Why the U.S. Must Lead the World with Intelligent Infrastructure


Americans have been through a great deal in the last two decades. In addition to the network effect that consolidated wealth in a few zip codes, we endured rapid globalization that benefited other nations at the expense of our own, the 9/11 terrorist attacks, multiple wars, and the global financial crisis, all within the first few years of this millennium.

To put this series of interconnected events in perspective, the collective shock is roughly comparable to the impact of a small super volcano, a minor asteroid, or a limited nuclear war. Catastrophes of this scale are thought to be of sufficient size to change the course of modern civilization, depending of course upon our response.

The most recent CBO report forecasts the U.S. federal debt at 150 percent of gross domestic product in 2047, which would place the U.S. as the third most indebted nation in 2017 between Greece and Lebanon. This is obviously not where the U.S. wants to be in 30 years. Fortunately, such a decline is unnecessary and well within our power to avoid, though the path is narrow and hazards are many.

Catching up on deferred maintenance is a necessary but insufficient plan for the challenges facing Americans. A modern strategic infrastructure plan should be focused on unleashing the current national economy similar to previous eras with the intercontinental railroad, interstate highway system, or electric grid.

The focus should be maximize benefits from our inventions, engineered systems and technologies to recreate a sustainable competitive advantage. One benefit of lagging behind other countries in infrastructure is that much progress has been made in recent years. Future projects can be embedded with hardware that enable intelligent networks, which can then be managed with distributed operating systems enhanced with artificial intelligence (AI) to meet the diverse needs of our society.

AI systems can substantially resolve many of the destructive forces and high-risk areas facing the modern economy, including the ability to provide far more effective governance in a highly complex data-driven world, prevention of most types of human-caused catastrophes, improved workplace productivity, more effective security, and reversal of the dangerous trajectory in healthcare costs.

In order to realize the full potential of a national intelligent infrastructure strategy, it must be planned in a highly specific manner. Intelligent infrastructure is driven by physics and engineering, which can be easily damaged by misguided or corrupted politics. The value of AI systems is substantially dependent upon the availability and integrity of data. Important priorities include but are not limited to interoperability, security, privacy, business modeling, cost of ongoing maintenance, and adaptability for future innovations.

The combination of technical viability in AI systems with the current macro economic scenario has created a perfect storm for public-private partnerships. Funds with trillions USD under management are in search of improved yields in mid to long-term bonds that offer lower risk profiles and diversification, which allows risk transfer to investors for specific projects rather than tacked on to an unsustainable national debt trajectory. Moreover, the combination of intelligent infrastructure with AI systems can improve productivity, provide attractive return on investment, and create new high paying jobs that will be competitive far into the future.

The federal government should act as the policy and standards body to avoid hard lessons learned in previous national infrastructure programs. A plug-and-play architecture is needed that encourages economic diversification in all states, fosters new business formation and new wealth creation that has the capacity for reversing the increasingly historic wealth gap.

In today’s fast moving hyper competitive world, the U.S. cannot afford to wait a century to unravel the type of monopolies that were cobbled together during the formation of the electric grid. The network economy increasingly represents the entire economy so must be as diversified and dynamic as society if to remain healthy and sustainable.

If the Trump administration and U.S. Congress seize this historic opportunity for a strategic intelligent infrastructure plan, they should find bipartisan support as it can positively impact every zip code in America, which could serve to reunify the nation around common good. Executed well, a strategic intelligent infrastructure plan can serve as a solid foundational platform to solve many of the current and future challenges facing America and the world.

Mark Montgomery is the founder and CEO of Kyield, originator of the theorem ‘yield management of knowledge’, and inventor of the patented AI system that serves as the foundation for Kyield: ‘Modular System for Optimizing Knowledge Yield in the Digital Workplace’. He can be reached at markm@kyield.com.

E-book on AI systems by Kyield


My ebook “Ascension to a Higher Level of Performance” is now available to the public.

Learn about the background of Kyield and the multi-disciplinary science involved with AI systems, with a particular focus on AI augmentation for knowledge work and how to achieve a continuously adaptive learning organization (CALO).

 

ebook-kyield-ascension-to-higher-level

TABLE OF CONTENTS

INTRODUCTION ……………………………………………………………………………………..

REVOLUTION IN IT-ENABLED COMPETITIVENESS …………………………………………..

POWER OF TRANSDISCIPLINARY CONVERGENCE …………………………………………..

MANAGEMENT CONSULTING ……………………………………………………………………

COMPUTER SCIENCE AND PHYSICS…………………………………………………………….

ECONOMICS AND PSYCHOLOGY ………………………………………………………………..

LIFE SCIENCES AND HEALTHCARE……………………………………………………………

PRODUCTS AND INDUSTRY PLATFORMS…………………………………………………….

KYIELD OS …………………………………………………………………………………………..

THE KYIELD PERSONALIZED HEALTHCARE PLATFORM ………………………………….

ACCELERATED R&D: THE LIVING ONTOLOGY ………………………………………………

SPECIFIC LIFE SCIENCE AND HEALTHCARE USE CASES …………………………………

BANKING AND FINANCIAL SERVICES ………………………………………………………..

THE PILOT PROCESS ……………………………………………………………………………..

EXAMPLE: BANKING, PHASE 1…………………………………………………………………

PHASE 2…………………………………………………………………………………………….

PHASE 3…………………………………………………………………………………………….

PHASE 4…………………………………………………………………………………………….

CONCLUSION: IN THIS CASE THE END JUSTIFIES THE MEANS …………………………21

 

Visit our learning center to download this ebook and view other publications from Kyield at the confluence of AI systems, crisis prevention, risk management, security, productivity and organizational management.

A Visit From America’s Founding Fathers – New Year’s Eve 2016


‘Twas the week after Christmas, when all thro’ Wall Street,

Not a broker was working, not even a tweet;

401ks were chock-full from the Fed,

In hopes that someone else would put their crisis to bed;

Investors were contented with the size of their yachts,

And dreams teased of eternity on Mars with toy bots;

Small businesses were suffering, employees quite stressed,

Working part-time jobs so that others may rest,

Then storm clouds of democracy began to gather,

So I dashed from my office to see what was the matter.

I threw on my coat and ran to the train station,

Hoping that a miracle could restore this great nation.

The moon shined brightly on glistening ice,

But a cold wind on Main St. punished rolling the dice,

When, to my great surprise what did we hear?

Could that be rumblings of a government we need not fear?

With corporate jets scrambling, and lobbyists screaming,

Something awful scary must have caused this convening.

More rapid than geese in flocks they came,

And he whistled, and shouted, and called them by name;

“Now, PENCE! now, ROSS! now, TILLERSON and COHN!,

On, SESSIONS! on, CARSON! on, PRUITT and MCMAHON!

To the New York penthouse! to the top of Trump Tower!

Now heal thy economy! Make great again this power!

As surgeons faced with a pandemic of moral hazard,

When trust in institutions remained torn and shattered,

So off to the capitol as physicians they flew,

With jets full of billionaires, and Donald J. Trump too.

And then, high above the plains jet engines roared

Then screeching of tires with titans on board.

As people left offices, churches, and schools,

They whispered to each other “hope we weren’t fools”

They were dressed in fine clothing from head to foot,

Some flashing gold like some kind of crooks;

A belly full of solutions in the cargo bay,

More false promises or will they do as they say?

From heaven above the Founders looked down,

Their eyes – how wise! Their faces full of frowns!

Although they expected the corruption found below,

It still pained to witness this nation they bestowed.

So they sprang to their sleigh, a founding force of seven,

And gathered their writings; then descended from heaven,

They flew straight to the rooftops above the West Wing,

And scurried down a chimney to the room in shape of a ring;

Leaders from all three branches gathered with their teams,

Who sat silently listening, voices finally out of steam,

When ghostly founders read their papers, it was quite a sight!

Closing in unison – WE’RE NOT LEAVING ‘TIL YOU GET THIS RIGHT!

Copyright © 2016 Mark Montgomery. All Rights Reserved.

Independence Day Lessons on Adaptability and Survival from the Ancestral Puebloans


Aroma Pueblo, by Betsy Genta-Montgomery Copyright 2016

Aroma Pueblo by Betsy Genta-Montgomery Copyright 2016

July 4th, 2016

The photo above represents a learning opportunity especially relating to survival and adaptation. Recently completed by my wife Betsy[i], the artwork was inspired by our visit to the Acoma Pueblo a few months ago, which is one of the oldest continuously inhabited communities in North America. Ancestors of current residents have lived on top of a 360-foot tall rock tower since 1150 A.D.

Their previous home was located on an even more formidable tower across the valley similar to the rock mesa in the center of Betsy’s art piece. Legend has it that a bolt of lightening shattered the steep rock steps leading to their old village so the Acoma people moved to the current location.

Other than the occasional battles with other Native American tribes, the Acoma people lived for generations at a time in relative peace until interrupted by major events that would change the course of history. The first major event occurred in the form of a 50-year drought that forced the Ancestral Pueblo peoples from the Chaco Canyon to other locations throughout the Southwestern U.S.

A second history-changing event for the Pueblos began with the arrival of the Spanish around 1540. The relationship between these two very different cultures was peaceful for several decades until a series of mishaps led to the horrific Battle of Acoma Pueblo. After two days of traditional warfare, modern technology in the form of cannon proved decisive for the Spanish in winning the battle. Tragically, the Spanish officer in charge ordered savage retribution followed by many years of slavery, ultimately leading to the bloody Pueblo Revolt eight decades later when tribes joined together and drove the Spanish out of the region.

Taken together, the Acoma Massacre and Pueblo Revolt represent an extreme case of leadership failure that decision makers from all walks of life can learn from. A single horrific decision by one military leader on a single day nearly two centuries before the American Revolution still brings pain and influences decisions throughout the region over four centuries later, and no doubt influenced many a negotiation.

The centuries that followed offered more turmoil for the region under the control of Spain, Mexico, and then finally the United States in 1848, but today the Acoma people are applying modern business methods in making the best of a challenging situation, seizing opportunities, and improving their future while preserving their cultural roots and traditions. The Acoma Pueblo own and operate cultural facilities at ‘old Acoma’ as well as the Sky City Casino Hotel and travel center, which is a significant employer and economic engine on I-40 between Albuquerque and Grants, New Mexico.

In addition to visiting with the friendly people at the old pueblo, who graciously welcomed a diverse mix of international tourists during our Easter weekend tour, we also enjoyed visiting the San Esteban del Rey Mission. A Catholic mission founded in 1629 that required 12 years to complete, the church is 150 feet long with vigas spanning the entire 40-foot width. The timber used for the vigas were harvested in the San Mateo Mountains 30 miles to the north and were transported by the Acoma people by foot. The adobe walls of the church are seven foot thick at the base on one side and five on the other. Adjacent to the church is their historic cemetery made of soil carried manually up steep steps carved out of the sandstone cliffs.

My takeaway

The Acoma people and their story represent a fine lesson for business and community leaders in adapting to radical changes beyond their control, despite extreme culture clashes and harsh environments. Lessons learned from the Acoma Pueblo can no doubt be applied to many around the world (see UNM business case summary).

Among the most important responsibilities each of us face during our brief life is taking charge of our own learning. Only then can we begin to make decisions as independent thinkers free from indoctrination, conflicting interests or agendas of others, which is prerequisite to becoming mature adults and valuable citizens prepared to contribute, particularly in a democracy in the vital role of informed citizens and consumers. This responsibility to others and ourselves never ends in our conscious lives, so we should grasp opportunities to learn and grow at every reasonable opportunity.

Leaders have a greater responsibility to practice continuous learning in order to maintain a high state of awareness in relevant matters; particularly in the type of highly complex, tumultuous and hypercompetitive environments we face today. Those few I consider great leaders then apply wisdom gained from experiential learning to rise above short-termism to contribute more to our world than they extract.

Although much easier to claim sustainability than to achieve, important lessons on stewardship can be learned from other cultures and eras. Our Founding Fathers of the United States for example studied many cultures and governance models before collectively deciding on a specific type of democracy in our constitutional republic.

Visiting the Acoma Pueblo

The old Acoma Pueblo is located about 60 miles west of Albuquerque a few miles south of I-40 on a good paved road. We spent the night at one of several motels in Grants, NM on our visit, which is a pleasant 40-minute drive by car. Visitors must park at the Sky City Cultural Center located at the base of the rock tower, which houses the Haak’u museum, Y’aak’a Café, gift shop and conference rooms, providing an experience similar to a national park. Walking tours are regularly scheduled with a short mini bus ride from the cultural center up to the village, which consists of over 250 family-owned dwellings still without water or electricity, some portion of which are still full-time residents with the remainder used by families during cultural and religious ceremonies.

About the author:

Mark Montgomery is the founder and CEO of Kyield, which has been a pioneer at the confluence of human and machine intelligence for two decades.

[i] Though quite similar to ‘Old’ Acoma Pueblo, it is not a replica. Betsy has a unique style of mortar sculpture over wood with different thicknesses for depth perception and shapes, natural woods, and oil paint.

Priority Considerations When Investing in Artificial Intelligence


IMG_7892.JPG

After several decades of severe volatility in climatology across the fields involved with artificial intelligence (AI), we’ve finally breached the tipping point towards sustainability, which may also represent the true beginnings for a sustainable planet and humanity.

Recent investment in AI is primarily due to the formation of viable components in applied R&D that came together through a combination of purposeful engineering and serendipity, resulting in a wide variety of revolutionary functionality.  However, since investment spikes also typically reflect reactionary herding, asset allocation mandates, monetary policy, and opaque strategic interests among other factors, caution is warranted.

The following considerations are offered as observations from my perch as an architect and founder who has been dealing with many dozens of management teams over the last few years.  The order of priority will not be the same for each organization, though in practice are usually similar within industries.

Risk Management and Crisis Prevention

The nature of AI when combined with computer networking and interconnected emerging technology such as cryptography, 3D printing, biotech and nanotech represents perhaps the most significant risk and opportunity in history.

While the global warnings on AI are premature, often inaccurate, and appear to be a battle for control, catastrophic risk for individual companies is considerable.  For most organizations the risk should be manageable, though not with traditional strategies and tactics.  That is to say that AI within the overall environment requires aggressive behavioral change outside comfort zones.

Recent examples of multi-billion dollar investments in AI include Google, IBM, and Toyota, though multi-million USD investments now number in the thousands if we include internal investments and venturing.  To be sure much of this investment is reactionary and wasteful, but the nature of the technology only requires a small fraction of the functionality to prove successful, which can be decisive in some markets.

For appreciation of the sea change, common functions employed today were deemed futuristic and decades in the future just three or four years ago.  So it’s not surprising that a majority of senior management teams we’ve engaged in the last two years confirm that AI is among their highest priorities, though I must say some are still moving too slow. We’ve observed a wide range of actions from window dressing for Wall Street to confusing to brilliant.

The highest return on investment possible is prevention of catastrophic events, whether an industrial accident, lone wolf bad actors, systemic fraud, or disruption leading to displacement or irrelevance.  Preventable losses in the tens of billions in single organizations have become common.  Smaller events that require a similar core design to prevent or mitigate are the norm rather than the exception, but are often nonetheless career ending in hindsight, and can be fatal to all but the most capitalized companies.  We’ve experienced several multi-billion dollar events in former management teams that likely could have been prevented if they had moved more quickly, including unfortunately loss of lives, which is what gets me up at 3am.

Talent War

An exponential surge in training is underway in machine learning (ML) along with substantial funding in tools, so we can expect the cost of more common technical skills will begin to subside, while other challenges will escalate.

“In their struggle against the powers of the world around them their first weapon was magic, the earliest fore-runner of the technology of to-day.  Their reliance on magic was, as we suppose, derived from their overvaluation of their own intellectual operations, from their belief in the ‘omnipotence of thoughts’, which, incidentally, we come upon again in our obsessional neurotic patients.’’ — Sigmund Freud, 1932.

The challenge is that the magic of the previous century has evolved and matured by necessity from the efforts of many well meaning scientists, but some of the magicians on stage still suffer from neurosis.  Technology is evolving much faster than humans or organizations.

Examples of talent issues commonly found in our communications:

  • Due to long AI winters followed by the recent tipping point in viability, the number of individuals with extensive experience is very small, and most are at a few tech companies attempting to displace other industries.

  • Industry-specific expertise beyond search and robotics is rare and very specialized with little understanding of enterprise-wide potential.
    An exceptional level of caution is warranted on conflicts in AI counsel due to competency and pre-existing alliances.

  • Despite efforts to exploit emerging opportunity, ability to think strategically in AI systems appears to be almost non-existent.

  • CTOs may win some key battles in tactical applications, but CEOs must win the wars with organizational AI systems.

The talent war for the top tier in AI is so severe with such serious implications that hundreds of millions USD have been invested for key individuals.  Of course very few organizations can compete in talent auctions, which is one reason why the Kyield OS is so important.  We automate many AI functions that will be common in organizations and their networks for the foreseeable future while also making deep dive custom algorithmics simpler and more relevant.

Historic Opportunity

Not only is AI a classic case of ‘offense is the best defense’, when designed and executed well to enhance knowledge workers and customers, the embedded intelligence with prescriptive analytics can accelerate discovery, uncover previously unknown opportunities, providing historically rare potential for new businesses, spin outs, joint ventures and other types of partnering.  Managed well, this is precisely what many companies and national economies need.

Architectural Design

Impacting every part of distributed organizations, the importance of architecture cannot be overstated as it will influence and in many instances determine outcomes in the distributed network environment.  AI is a continuous process, not a one-off project, so it requires pivotal thinking from two decades of fast fail lean innovation that our lab helped pioneer.  Key considerations in architecture we incorporated in the Kyield OS include but are not limited to the following:

  • Optimizing the Internet of Entities

  • Governance, compliance, and data quality

  • Accelerated discovery and innovation

  • Continuous improvement

  • Real-time adaptability

  • Interoperability

  • Business modeling

  • Relationship management

  • Smart contracts

  • Security and privacy

  • Transactions

  • Digital currency

  • Ownership and control of data

  • Audits and reporting

  • Productivity Improvement

A priority outcome for most organizations in competitive environments, productivity improvement is increasingly derived from optimizing embedded intelligence, which is also desperately needed to improve the macro global economic situation.  A large gap remains in most AI strategies with respect to enterprise-wide productivity, which represents the foundation of recurring value to organizations and society, regardless of the specific task of each knowledge worker and organization.

While cultural challenges and defensive efforts are common obstacles to any productivity improvement, strong leadership has proven the ability to triumph.  Internal and external consultants and advisors can help, particularly given the steep learning curve in AI;  just be cautious on unhealthy relationships that may have interests directly opposed to the client organization, as conflicts are pervasive and tactics are sophisticated.

Trust

Just when we thought trust couldn’t become more important, it seems to dominate life on earth.  We’ve come across quite a few trust related issues in our AI voyage. A few examples that come to mind:

Intellectual property:  Trust is a two-way street, particularly when it comes to intellectual assets, so upfront mutual protection is a necessary evil and serves as the first formal step in establishing a trustworthy relationship, without which the other party must presume the worst of intentions.  Once the Kyield OS is installed with partners this problem is effectively eliminated with smart contracts and digital currency based on internal dynamics and verified intelligence (aka evidence).

Fear of displacement:  Since AI is new for most, suffice to say that fear is omnipresent and must be dealt with in a transparent and intelligent manner. At the knowledge worker level we overcome the problem with transparency, which makes it obvious that the Kyield OS is likely their strongest ally.

Modeling:  While motivation to change is often needed from external sources such as regulatory or competition, it’s probably not a good idea to trust a company that has the capability, desire, culture and incentive to displace customers.  Another problem to avoid at the confluence of networked computing and AI is lock-in from technology or talent, including service models.  Beware the overfunded offering that attempts to buy adoption and/or over-reliance on marketing hype.

Authenticity:  Apart from the serious structural economic problems caused by copying or theft of intellectual work, consider the trustworthiness of those who would do so and how much know-how is withheld because of this problem.  Authenticity is especially important in this field due to the length of time required to understand the breadth and depth of implications across the organization and network economy.

Conclusion

Given the strategic implications to organizations, AI should be a top priority led by senior management.  However, since supply chains face similar challenges with AI, traditional methods and channels to technology adoption may not necessarily serve organizations well, and in some cases may be high risk.  Whether for strategic intent, financial return, operational necessity or any combination thereof, investing well in AI is not a trivial undertaking. Integrity, experience, knowledge and freedom from conflicts are therefore critical in choosing partners and investments.

About the author

Mark Montgomery is the founder and CEO of Kyield, which is based on two decades of self-funded R&D.  The Kyield OS is designed around his patented AI system, which tailors data to each entity in the digital network environment.

We must empower a more diversified economy in 2016


Austin Christmas Hat 1

Those of us growing up in the 1960s and 1970s experienced tumultuous times that had some similarities to the last decade. Among many other contributions from our generation—which include both positive and negative influences—were some great artists, one of whom Bob Dylan is featured in a massive IBM ad campaign. Dylan’s poetry is timeless and quite relevant today:

The post WW2 era we grew up in provided the best economic conditions the world has ever known. The baby boom population explosion, of which I am at the tail end of, combined with vast sequential gains in productivity to create the ‘miracles’ of economies in the U.S., Japan, Germany, and China among others, or so it seemed.

Although a few credible experts have warned all along that the world’s trajectory wasn’t sustainable, and perhaps most of us intuitively realized same, the financial crisis contained a potential silver lining in revealing the stark naked truth: much of that ‘success’ in the post war era came at the direct expense of the future, and the bills are coming due.

Although woefully deficient in ethics with poor visibility of systemic risk—even in cases where desire for prevention existed, master politicians and financial engineers in both the public and private sector have masked structural problems in the economy for decades—from the public and each other, by employing ever-more complex short-term remedies in a misguided game of musical chairs.

Unfortunately, the resolution of the financial crisis has consisted primarily of the very same type of financial engineering—it’s the only hammers central banks have in their toolbox. While central bankers are justified in pointing fingers at political and fiscal malfeasance, it’s up to humble citizens like me to hold up a mirror and suggest that they take a look to see that such malfeasance would not be possible if not empowered by monetary policy.

One certainty is that the super majority of consolidated malfeasance in much of the world has been transferred to the balance sheets of central banks and national debt at direct cost to billions of people, many of whom followed the rules, not least those who saved all their lives just as their public institutions recommended.  Those savings have been taxed for nearly a decade now by monetary policy rather than a democratic process; by devaluation of currency, record low (or negative) interest rates, inflation from asset bubbles such as commodities and housing, and the need for hundreds of millions to tap their principal for survival. Also certain is that regardless of whether or which stimulus measures were necessary, one outcome has been a dangerous expansion of the wealth gap now at record level in the modern era.

It’s very important to better understand that the previous wealth gap peak in the 1920s was partially causal to the Great Depression and WW2, among other earlier great revolutions and loss of life. Today’s billionaires seem to understand the moral hazard and potential for backlash, which is presumably one of the reasons for the philanthropic pledges. A nice gesture that will hopefully do much good, philanthropy is not an alternative for economic diversification, though can help if targeted for that purpose.

The financial crisis represents precisely how corrosive moral hazard is realized at dangerous levels that can reach critical mass, which could be triggered by unforeseen events.  Moral hazard is a psychological phenomenon, which occurs from regulatory, governance and policy failures that then combine with the ensuing economic weakness to cause the next crisis.  In this case the trigger was regulatory failure followed by heavy-handed resolution that caused massive collateral damage, further harming innocent citizens worldwide. In such cases where the non-virtuous (aka vicious) cycle is not interrupted by a moral realignment, typically through accountability by the justice system, strong credible governance, and adoption of new systems that punishes crimes and rewards beneficial behavior, then civilizations can and do rapidly decline.

In hindsight from a high level view, from a hopefully wiser former business consultant who has studied related phenomenon for decades now, it appears that we enjoyed a long period of one-off exploitations of planet and people combined with ever-increasing public debt and corruption supporting promises by politicians and institutions that were far beyond their means to deliver.

The bad news is that the combination of public debt and future liabilities tragically promised by politicians—and now expected—some portion of which is necessary to survive in the high cost modern economy caused by these policies, can’t possibly be paid by the current economy.

The good news is that not all of that massive spend on R&D over decades has gone to waste, and we now have much more accountable systems that can indeed prevent the super majority of future crises, if only we can muster the courage to adopt them. We are also seeing dramatic improvements in systems that have the capacity for exponential productivity growth over time, which is the only method in our current economic system to cover national debt, unfunded liabilities, and the needs of a quickly aging global population, given the immense future needs in healthcare, environment and economics.

So my plan for 2016 is to tap the exponentially decreased cost and performance improvement in computing hardware and algorithmics to extend our networked artificial intelligence system to the mid-market, NGOs, and governments to provide them with a world class system unavailable to anyone at any cost until very recently. My hope is that our Kyield OS will help even the playing field and lead to a more dynamic and robust economy of the type that is only possible with healthy balance of diversification. Soon thereafter we plan to do the same directly for small business and individuals.

“If your time to you is worth savin’
you better start swimmin’, or you’ll sink like a stone
For the times they are a-changin’”
– Bob Dylan

Why go to the Moon when what your company really needs is in the Rockies? (AI, Watson, Kyield)


Mark Betsy Austin on summit

Mark, Betsy & Austin on top of NM – 10-2015

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This post is in response to an excellent article Tom Davenport wrote for the WSJ (now on LinkedIn) ‘Lessons from the Cognitive Front Lines: Early Adopters of IBM’s Watson’.

Tom is a long-term advocate for increasing jobs related to analytics, particularly in the service sector, and is an advisor to Deloitte, which is a strong alliance partner with IBM, and Deloitte is a sponsor of WSJ CIO. Like most in our industry, we are in constant discussions, but as of now Kyield has no formal alliances or conflicts with any of the people or organizations mentioned in this article.

I too am an advocate for jobs, though not necessarily for IT incumbents, but rather for customers and the broader economy. Smaller companies create most jobs and most job losses come from incumbent consolidation, which is a credible place from which to start this discussion. I think Tom’s article and most of the related strategy is about protecting a few very specific jobs at Armonk, NY, and perhaps at a few alliance partners—not creating them for customers or the broader economy. Modern job creation is no mystery; it’s very well documented.

This article triggered a great many thoughts so I felt compelled to blog about it very early in the morning from my perch in Santa Fe, NM. You see I am the founder of a company called Kyield with an authentic invention based on a theory I developed in our small lab 20 years ago (yield management of knowledge), which looks and sounds increasingly like what Watson has been attempting to become over the last few years. Our company is self-funded almost entirely by me and my wife (well into 7 figures), and frankly I’m feeling just a bit over-exploited at the moment, so hang in there as I poke some fun at the expense of our esteemed colleagues on the east coast and hopefully share something valuable in the process.

Several very important clues and quotes were revealed in this article. I highly recommend reading it carefully as Tom is one of the most experienced and knowledgeable observers in related overlapping domains. First, let’s dissect the lessons the article shares with us including that only one of the organizations interviewed in the article was a customer of Watson, which was University of Texas MD Anderson Cancer Center (MDACC), three were a “partner/co-developer” or “Watson ecosystem partners”, and the undisclosed health insurance company’s relationship type was also not disclosed. Those of us enlightened on the complex relationships in enterprise IT will of course immediately wonder what the terms of these relationships are, who is paying for what, and most importantly why.

Some things we can confirm. IBM has disclosed a billion dollar investment in Watson, often claims to be betting the farm on Watson and/or the cloud, and is obviously spending enormous sums on marketing, partnerships and sales. I too have a lot riding on my company Kyield so IBM’s CEO Ginni and I share that in common—our jobs and future wealth are riding on our respective systems. IBM is constantly reminding us that Watson and healthcare in particular are “moon shots” for IBM, but I’m seriously beginning to wonder if this moon shot is a prudent business decision for IBM and its customers, or a science project that needs another two decades of R&D like we performed with Kyield before attempting to unleash it on customers—particularly business customers (more on basic vs. applied research in a minute).

In order to get our arms around this topic we need to understand a few of the business and technical issues, which for me dates back to the early 1980s to include discussions with IBM and most other industry leaders off and on the entire time. As you may be aware, IBM has been substantially dependent upon the high-end service model since the previous major transformation led by Lou Gerstner in the early 1990s.

What is less known is that IBM grew to over 400,000 employees in that model with more in India than in the U.S. While a brilliant turn-around model in Lou’s time that probably saved the company, 20+ years later the service model has in my view grown far beyond the means to pay for it, and become a big part of the problem in IT for customers and the macro economy. I think IBM understands this well, but it’s a slow and difficult transformation. Ginni herself often states in interviews the challenge is whether IBM “can make the transformation in time”. I suspect with some private confirmation that time may be growing short.

IBM is not alone. All system integrators and many IT consultants share this misalignment of interest challenge often discussed today regarding both internal and external IT investments. The IT services sector represents something like a third of the now almost $4 trillion global IT industry, but drives spending in the majority, which is one reason why the enterprise cloud market is exploding. We then need to understand that IBM’s quarterly revenue has been falling like a rock for several years and so too has the company’s value, during which time competitors like AWS are experiencing record rapid growth, which places a great deal of pressure on the company, partners and loyal customers, not to mention investors and employees. While I am empathetic with IBM’s challenge and especially employees, rest assured that whatever pressure IBM is under it cannot compare to a self-funded entrepreneur.

We have our challenges as well to include the fallout from IBM’s problem in the marketplace, not least of which is a massive ad spend and sales force, with a combined millions of individuals in shareholders, employees and partners all over the world clicking on articles about Watson, which just incentivizes publishers to write more articles with the keyword Watson. Unfortunately, all that attention and spending isn’t necessarily good for customers, the economy, or even IBM—in this regard I may have as much or more relevant experience in my background as our friends at IBM as the challenge to overcome such an advantage in small companies is substantially greater than defense in an incumbent.

The namesake Watson by the way was not a scientist, but a famous salesman who built the early IBM by going door to door selling machines—trust me I respect that, as well as IBM, and many I know and have known at the company. This may provide a clue however regarding the dual branding definition in the name Watson. Prior to becoming CEO of IBM, Ginni was SVP Sales, Marketing, and Strategy at IBM (I too am guilty as I was a CSO of smaller turn-around companies long before changing paths before Lou’s time).

Let’s talk technology

With business strategy, misalignment of interests, and potential business model conflicts out of the way, let’s now take a brief look at the science and technology involved with Watson, which like my company Kyield and our OS is based on AI—in fact my core patent was labeled an AI system by the USPTO. Ginni is stepping back from using the term AI now (“a small part of it”) presumably due to the fear of job displacement out there and other nonsense perpetuated by famous brands with all manner of agendas, which is certainly understandable. I’ve contributed to that learning curve myself over at Wired, but make no mistake Watson is AI even if most of the revenue may come from some other stream like system integration, solutions, and consulting.

While defining AI is not a perfect science, the consensus among scientists is that AI can be divided into two forms, which is extremely important to understand and directly relevant to almost everything discussed here and elsewhere on AI:

  1. General AI (AGI), which is also referred to by some leading AI scientists and authors who cover the field as ‘super intelligence’, or strong AI.
  2. Narrow AI, which is also called weak, narrow or applied AI.

Augmentation or enhancement is by extension applied AI as it is very narrow and highly specific, particularly in our case for each individual entity down to the molecular level when necessary (as in personalized healthcare). Kyield is without question one of the world’s competency leaders at the confluence of human and artificial intelligence, if not the leader.

Now let’s delve into the carefully structured quotes in Tom’s article to glean some additional intelligence.

“It’s an apprenticeship form of training that takes years—there are lots of subtleties that Watson has to learn,” said Dr. Kris at MSKCC.

This is inherent with any deep learning (DL) application including source code shared by researchers with the public and those in our system, but the challenge frankly has always been with system design, algorithmics, and hardware, not marketing. DL is now widely available for anyone who has the talent, providing a long-term benefit across all sectors, and certainly not dependent on Watson, Kyield or any other system. Rather it’s a function within the system. The difference with Kyield is that while DL is tapped for continuous learning over time, other critically important functionality in the basic core provides immediate value to customers, like increased productivity and crisis prevention.

It was not a trivial undertaking to design the Kyield OS in a simple to use fashion. I doubt that it would have been possible if funded by a conflicted organization of any kind, including the super majority of corporations, foundations or government R&D programs. We sacrificed to remain independent throughout the long voyage across the valley of death in large part to avoid such conflicts and be free to focus only on the needs of customers and the specific tasks at hand, not least of which is to prevent crises sourced within large organizations.

“But the problem comes when the needed knowledge isn’t in the corpus. Dr. Kris at MSKCC comments: We had three drugs approved in lung cancer this year. None of them are in the literature yet. And definitions of cancer and its variations are being redefined all the time as we understand the biological characteristics of each one. The science is changing more rapidly than the published literature.”

This is a good example of many specific types of intellectual obstacles we were forced to overcome early in our R&D, and the solution is frankly partially represented in our patented design. The complete solution also includes tradecraft and secrets to include expected future patents, and like IBM we are dependent on intellectual property for survival, so I can’t disclose further except to say that it was a very difficult and expensive problem to overcome; one deemed necessary prior to offering to customers.

“MDACC (UT MD Anderson Cancer Center) actually referred to its project as a moon shot.”….. “An application like OEA cannot deliver on its intended impact of improving patient outcomes worldwide without addressing the necessary network infrastructure, security and regulatory controls, data sharing/access/use contracts, and reimbursement, not to mention the culture of medicine and clinical adoption. Only through addressing these non-technical challenges, we will be able to translate a piece of technology, like OEA, into impact. That is what separates an innovation from a transformation…that is what makes it a moon shot.” — Dr. Lynda Chin, who led the Watson-based project at MDACC.

I see this as the most mission oriented statement in Tom’s article, coming from the only customer disclosed. MDACC has a clear mission in scientific research to eventually eliminate cancer so related ‘moon shots’ fall well within the organization’s responsibility. Most organizations to include most businesses do not share a similar mission as MDACC, which is why we took our R&D much further in applied form and removed as much risk as possible for customers prior to offering, even if admittedly lacking billions USD in development, marketing or sales.

Definition of Moonshot:

A moonshot, in a technology context, is an ambitious, exploratory and ground-breaking project undertaken without any expectation of near-term profitability or benefit and also, perhaps, without a full investigation of potential risks and benefits.”

If you concluded from reading this article that Kyield doesn’t claim to be a moonshot, that would be correct. Kyield does not provide artificial general intelligence, but rather offers a highly evolved system with as much complexity driven out of it as possible, so it is very much an applied system with a laser focus. While Kyield was a moon shot in the mid 1990s when developing the theorem in our lab, it is now a viable product and system at a very attractive price with a reasonably good probability of achieving an outstanding ROI.

Bringing discussion back to earth

Back down here on earth at the southern tip of the Rocky Mountains in the Land of Enchantment is a City Different called Santa Fe, which is over 400 years old. This area is known for history, art, culture, climate and science, the combination of which is why we brought Kyield here from the Bay area seven years ago to mature our R&D. While NM has vast open spaces made famous by Georgia O’Keeffe among others, we also have one of the highest concentrations of intellectual capital in the known universe, including of course the Moon!

I have a suggestion that is entirely compatible with moon shots of the Watson kind, which local theorists understand better than most, and that is to adopt a very pragmatic AI system that follows the rules of laws, physics and economics. We engaged in this process by the book, took massive risk, played strictly by the rules of engagement, invented an authentic system from scratch, and are now offering the world’s most advanced system at the confluence of human and artificial intelligence, which can be adopted at a tiny fraction of the cost as those described in Tom’s article.

In addition, while almost every single one of the Fortune 100 has benefited greatly from the science here in NM, most of which was produced with taxpayer’s money (Kyield is a rare exception in that regard), that value is almost always exported in the form of spinouts, flips and M&A, usually to the coasts and occasionally off-shore. This commercialization (aka tech transfer) model that generates considerable wealth for a very few has not manifested into benefitting NM from the beneficiaries of the R&D in the private sector, otherwise the numbers would be very different.

Seven decades after the Manhattan Project and hundreds of billions of dollars later, NM has yet to experience a significant business success, will soon surpass WV to rank dead last in unemployment, and has among the highest rates of poverty and crime in the U.S. And it isn’t just about education as many with advanced degrees are unemployed or underemployed here. Part-time wait staff at local hospitality establishments or gift shops holding doctorates is not uncommon.

So my suggestion is to come on out and visit Santa Fe just as hundreds of the leading minds in the world do each year, and we can then discuss in greater detail how our applied science in the form of the Kyield OS can help your organization ascend to a higher level of performance, and do the right thing for your career, organization and the economy in the process. In so doing you will empower us to empower NM and perhaps the rest of the global economy to ascend to the next level, which would be a good thing for everyone.

Oh, about that Watson we keep reading about? No worries, it’s likely compatible with the Kyield OS—that’s what all those APIs are for. And who knows, one of these days that moon shot may just pay off. In the interim we can help your organization ascend almost immediately following adoption of the Kyield OS!

Mark Montgomery