Industry-University Programs

While leading IBM Global University Programs for seven years, my team and I developed the 6 R’s of industry-university programs:


These 6 R’s are described with examples in this presentation and this paper:


IBM GUP 5Rs copy 2

Click on the links above to download the presentation and paper.

Done well, the 6 R’s can help boost an all important 7th R = Reputation, or brand of the company when working with universities.

Readings and thoughts


1.Csikszentmihalyi M (1990) Flow: The pyschology of optimal experience. NY: Harper.

2.Hendy S, Callaghan P (2013) Get off the grass: kickstarting New Zealand’s innovation economy. Auckland University Press.
Review 1:
Review 2:
Weta Digital:

3.Anderson JC, Kumar N, Narus JA (2007) Value merchants: Demonstrating and documenting superior value in business markets. Harvard Business Press.

4.Johnson C, Lusch R, Schmidtz D (2016) Ethics, Economy, and Entrepreneurship. SagentsLab.

5.Wright R (209) The evolution of God. Boston: Back Bay Books.



1. Gigerenzer G (2010) Moral satisficing: Rethinking moral behavior as bounded rationality. Topics in cognitive science. 2(3):528-54.
Pat Langley suggested the above.
The author wrote: Herbert Simon once told me that he wanted to sue people who misuse his concept for another form of optimization.

2.Andrej Karpathy, Deep Learning
This article:

This video:

This tool on arXiv is especially cool:

All created by this guy, Andrej Karpathy:

3.Richard Socher, Deep Learning for NLP
This video:

4. Rhizome Web Recorder – personal perspective and collections (via Vint Cerf)

5. Gary Kasparov
Gary Kasparov, first world champion grand master of chess to lose to a machine (IBM Deep Blue)

Two years after the loss, he invented and started writing about Freestyle chess – people playing better chess, even competition matches, with their computer buddy.

He has gotten over it, and reframes the discussion:

We can do new things together that were never before possible… thinking better together.

6. Physics and Biology – understanding when history matters.

Once we regard living things as agents performing a computation — collecting and storing information about an unpredictable environment — capacities and considerations such as replication, adaptation, agency, purpose and meaning can be understood as arising not from evolutionary improvisation, but as inevitable corollaries of physical laws. In other words, there appears to be a kind of physics of things doing stuff, and evolving to do stuff. Meaning and intention — thought to be the defining characteristics of living systems — may then emerge naturally through the laws of thermodynamics and statistical mechanics.

Looked at this way, life can be considered as a computation that aims to optimize the storage and use of meaningful information. And life turns out to be extremely good at it. Landauer’s resolution of the conundrum of Maxwell’s demon set an absolute lower limit on the amount of energy a finite-memory computation requires: namely, the energetic cost of forgetting. The best computers today are far, far more wasteful of energy than that…

So living organisms can be regarded as entities that attune to their environment by using information to harvest energy and evade equilibrium.

England’s definition of “adaptation” is closer to Schrödinger’s, and indeed to Maxwell’s: A well-adapted entity can absorb energy efficiently from an unpredictable, fluctuating environment. It is like the person who keeps her footing on a pitching ship while others fall over because she’s better at adjusting to the fluctuations of the deck. Using the concepts and methods of statistical mechanics in a nonequilibrium setting, England and his colleagues argue that these well-adapted systems are the ones that absorb and dissipate the energy of the environment, generating entropy in the process.

You might say that the system of particles experiences a kind of urge to preserve freedom of future action, and that this urge guides its behavior at any moment. The researchers who developed the model — Alexander Wissner-Gross at Harvard University and Cameron Freer, a mathematician at the Massachusetts Institute of Technology — call this a “causal entropic force.” In computer simulations of configurations of disk-shaped particles moving around in particular settings, this force creates outcomes that are eerily suggestive of intelligence.

In other words, the appearance of life on a planet like the early Earth, imbued with energy sources such as sunlight and volcanic activity that keep things churning out of equilibrium, starts to seem not an extremely unlikely event, as many scientists have assumed, but virtually inevitable.

7. Todd Kelsey
RGB book – Health, Environment, Community –
Stock exchange for non-profits idea
DigitalArcheology – Vint Cerf Rhizome – WebRecorder Link:
Todd Kelsey wrote:
 AI might be capable of somehow communicating these things to a new generation
a great grandchild who never met their ancestor might have an opportunity to learn from them and be mentored by them

Yes, termed “weak immortality” by Doug Lenat’s this AI Magazine issue:
Search for “Weak Immortality” – it will arrive around 2035 with cognitive mediators who know us, in some ways, better than we know ourselves.

You might also enjoy how these systems seems to be evolving:

The ability to rapidly rebuild from scratch seems to be an attractor in energy/knowledge rich systems – for example, seed to tree, planet to life, etc.



1.Henry Chesbrough/Solomon Darwin (Chief Innovation Officer) discussion – April 19, 2017.

My three questions for Henry to ask are:

(1) What will be the concrete outcomes from the Partnership on AI?
(2) When can we expect the unsolved challenges to be completed?
(3) What can individuals to to ensure benefits achieved, and social challenges mitigated?

My three points would be:

– IBM and the industry (Google, Microsoft, Amazon, Apple, etc.) are working on thematic pillars together:

Thematic Pillars

– Building blocks getting better, but unsolved grand challenges remain
– deep learning breakthroughs by Hinton (U Toronto) 2012 for images and speech
– hard unsolved before super-human general intelligence will be achieved
– commonsense reasoning, social interactions
– fluent conversation, ingest textbooks, creative collaboration

– Benefits and challenges for people, business, and society along the way…
– gigantic boost in productivity (what would you do with 100 digital workers working for you?)
– Baylor Biochemical Engineering example
– driverless cars can become guided missiles and/or smart enough not to be used to drive over people
– we already have super-intelligence, called corporations and governments
– they cannot always be held accountable for doing stupid/bad things
– 2008 financial meltdown

2. After meeting Per-Ane Lundberg (Sweden, Science Cluster, Gaming):
Here is the video that gives a good sense of open, sharing, and the future – see the 90 minute video at the bottom of this blog:

Here is the blog of Zanker Recycling with pictures:
Los Esteros Rd, San Jose, CA 95134

For tours contact: Michael Gross <>, Jerame Renteria <>

You also should meet the folks at Cogswell for gaming and movie making:
191 Baypointe Pkwy, San Jose, CA 95134

They have an interesting history:

Solomon Darwin about his upcoming events, and their invitation list –

Henry Chesbrough is also a good colleague – father of open innovation – and he keynoted at this NSF workshop we ran a couple weeks ago:

The key to the future of regions is energy-independence plans, things get easy after that – water is just energy, so is food, shelter, recycling, circular-economy….. all depends on energy…   geo-thermal is probably the way to go in most places, and the artificial leaf is also very good, and nuclear will make a smaller comeback too.

See slide #9 for a summary of 2035-ish:

Also important to understand technology deflation and macroeconomics of printing money and taxes – Sweden does it, so do all major countries:

Technology deflation is real – and the smart phone is a great example of it in action – a black hole absorbing all that is digital – nicely shrinking costs.

3. AI Hardware and things to play with online:

TPU: tools:
Play with Google Trends more:


ISSIP & JST: Future Services and Societal Systems in Society 5.0 and Japan Science and Technology (JST) co-created a workshop and here is the report:

(full text)


Best Regards


Naohumi,Yamada                        Center for R&D Strategy, JST
Tel;03-6261-1858                         FAX;03-5214-7385

NAS Workshop – Integrated Education (STEM, Liberal Arts, etc.)

I have been asked to present an industry perspective on the need for T-shaped skills at a National Academy of Sciences (NAS) workhop on “STEM Integration Into The Liberal Arts.”

Here is my presentation:

Here is a podcast (Dave Goldberg, Big Beacon/Whole New Engineer):

In industry, we see the need for business, engineering, social scientists, communications, and legal/policy people to work together and interact a lot on nearly every project. For example, when IBM communications department posted this about Quantum Computing advances – behind the scenes, all the above and more had to interact.  In the age of accelerations, this becomes more and more true – just think of driverless cars and Uber – if you like controversies.

A range of people study or work to improve this “need for diverse interactions.”

Some call it interactional expertise:

Some call it T-shapes and empathy:

At IBM, we like T-shapes, and the diversity is not just disciplines, but systems,and cultures as well:

Of course, integrated education is hard to design – it is hard for a single person to learn just one discipline or area deeply, but to learn several requires a polymath – and too often they are broad not deep, good for connecting, but less so for solving problems that require deep understanding:

To achieve integrated education will require a vision and a process, a process that works just a little bit, year over year to eventually get closer and closer to the goal of integrated education – I have called this a Moore’s law for education (not sure if you can access Example 1 on education here – and the details have been part of service science.   Simply put, service science is about improving our ability to play win-win or positive sum games through a better understanding of socio-technical system evolution and design.  Socio-technical systems of people and technology interconnected by value propositions are known as service systems.   The need for T-shaped people to advance service science and service innovation was written about in this report from University of Cambridge some years ago – notice figure 1 on the gaps beween academic disciplines especially:


Additional Readings

Miller RK. Why the Hard Science of Engineering is No Longer Enough to Meet the 21 st Century Challenges. Olin College of Engineering. 2015 May.
Kline SJ. Conceptual foundations for multidisciplinary thinking. Stanford University Press; 1995.

Friedman TL (2016) Thank-you for being late: An optimist’s guide to thriving in the age of accelerations.  NY: Farrae, Stauss, Grioux.


Also watch and listen to these two items:

Jim Corgel on the Right Attitude and Skill Set

SYSK Empathy:


For Ashley Bear.

National Academies Study Committee on the Integration of Education in STEM, Humanities, and Arts at the Undergraduate and Graduate Levels

(Arizona State University; Life Sciences Building Room C202; C Wing 401 E. Tyler Mall; Tempe, Arizona; Thursday, April 6th, 2017)

Sharing Information in the Digital Age

The key question:
Who may
share what information with whom for what purpose in what context and be on firm legal ground?

(1) Who may – in the digital age we can all capture and share information more easily.

(2) what information- even information that is captured digitally can be altered, or opinions can be associated with it.

(3) with whom – sometimes it is OK to share information with some people, but not others.

(4) purpose – the intention of the sharing may be important, in many cases

(5) context – this may override other factors, such as in a disaster situation – when normal rules do not apply.

(6) on firm legal ground – this is what title companies do for real property.

What is Title Insurance? – Stewart Title
Quote: Title insurance protects real estate owners and lenders against any property loss or damage they might experience because of liens, encumbrances or defects in the title to the property. Each title insurance policy is subject to specific terms, conditions and exclusions.


Who offers title insurance on real property and how did that come to be?


Who offers title insurance on information?  UNKNOWN


Information Provenance:

IBM Knowledge Center: Provenance information


The world is a messy place with other people’s data and property all over the place – Google ran into this with Glass –

Scroll down to Privacy Concerns:

Quote: Additionally, there is controversy that Google Glass would cause security problems and violate privacy rights.[86][87][88] Organizations like the FTC Fair Information Practice work to uphold privacy rights through Fair Information Practice Principles (FIPPS), which are guidelines representing concepts that concern fair information practice in an electronic marketplace.[89]

Also see:

Quote: 4. Integrity/Security[14] Information collectors should ensure that the data they collect is accurate and secure. They can improve the integrity of data by cross-referencing it with only reputable databases and by providing access for the consumer to verify it. Information collectors can keep their data secure by protecting against both internal and external security threats. They can limit access within their company to only necessary employees to protect against internal threats, and they can use encryption and other computer-based security systems to stop outside threats.[14]

For commercial and legal purposes, every time we share digital information via email, social media, etc., we may want to have a record of the sharing event which is automatically added to a blockchain. Is this practical? desireable? viable?  Questions: Should we, can we, may we, will we?

What if the person we share the information with – does not read it, process it, understand it? What if they don’t want to receive it?

Some additional readings:

Benefits that search engines get – users must actively opt out:

Type of information matters:
Malin B, Karp D, Scheuermann RH (2010) Technical and policy approaches to balancing patient privacy and data sharing in clinical and translational research. Journal of Investigative Medicine. 58(1):11-8.
HAT – Hub of All Things – “Own Your Data” –
Context matters:
Harvard Humanitarian Initiative (2010) Disaster Relief 2.0: The future of information sharing in humanitarian emergencies. In Disaster Relief 2.0: The future of information sharing in humanitarian emergencies  (pp. 72-72).
Implications for development:

What is a “busy fee earner”? Read this here.

The Future of Business Education

The Future of Business Education Isn’t What You Think It Is: How Cognitive Systems and Industry 4.0 Will Revolutionize Management.

In the age of accelerations, the best way to predict the future is to inspire the next generation of students and early career talent to build a better world (Friedman 2017).  Building a better world requires grit and better building blocks, and perhaps even heroism at times ( Duckworth 2016; Hatch 2013; Lowney 2010; Hannibal, 2017).   Artificial Intelligence/Intelligence augmentation, virtual reality/augmented reality, blockchain/open technologies, and material/energy systems provide these new building blocks (Domingos 2015; Antunes 2012).  In the corner of my garage, there is a stack of boxes my wife is after me to throw out.  Old stereos, sound systems, albums, cameras, video recorders, computers, and more that I paid many thousands of dollars for as a struggling student then early career professional over the years.  Today my smartphone provides all these functions, and more – such as speech translation from other languages – at a fraction of the earlier cost (Gada 2017; Gershuny 2003).   By 2035, no one can yet predict the form factor of your mobile device, but projections indicate that it will have an exascale of computing power – the computing power estimate of one person’s brain (Friedman 2017; Norman 1993). Let’s explore together the implications of cognitive systems and Industry 4.0 on the future of business education. (Hint: Faculty and students will need to become more T-shaped!).


Antunes S (2012) DIY Satellite Platforms: Building a Space-Ready General Base Picosatellite for Any Mission. O’Reilly Media.

Domingos P (2015) The master algorithm: How the quest for the ultimate learning machine will remake our world. Basic Books.

Duckworth A (2016) GRIT: The power of passion and perseverance. NY,NY: Simon & Schuster, Scribner.

Gada, K (2017 forth coming) ATOM: Technology deflation.  ISSIP Business Expert Press.

Gershuny J (2003) Changing times: Work and leisure in postindustrial society. Oxford University Press.

Hannibal, ME (2017) Citizen Scientist: Searching for Heroes and Hope in an Age of Extinction Kindle Edition. The Experiment Press.

Hatch M (2013) The maker movement manifesto: rules for innovation in the new world of crafters, hackers, and tinkerers. McGraw Hill Professional.

Friedman TL (2017) Thank you for being late: An optimist’s guide to thriving in the age of accelerations. Farrar, Straus and Giroux.

Lowney C (2010) Heroic leadership: Best practices from a 450-year-old company that changed the world. Loyola Press.

Norman DA (1993) Things that make us smart: Defending human attributes in the age of the machine. Basic Books.

For even more readings:

Top 10:

Holiday 2016:

Jobs of the Future:

For relevant presentation see: 

IBM Welcome and Cognitive Futures

Per request of Timothy Keiningham

Zanker Recycling Center

Great tour guide for Zanker Recycling Center: Jerame Renteria (with support from Michael Gross)

Lorenzo Napoleone and Federico Columbro (U Rome Tor Vergata) are working on waste management as a smart service system so we were lucky to get a tour of Zanker Recycling today.

Suited up and ready to get in the van.


Hot compressed air separator


inside the belly of the beast – the digestor – creating methane (and smells) to power Zanker Recycling


75 tons per hour of construction and demolition waste – separated


seagulls on treadmill in background

For those who would like to know more trash talk – I recommend “Stuff You Should Know” podcasts episodes below:

SYSK: How landfills work

SYSK: How plasma waste converters work

SYSK: Recycling and the Great Pacific Garbage Patch

SYSK: E-Waste Video

and my presentation on Manufacturing as a Local Recycling Service

also see Circular Economy video

largest anaerobic digestion facility in the world at Zanker Recycling

From IBM Almaden: Jim Spohrer, Federico Columbro, Lorenzo Napoleone, Spike Narayan, Obinna Anya, Barry Eberly.

From SJSU:  Jacob Tsao,  Femi Aluko

Cognitive OpenTech

Whether we know it or not, and most of us don’t, we will all soon be building our own personal cognitive systems.   Nearly everyone is on a journey as a developer/maker/citizen scientist/data wrangler/lifelong learner/T-shaped service scientist…  people with depth for problem solving and breadth for empathy and communication skills, evolving to work better on multidisciplinary, multisystem, multiculture teams to take on larger and larger challenges.

We will build them, and they will know us well, and keep our data private.  We will be able to build them, because the building blocks are getting better fast.   For example, just sixty years ago it required the combined resources of a nation to put a satellite into orbit. And now it is rapidly becoming something that a single teenager can aspire to do – from DIY satellite to DIY rocketry.  Making the world safe and secure, and escaping fear of harm from others is one of the biggest challenges we face.  Making tools to solve our most pressing problems is getting easier and easier as the building blocks get better – rebuilding society from scratch is becoming easier, not harder, to imagine.

Cognitive Open Technology building blocks (Cognitive OpenTech) are getting better, and they include a wide range of capabilities as a service: Augmented Intelligence, Artificial Intelligence, Machine Learning, Deep Learning, Exoskeleton Clothing, Maker/Rapid Rebuild Tools, etc.

However, there are still many unsolved grand challenges remaining:

These challenges are best approached as an open ecosystem of collaborators, working on technology as a service – see

Regarding Open Technology – if you have 90 minutes, you really should watch this:


Intro animation

Sam Ramji (Google, VP Product Development – Developer and Compute Platform)

Sarah Novotny (Google, Program Manager – Kubernetes Community Development, Google Cloud)

Vint Cerf (Google, VP and Chief Internet Evangelist)

Jim Zemlin (The Linux Foundation, Executive Director)

Eric Brewer (Google, VP Infrastructure)
(26:00 – Thousands of Googlers contributed to 1000’s of open source projects in 2016)

Chris Wright (RedHat, VP and Chief Technologist)

Jeff Dean (Google, Senior Fellow)
(4000 projects use TensorFlow insider Google today)
(I think this means: Google promotes “open” as key to employees, customers, developers, researchers, universities, and citizen science. The distinction between employees and customers may decrease over time as everyone becomes a developer/lifelong learner)

Rajat Monga  (Google, Principle Engineer)
Examples including skin cancer detection and eye disease:

Sam Ramji (Google, VP Product Development – Developer and Compute Platform)
“Best time in history to be a developer – craft is respected”
“Age of open source – fast innovation.”
“Days of committing to a closed ecosystem are over”

Alison Wagonfeld (Google, VP Marketing – Google Cloud)

Will Marshall (Planet, CEO)
Satellites to map the surface of Earth.

Willem Sundblad (Oden Technologies, CEO)
Empowering manufacturers with data

Herman Narula (Improbable, CEO)
SpatialOS – Simulation of cities for policy making, game development platform

Alison Wagonfeld (Google, VP Marketing – Google Cloud)
Anthony Goldbloom (Kaggle, Co-Founder and CEO)
Scaling up to deep learning from simpler machine learning

Alison Wagonfeld (Google, VP Marketing – Google Cloud)
Santi Subotovsky (Emergence Capital, Managing Partner)
Matt Ocko (Data Collective, Managing Partner)
Last ten minutes is VC funding for microservices on cognitive open tech…

Fei-Fei Li (former Stanford, Chief Scientist, Google Cloud for AI)

11:00 “…democratizing compute, algorithms, data, models, talent and expertise.”
12:00 “…model for AI… best papers for AI competition – quickly turned into products and services.”
13:00 “vision API and meta-data from Google search to recognize entities in Google Knowledge Graph”
14:43 “video-intelligence API – Sara Robinson, scene changes in video”
Sheep dogs and mops –

These are also important:

OpenWhisk for serveless microservices

BonnyCI for rapid rebuilding

Jupyter Notebook and used by DSx (Data Science Experience)

Sonnet is open now too.

CIO’s are using AI and Open Technologies to continuously improve their organizations:


Go Nat Friedman – $5K grants for Open AI projects:

Open source AI/ML/DL for smarter/wiser service systems is a passion, including circular economy and rapidly rebuilding from scratch for sustainability and resilience of systems – helping all nations become energy independent is a key first step, and geothermal needs to be 100x cheaper than today, but that is a good challenge to work on….

Some online talks

Some recorded talks:

2016 Almaden – Cognitive Systems:

2015 Almaden – Better Building Blocks:

2015 Italy – Future:

2015 TokyoTech – Smart Service Systems:

2014 Talent from Real World Challenges:

2013 Service Science –

2013 ISSIP – New Member:

2013 Panel – Emerging Technology:

2011 CITRIS – Skills:

2011 MPICT – Skills:

2009 California Hillside –


More here:


and here:

In memory- 20 second mark – Bob Lusch:

Disruption: A service science blog bookmark

(1) On Irene Ng’s “The Markets to Redesign” – personal data, share manufactured things, and drugs/pharma all need disruption for sure, and in next decade human microbiome may disrupt pharma finally and permanently…


Innovation Caucus tool – to help disrupt interconnected path dependent business models in industries:
For more see, 55 Jobs of the future:

The Dismantlers: Prison System Dismantlers, Hospital and Healthcare Dismantlers, Income Tax System Dismantlers, Government Agency Dismantlers


(2)  On Gautam Mahajan’s disruption value tree and disruption of industries, I have also enjoyed these four items a great deal:

(a) Routine labor industry: What will everyone do with 100 digital workers each by 2055?

(b) Efficiency of different types of capital for disruption and better explanations:
Hunter Hastings (with Jeff Saperstein) ISSIP BEP book author – writes, presents, and speaks about…
Entrepreneurial super intelligence:
Ray Dalio (BridgeWater):
George Gilder (Scandal of Money):
Hunter wrote: “A major thought of his [Gilder] is that trading financial assets does not add new knowledge to the economy, and it is new knowledge that makes the economy grow, and creates jobs. Entrepreneurs are engaged in conducting what he calls falsifiable experiments that become learning and knowledge. Therefore, venture capital is the most valuable money in the economy. He quotes Peter Thiel’s numbers: venture capital is less than 0.2% of total capital, but has seeded companies that now produce 21% of GDP, 65% of market capitalization and 17% of all jobs (that last number is probably under-estimated, notes Gilder).”
David Deutsch (Beginning of Infinity):
Robert Wright (Evolution of God):

(c) Government funding needed – taxes can go away by 2035: technology deflation: salvation or death trap…

(d) Government enforces responsible behavior – innovate responsibility – complex system have capabilities and constraints; service systems have rights and responsibilities, too:


Built on top of:

(1) Irene Ng’s Value and Worth (price – money – what people are willing to pay for something) is a helpful framework for your work in my mind.

(2) The tree-diagrams that lead to industries is also a nice direction to pursue to highlight some aspects of the systems dynamics.   I like the the work of John Sterman for modeling some of these disruptinve dynamics…

(3) The industry level analysis might also benefit from looking at Basole and Rouse:

(4) Paul Maglio and I are approaching the problem from the perspective of a simulation of the evolving ecology of service system entities – we have been brainstorming for years about how units-analysis (miles/gallon, bits/joule) etc. and other units based key performance indicators of smarter service systems evolve over time.   There is still a lot of work to do on this, but my inspiration for keeping at the task is the inspiration I draw from Kline’s book below – which discuss human-techno-extension factors and socio-technical-system design loops accelerating as more units get integrated into systems…

Kline SJ (1995) Conceptual foundations for multidisciplinary thinking. Stanford University Press.  OK, summary here – but the book is much better:

The following book is the best treatment of B2B KPIs (Key Performance Indicators) I have read across industries, and also highlights the importance of units analysis in B2B KPIs… businesses that can intelligently evolve their KPIs over time, do better as disruptive innovators, than those who use overly simplistics KPIs that do not evolve, in general.