&D Tax Credit Aspects of Telemedicine
R&D Tax Credits Enhance Life Science Impact Investing
The R&D Tax Credit Aspects of Pediatric Hypertension
The R&D Tax Credit Aspects of Parkinsons Disease Technology
The R&D Tax Credit Aspects of Legal Medical Marijuana
Reaching for the Moon: The R&D Tax Credit Aspects of Conquering Cancer
The R&D Tax Credit Aspects of Zika
The R&D Tax Aspects of CRISPR-CAS9
The R&D Tax Credit Aspects of Bioelectronic Medicine
The R&D Tax Credit Aspects of Liquid Biopsy Testing
The R&D Tax Credit Aspects of Cryogenics
The R&D Tax Aspects of Microbiome Research
The R&D Tax Aspects of Mouse Models in Clinical Research
The R&D Tax Aspects of Precision Medicine
The R&D Tax Aspects of Synthetic Biology
The R&D Tax Aspects of Pharmaceutical Packaging
New Standards and Regulations Create R&D Tax Credit Opportunities for the Pharmaceutical Packaging Industry
The R&D Tax Credit Aspects of Orphan Drugs
The R&D Tax Credit Aspects of Blood
The R&D Tax Aspects of Regenerative Medicine
The R&D Tax Credit Aspects of Environmental Remediation
The R&D Tax Credit Aspects of Gastro Technology
The R&D Tax Credit Aspects of Multiple Sclerosis
The R&D Tax Credit Aspects of the Internet of DNA
The R&D Tax Credit Aspects of Concussion Technology
The R&D Tax Credit Aspects of Schizophrenia
The R&D Tax Aspects of Cancer Treatment
The R&D Tax Aspects of the New FDA Mobile Apps Requirements
The R&D Tax Credit Aspects of the Medical Software Industry
The R&D Tax Aspects of Computer Enabled Human Identification
The R&D Tax Credit Aspects of Heart Disease
The R&D Tax Credit Aspects of Biological Drugs
The R&D Tax Aspects of Respiratory Diseases
The R&D Tax Credit Aspects of Cosmetics
The R&D Tax Credit Aspects of Major Life Science Benefactors
The R&D Tax Credit Aspects of the Health Cloud
The R&D Tax Credit Aspects of Autism
The R&D Tax Credit Aspects of 3D Bioprinting
The R&D Credit Aspects of Cell Therapy
The R&D Tax Credit Aspects of Sugar Substitution and Reduction in Food Products
The R&D Tax Credit Aspects of Gluten-Free Foods
R&D Tax Credit Aspects of Sleep Innovation
R&D Tax Credit Aspects of Medical Robotics
The R&D Tax Aspects of Neuroscience
The R&D Tax Credit Aspects of Hearing Technology
The R&D Tax Credit Aspects of Eye Disease
The R&D Tax Credit Aspects of Dermatology Innovation
The R&D Tax Credit Aspects of Bioinformatics
The R&D Tax Aspects of Lab Equipment and Instrumentation
The R&D Tax Aspects of Salt Reduction
The R&D Tax Aspects of Generic Drugs
The R&D Tax Credit Aspects of Novel Uses for Genetically Engineered Organisms
R&D Tax Credit Fundamentals
R&D Credits for Companies Combating Superbugs
The R&D Tax Credit Aspects of Alzheimers
The R&D Tax Aspects of Diabetes
The R&D Tax Aspects of Brain Mapping
R&D Tax Credit Aspects of Human Body Weight