INVENTING INNOVATIVE ENTERPRISES - STARTUPs, OPEN INNOVATION, INCUBATION, INVENTIONS

 

On 18th July 2022, I was invited to conduct a half-day workshop at VVIET MYSURU, Entrepreneurship Development Cell. It was attended by about 100 students and faculty members.

 

The key points are 

1. Invent a solution  or a venture using sixth wave of innovation technologies or changes http://www.crafitti.com/sixth-woi.html

2. Create a Lean Canvas

3. Customer value framework is essential 

4. Invent using TRIZ 

5. minimum viable product needs a plan for verification  and validation of all assumptions hypothesis

6. use the Goal Canvas for continuous evolution of MVP

7. Use Crafitti idea Journal weekly capturing problem  and ideation

8. Create a White Paper for your product or venture 

9. Continuously keep on inventing 

10. Prepare an invention disclosure even if your venture is not inventive 

 

 

TRIZCON 2020 - My Abstract - Inventing Complex Intelligent Strategic Systems (CISS)

 

Inventing Complex, Intelligent, Strategic Systems (CISS) - ALVIS-SCAN thinking for the Sixth Wave of Innovation

Navneet Bhushan

We define a new class of systems and products named Complex Intelligent Strategic Systems (CISS). We propose that these systems are emerging in the Sixth Wave of Innovation (years 2015-2045). We evolve the formal definition of a system described in TRIZ and in Hubka’s Theory of Technical Systems, to include technical systems with a “mind” of their own. This also maps to the 10^th Law of TRIZ proposed in 2012 – the Law of Increasing Intelligence of Technical Systems. The challenges of discovering, defining, describing, designing, developing, deploying, and deducing (7Ds) the CISS require a complete relook of their lifecycle. Besides the advent of cyber-physical systems, increasing intelligence of technical systems, the massive scale of these systems coupled with strategic nature of many of these systems leads to unprecedented challenges. 

These systems are characterized by substantial decentralization, higher embedded/ambient algorithmic intelligence, inherently conflicting, unknowable and diverse needs/requirements, continuous evolution/deployment/learning, heterogeneous, inconsistent, and changing elements, erosion of people/system boundary, regular failures and new paradigms regeneration of parts of the system. Key aspects for 7Ds of CISS lifecycle i.e., Value, Inventiveness, Human Interaction, Computational Emergence, multi-level Design, Computational Engineering, Adaptive System Infrastructure, Adaptable and Predictable System Quality, Policy, Acquisition and Management are explained. Nine thinking dimensions proposed for CISS are Analytical, Logical, Value, Inventive, and Systems thinking (ALVIS) and Scale, Computational, Algorithmic and Network (SCAN) thinking. These thinking dimensions need to play a much larger part in an integrated manner than the current mostly analytical, logical and analogical thinking. We describe few case studies in ALVIS-SCAN thinking and describe ALVIS-SCAN thinking framework for 7Ds of CISS.

 

 

The TRIZCON 2020 was held online - a Virtual conference. The abstracts of all talks are published at AITRIZ site

 

https://www.aitriz.org/trizcon2020/abstracts-papers

 

Some Slides from my presentation 

System Classification Framework

Complex Intelligent Strategic Systems

 Law of Increasing Intelligence of Technical Systems

Function Model for CISS (Sixth wave of Innovation )

 

Evolving TRIZ for the Sixth Wave of Innovation (Key Slides)

Typology of Problems - Problem Formulation Framework

Problem Solving requires problem understanding and problem exploration. We have seen there is general tendency to get into solving - getting to solutions quickly before even understanding the problem.

We describe 4 Types of Problems that we encountered usually in our workshops. Theory of Inventive Problem Solving (TRIZ) describe these as contradictions - some sort of conflicts between various system parameters.

Type A: Wish/Aspiration ~ Administrative Contradiction ~ May be High level Objective setting (Almost ~ Do "Something")

Type B: Unexpected Results/Consequences of an action

Type C: Beyond Optimisation (Technical Contradiction)

Type D: Paradox (physical contradiction)

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We describe below the basic anatomy of these 4 type of problems and what questions can help you refine these problem statements towards a solution thinking.

This is part of our SOUL-ALVIS-CRAFT framework

Type A: Wish/Aspiration ~ Administrative Contradiction ~ May be High level Objective setting (Almost ~ Do "Something")

Anatomy of Type A problems : (1) We should do X (increase productivity, profit, reliability, etc, decrease attrition, waste, etc)) (2) I want to do X, but have no opportunity or not allowed to do X. (3) We should do X, but do not know how/vague idea of how to do

Question on the problem statement : Why should you do X? What is stopping you to do X?
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Type B: Unexpected Results/Consequences of an action

 Anatomy of Type B problems : (1) We did Y expecting X, but it resulted in Z? (2) We did Y to do X, we achieved X partially but we also had Z which is harmful/not expected/not thought through?

 Question on the problem statement : Why were you expecting X (X only)? What was missed out when you conceived Y to achieve X? Why Z was not expected? Could something done while doing Y caused Z? Can Y be modified to eliminate that something?

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 Type C: Beyond Optimisation


Anatomy of Type C problems : (1) We improve X by doing Y but it worsen/reduce Z which is not desired. (2) We improve X by doing Y but we can not do more Y to improve X as it reduces/worsens Z, so we do Y only to an extent to optimise X and Z.

 Question on the problem statement : Could something done while doing Y caused Z to worsen? What is that? Can Y be modified to eliminate that something? Can we find Y-Dash which does X AND doesn’t worsen Z?

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Type D: Paradox (physical contradiction)

Anatomy of Type D problems : (1) We want X to have P AND we want X to have "Not P". (2) We want X to function as Y AND we want X to function as NOT Y

Question on the problem statement : When do you want P and when not P? Where do you want P and where not P? Under what conditions you want P and under what conditions you want not P?


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TRIZ Trends 2016 - at GE John F. Welch Center at Bangalore - Some key slides

Inventing in the expanding frontier of ignorance - TRIZ for Information-era Artificial Intelligence and Systems with a MIND

Presentation today at TRIZ Trends 2016 at GE John F Welch Center of Technology at Bangalore

- Some key slides

Event: TRIZ Trends 2016 - at GE John F. Welch Technology Center, Bangalore, INDIA, Tuesday – April 12, 2016.

The Agenda is now Available for the day

Event: TRIZ Trends 2016 - at GE John F. Welch Technology Center, Bangalore, INDIA, Tuesday – April 12, 2016.

Dear All,

Please find attached an announcement on a one day summit called TRIZ-Trends 2016 at GE John F. Welch Technology Center, Bangalore, INDIA, Tuesday – April 12, 2016.

The first such summit was held in 2014 and this one provides a platform to learn, share, and network.

It is indeed a great initiative by GE.

Crafitti is happy to participate in this summit.

If you can make it kindly register quickly. Registration is FREE however seats are limited and time is by 31st March.

Kindly register early if you are in Bangalore on that day.   KINDLY FORWARD THIS TO YOUR CONTACTS WHO MAY BE INTERESTED.

"Participation & Registration : Participation is open to Engineers, Scientists, Academicians, Researchers and others interested in practicing and applying TRIZ for Innovation in their respective disciplines on a first-come-first-serve basis limited to a maximum of 50 participants. Preference will be given to those who have a background in TRIZ through formal or informal learning / training / certification.
REGISTRATION IS FREE BUT MANDATORY.

To Register please send an email to mt.shyamsunder@ge.com with subject as “TRIZ-TRENDS 2016 Registration” and provide details of Name, Designation, Organization, City, Email ID, Phone and TRIZ relevant certification and experience.
LAST DATE TO REGISTER : March 31, 2016

LOOK FORWARD TO MEETING YOU AT GE Bangalore on 12th April 2016.

Inventing in an Expanding Frontier of Ignorance - Extended Abstract

Inventing in an Expanding Frontier of Ignorance –

TRIZ for Information-era Artificial Intelligence and Systems with a Mind

Extended Abstract

Chances are remote that when Feynman was delivering his famous lectures on physics in 1962 and wrote “we do not yet know all the basic laws: there is an expanding frontier of ignorance” in USA, he would have heard of Altshuller, the Soviet prisoner released after Stalin’s death from Siberian confinement, who was discovering the laws of evolution of technical systems through painstaking analysis of thousands of patents which was to result in the Theory of inventive problem solving (TRIZ in Russian parlance). It is indeed the peculiar fate of our world that multiple directions are taken for exploration and development in decoupled social, political and cultural systems – as USA and USSR were after World War II – yet the key to “knowing” or creating “new knowledge” continues to be an evolutionary approach – rather than design, direction and planning. 

Feynman describes that although the sole judge of scientific truth is experiment giving us hints to the laws underlying our world, yet imagination is needed to “create from these hints the great generalizations – to guess and then to experiment to check again whether we have made the right guess.” He further states that laws of nature are approximate and, “… at each stage it is worth learning what is not known, how accurate it is, how it fits into everything else and how it may be changed when we learn more” [1]. This is indeed the process of continuous learning and understanding through an evolutionary process.  However, despite its discovery by Darwin, 150 years back, acceptance of evolution by natural selection as a possible model of explanation of progress of cosmos is relatively a recent phenomenon [2]. As Ridley states in [3], “the way the human history is taught can therefore mislead, because it places far too much emphasis on design, direction and planning, and far too little on evolution”. He further states that, “… to see past the illusion of design, to see the emergent, unplanned, inexorable and beautiful process of change that lies underneath”.

One of the earlier recognition of evolution due to ingenuity of human mind reflected in the successful inventions described in patents and technological knowledge was discovered and explained by the Theory of Inventive Problem Solving (TRIZ). This resulted in discovery of laws of evolution of technical systems which became the basis of classical TRIZ. As per Altshuller the purpose of evolution of technical systems was to achieve the “Ideal system”. Technical systems exist or are created to perform a function. The ideal technical system describes the fulfillment of the function with reduction in number of the elements of technical system that actuates the function. TRIZ and its laws of evolution of technical systems discovered in the era of physical systems – the era of machines – explained the fulfillment of function in an ideal way. The algorithm of achieving ideality was to avoid the costly “trial and error” approaches of evolution – small local changes in multiple copies of the same system which get reflected in the “subsequent generations of system”. TRIZ proposed to jump the costly “trial and error” and focused on ideality and jump many avoidable generations of unnecessary random stages.

Three Eras – Machine, Information, and Mind

From the era of machines – dominated by automobile – which incidentally became the model for classical TRIZ – we are rapidly moving in the era of information. Our understanding of “information” – its nature and its deeper manifestations – is increasing day by day. When we started investigating the applicability of laws of system evolution as described by TRIZ in the current era of information, we realized that TRIZ, understandably missed the key ingredient, i.e., information, embedded in modern technical systems and environment in which these technical systems will be operating.

We discovered that human beings by collectively evolving their technical systems, are trying to make each technical system as close to a human being as possible – or at least a model of human being and its environment based on the current understanding of the world (for example, understanding of laws of physics and chemistry in making an automobile) and the current understanding of the system called the human being. As man understands the world around it as well as its body and its mind, it wants to create an “ideal man” or at least an idealized human of all technical systems it is creating. This is an unexpected discovery and may take the readers used to classical TRIZ, sometime to accept it [4].

Increasing Intelligence of Technical Systems

Given our understanding of the current information era and how technical systems are evolving from their predominantly physical characteristics into information enriched technical systems, we propose in this paper a new law – the law of increasing intelligence of technical systems.

We are in the era of information today. This is an era that has replaced the era of machines that started with industrial revolution. This era of information is giving us systems that are becoming increasingly intelligent. From the dumb systems that were responding to inputs to perform specific functions, we have evolved to guided systems and smart systems of the information era. The next stage of evolution of technical systems is increasingly becoming clear as we are seeing emergence of brilliant systems which we predict will become genius systems. By 2050 AD, the world will have technical systems with more intelligence than biological intelligence – predicted as the Singularity. From information era we are now entering rapidly into the era of mind. This we call as law of increasing intelligence of technical systems.

In the current Information Era, TRIZ needs to update its definition of a technical system to include “information”. The goal of system evolution should be to create ideal systems that attain perfect information to actualize the underlying system functions.

In the emerging era of Mind, TRIZ should be about ideas and thoughts. How can any technical system process and actuate ideas? The ideal technical system will be able to generate and actuate perfect ideas to attain system functions needed in real time or even ahead of time.

Lines of System Intelligence

In the era of information and coming era of mind of technical systems we have proposed a new law of evolution of technical systems using TRIZ way of exploration and creating new knowledge. We call this the Law of Increasing Intelligence of Technical systems. We further propose that TRIZ should incorporate this new law to the existing laws of evolution of technical systems as the current information era and future mind era of technical systems will require new ways and concepts to invent systems that will have more information and in future will have the fourth fundamental we call the mind as their most prominent components.

In the talk we will explain the Lines of system intelligence under the law of increasing intelligence of technical systems that we have uncovered in our exploration so far. These are lines for –

(a) Increasing levels of sensing and detecting,

(b) Increasing levels of processing data, information and knowledge,

(c) Increasing levels of Learning,

(d) Increasing levels of choice –making,

(e) Increasing levels of concept-creation,

(f) Increasing levels of uncertainty, randomness and vagueness

Final Point:

The Artificial Intelligence(AI) and Artificial Super Intelligence (ASI) debate going on in the world today misses out on one key point on “intelligence” – the intelligence need not be “conscious” or “aware”. Non-consciousness intelligence is what we are calling artificial intelligence and that perhaps will continue in the near future and may exceed biological intelligence as per “singularity” by 2045-2055. However, the “artificial consciousness” really has no clarity – unless we claim the cloning of human beings to be the creation of artificial consciousness.

References

[1] The Feynman Lectures on Physics

[2] Steven J. Dick and Mark L. Lupisella (Ed.), Cosmos & Culture – Cultural Evolution in a Cosmic Context, NASA report number, NASA SP-2009-4802, 2009.

[3] Ridley M., The Evolution of Everything – How New Ideas Emerge, Harper Collins, London, 2015.

[4] Bhushan, N., Law of increasing Intelligence of Technical Systems, accessed on 18^th March 2016 http://aitriz.org/triz-articles/inside-triz/596-law-of-increasing-intelligence-of-technical-systems