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.

iGNITIATE - Generative Creativity Is Anything But Common Goings-on

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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