iGNITIATE

Tuesday, 22 August 2023

Design Meant Discipline – MIT’s Radical Redefinition

Draftperson’s 1st efforts once meant months & then CAD=weeks. Draft to “Doable” has decimated the design world. Sketching & pullable surfaces to grasshopper meant weeks & then Vizcom=seconds. Now what?

It’s no surprise that the radical redefinition of the word “commerce” in the early 21st century was directly influenced by the founding of Amazon ( 1995 ) and only 10yrs years after the massive growth via the general public jumping into the dial-up world when America Online ( 1985 ) was founded bringing 100’s of millions into an electronically connected world. But like the horse & buggy after the advent of wide spread car manufacturing / assembly line model, the landscape of what is now “design” demands it own definitional reassessment. As detailed in the “Why The Definition Of Design Might Need A Change” we see the simple ways that breakthroughs like T-splines and later Ai visual creation services changed the entire world of what it now means to be a “designer” where rapid fire A-B testing is where “design” is headed.

The radical departure from the laborious task of incredibly detailed specifications ” design ” to be able to visualize and then move through to engineering and manufacturing has taken a light speed jump from it’s origins all the way back to the 1300’s. Even before, design was incredibly detailed ( within the minds of the artisans / masters – who were also, and where they were expected to be construction capable ) and with that came the contractual obligations necessary for delivery. Design ( and detailed design in fact ) defined contracting and where the responsibilities of those that built and manufactured ( within the guild world ) existed. It was this design to detail to delivery where design cut it’s teeth in it’s definitional dimension eg. the mastery and systems of Wedgewood and the products he made – the small atelier to final production model.

Enter mass manufacturing: the incredible complexity of sketching to computer aided design ( CAD ) to computer aided manufacturing ( CAM ) to computer integrated manufacturing ( CIM ) and the incredible levels of knowledge that no one person could possibly have a complete knowledge of. Design then ( possibly ) becomes the need to see the 1st steps without missing the desire to be conversant in all the other later steps. However not slipping, and that the initial phases cannot exist without considerable levels of investigation mean quick and dirty never turned out well.

Today however, this notion is almost erased. Thoughts ( words ) become things ( images ) in a matter of seconds with Ai and sketch to real world imagery capabilities. More, the faster the development of these Ai interfaces become the quicker the design process changes: mini-productions become possible. Skinning ( via 3D printing ) now relatively expensive for small batch production gets cheaper and cheaper by the moment. Where printing one shell for one design required hours, weeks, months of work, with Ai systems that hold assembly pin locations in place while outer shell structures are changed at will means a higher level artisan production becomes the norm. Small scale Ai designed to Ai produced is happening faster than ever before and the long and painful economies of scale to make such small batches possible is now not so small and thus coming to fruition. Inserted into shop on demand systems and auto Amazon delivery and future forward ideas / designs will be in the hands of users faster that we ever expected. The ” on demand ” designer is right around the corner.

This then means that the definition of design returns in one way to the artisan / master designer. The economics of design then become the definition of design once again with the expectation that now, designers and design have an even broader more complicated path: constant evolution and production. Did Ai just make ” designing ” easier? Surely it did. Did Ai just make the entire production process that much more expensive ? Surely it did. Those precious few seconds that designers can now create anything just made design a lot more expensive. Thanks Ai. Now the real fun begins.

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Saturday, 29 July 2023

Igniting Innovation = -5,3,1 to +1,3,5 Timing

Innovation, more misused than almost any other word means misunderstandings multiply without the reality check of " timing " being present. But how can we cultivate it, timing, a mechanism even more misconstrued than possibly the word innovation itself ? But it doesn't need to be. Here's how.

With the ever present idea by Mark McCormack that "you can't teach timing" means the reality is that with a keen understanding of raw scientific research X taking sometimes 10 or more initial years, and ultimately 20 when it comes to truly experimental underlying physical sciences research, then leads to to an almost 10yr in lab invention window Y before the primary movement to a usable Z based v0.5 of said original ground breaking X research takes place. Thus is the capability to teach innovation ( timing ) possible yes.

In the classic example of Douglas Englebart's 1st lectures of a mouse ( based on years of previous efforts ) on what computers could be ( and would be ) and including his ground breaking work with augmented and virtual reality capabilities ( 1961 ) from work completed in US Military labs many more years earlier ( 1954 ) ; culminating with Englebart's " Mother of All Demos " ( 1968 ) then changed the face of computing. This led directly to the the creation of the the Xerox Alto at the famous Xerox PARC Labs ( 1972 ) resulting in the team pilfered from PARC to Apple who created of the 1st Macintosh Prototype ( 1981 ) and then onto launch of the the 1st Macintosh computer ( 1984 ) = a roughly 30yr ( 1054 - 1984 ) 3 phase path. And, where " industrial " use was in a -5,3,1 ( in commercial labs ) to real world +1,3,5 to launch system.

With the infrastructure in place via a government, military, commercial or artistic R&D model, the realty of The “ARPA Model” and as detailed in Funding Breakthrough Research: Promises and Challenges the pattern not only becomes clear, but the timing even more carefully articulated and the marathon model uncovered that allows this to happen. Through consistent and carefully orchestrated internal competition and leadership rotations a relay system emerges which allows for breakthrough efforts to run the hurdles necessary for what could previously never have been done before to gestate and birth, within the explicit context of experimentation to usability, legitimate innovations. Surprisingly then timing, no matter how complex the jazz timing or how syncopated the movement of the players becomes, there is a way to achieve more than expected from the outset and exactly how cutting edge firms are able to leverage this today.

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Wednesday, 28 June 2023

R&D Realizations Mean Constant Convergence

With the consistent swarm of related and sometimes unrelated efforts necessary to push the boundaries of R&D into viable and usable tools, it's not only firm size, previous R&D experience, belonging to related high-tech services sectors and obtaining public funding which all influence positively and significantly the propensity to cooperate with agents of change to engage and support the capability of making breakthroughs take place.

What this is often at odds with ( and due to the complexity of garnishing funding from country specific national science foundations, government and military funding sources ) is what R&D portfolios of cooperating firms look like as compared to those that do not cooperate. In " Generation Activities And Innovation Results Of Firms " we see, interestingly it's firms that collaborated with customers and possible end users not yet prepared for massive technological changes which show significantly lower investment in basic research compared vs. firms where investments in applied research and basic research that end up seeing significantly greater success rates due to R&D convergence efforts. Where some firms are also able to effectively use this strategy to pursue objective short-term solutions to market needs, this has been shown to also be to the detriment of expanding their technological knowledge base to other fields ( via basic research ) and without this further expansion synergistic effects of said convergence capability and activities were smaller in firms that did not adopt this mechanism.

With basic research investment reductions and in the case of customer cooperating firms the pattern further reveals the preference of these companies to develop near-market research activities and thus an imbalance for farther reaching efforts in unproven targets but where said successes can be drastically effected by efforts such as consistent merger and acquisition activities. As in the case of apple and their new iVisionPro system such efforts to develop new product lines required an M&A activity of bringing in new companies on average of buying one company every two to three weeks and where many of these firms are effectively purchased out of existence due to the need for person talent and thus intellectual property capture and dominance. It is therefore that such a system and effectively " innovation plus " intellectual property via an R&D mentality that becomes the driving factor for specialized design and engineering solutions and thus a breakthrough innovation model implementation.

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Wednesday, 31 May 2023

Generative Creativity Is Anything But Common Goings-on

Not even one year ago, as the world slept, unaware ( except for a small group, relativistically ) of behind the scenes specialists, a 50yr race was running one of it's final relay sections. R&D Lab efforts unknown to most was about to break through it's shell where previously, the idea that Innovation Doesn't Have A Creativity Problem ; It's Got A Commitment Problem assumed that creativity was once like R&D ( a capability of a specific number of people, with advanced equipment ) was the case, but that with focus, creativity could be accessed by many. That however was all about to change.

Little did the world know, we would soon all have a capability in our hands in no short time that would radically up-end the idea of even the thought of ownership and now it seems Generative AI Has an Intellectual Property Problem where creativity is instantaneous and editable. Gone are the notions of years of graduate school necessary to hone the capability of creativity, but more, the capability to manifest it via highly specific technological tools, etc,. now leading us to a new torture: the legal and ethical challenges posed by generative AI, stemming from content based on existing data scraped from the web for free. Now, with Generative AI the disruption of the design world ( an AI enabling faster and more diverse creation of images, text, and other forms of expression ) is right on top of us all.

Can AI platform uses photos from a licensing service without permission to generate new images, violating the service's rights and expose itself and its users to legal action? Could it even be proven via some yet unknown reverse engineering of Ai created images to show their relevance to existing works, if those works could even be found and proven related? With AI platform and systems generating images resembling a famous painting or a brand logo, while it may infringe on the rights of the artist or the company that owns them could it even be that an artist or creator would even have the capability, let alone raw cash to mount such a lawsuit? Chances are no. There are the ideas of the fair use doctrine, if it is even possible to say that a new work is a criticism, comment, education, or research, but worse that as we all know, once it is on the web, the chances of ever having it taken down, not to mention again, the cost means that Generative Ai is the ever morphing digital noose that has no chance of ever being stopped thanks to in fact search engines. The noose tightens.

Creators, designers, architects, engineers then are faced with transparency and accountability for generative AI platforms but again, could the costs to even mount a case where designers and developers must prove license and compensation for content creators used to train their models, and maintain provenance records of the AI-generated works that include information about the platform, settings, seed data, metadata, and prompt even be possible? Unlikely. Confidential data, trade secrets, personal information and even within the context of millimeter by millimeter exact copies of works, functionalities and even family photos used on the packaging ( as in the incredibly famous X-IT vs. Kiddy case - an open and shut situation that took 20yrs to come to court with a $116M judgement knocked down to $17M in final payout ) means Ai and Generative art are not only untraceable but even less protectable. The raw power and capability of Ai Generative art and nano-second publishing means an unlimited zeitgeist fire hose of power can be wielded and for which no laws can even begin to contain said capability. The 10,000b gorilla Genii is out of the bottle and now there is nothing that can ever contain it again.

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Friday, 28 April 2023

Invention <> Innovation <> Intrapreneurship

With the plethora of design & innovation paradoxes at hand today, the reality is NPD ( new product development ) efforts and the turnaround roadblocks that are persistent in many situations ( to get from 0 to 1 ) are vastly different from the standpoint of usability that typical " successes " define.

Many times and known well often as the:
     • Innovation ( it works on a lab bench ) ;
     • Innovation ( a transition against the tides of "no" it's not acceptable ) into usability; and onto
     • Intrapreneurship ( at enough large enough firms ) so that usability is increased.
model, this also can be in an entrepreneurship model however the balance remains the same.

Seen in The Twelve Paradoxes of Innovation! and The Inescapable Paradox of Managing Creativity and more interestingly The Real Leadership Lessons of Steve Jobs where surprisingly we see the same pattern: the people paradox is not an innovation intractability situation. What then separates the core sections of awareness ( that X is possible through unique invention ) accountability ( through the process of innovation insertion into an already existing or entirely new area of capability ) and then on to acceptance ( large exiting organizational usage via an intrapreneurial stamp of "ok" ) and then ( with large organizations ) incredible adoptable daily usage ?

The separation is in knowing what category of "Innovation" ( a severely overused description ) a situation or activity is part of, and not fooling ourselves where:
     • an effort of invention is taking place
vs.
     • the unknown valley of death where innovation often has to live and breathe
and squarely between
     • the non top and ever pursuing step of intrapreneurship / entrepreneurship, or frankly, selling.

Where we see Job's efforts to mitigate this with: Focus ; Simplify ; Take Responsibility End to End ; When Behind, Leapfrog ; Put Products Before Profits ; Don’t Be a Slave To Focus Groups ; Bend Reality ; Impute ; Push for Perfection ; Tolerate Only “A” Players ; Engage Face-to-Face ; Know Both the Big Picture and the Details ; Combine the Humanities with the Sciences ; Stay Hungry ; Stay Foolish, so many of these are standard cannon in the New Product Development toolbox. More we see how Paradoxes of Innovation bind the idea of immediate results with grander capabilities and certainly vision and thus managing creativity is firmly mixed into this.

Knowing, Noticing and Locking down the core essences of the three phases of Zero to One in the rapidly evolving functional and aesthetic hyperplane that is design, engineering and finance and as all connected to an innovation mindset requires a capability to hold desperate and often contradicting capabilities all at the same time while progressing forward towards an often fuzzy and moving goal, however, in the end, it is ultimately reached.

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