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DNA Learning? a quantum leap… if we can change our binary paradigm


Microsoft and the University of Washington announced they had produced a breakthrough in computing power, by storing and retrieving video files successfully in a DNA molecule.


With its vast flexibility and capacity for multiple, parallel computing, DNA computing is quite likely the way of the future for developing the most promising forms of Artificial Intelligence or, in other words -artificial learning, human-made systems that can learn and solve new problems and complex situations in shorter times.



The “marriage” of computing tech and nano biology presents a very interesting example of what we could call “retro-innovation”, for that kind of “invention” that actually is based on “reverse-engineering” Nature.










Almost a hundred years ago, quantum theory proposed the idea that the macrocosm, our physical universe actually mirrors our microcosm -the subatomic structure-.


Canadian animation filmmaker Norman McLaren explained it very clearly in his 1955’s film “Cosmic Zoom”


 Entrepreneurial ecosystems as DNA value chains


When we apply this DNA model to social and economic systems, we recognize how the components of a entrepreneurial ecosystem work and relate in multiple dimensions.


Customers, suppliers and human capital interact in different value chains -much like those of DNA and RNA- moving ever more fluidly between what traditional management theory conceived as independent, closed “companies”, separated by ownership and legal incorporation.


In reality, organizations operate much more like cells or tissue -engines and tires to cars and highways and parking and pollution-, growing and creating new challenges, transferring information and know-how and people.



From Digital to DNA-thinking: the next frontier


The most immediate application of DNA-modeling and DNA-learning is in cracking the code of cancer.


Quite in the same manner in which Turing cracked the code of the Enigma machine, cancer researchers have been cracking the code of cancer cells and tumors. It took decades to digital computers to digitize the basic DNA. Finding what makes normal cells and tissues turn cancerous present daunting challenges for even the most powerful digital computers.


Cancer researchedrs and nano technologists have moved away from the “digital”, binary and Boolean computing paradigm towards the more fluid processes of parallel processing that happen at the nano-scale in the DNA structure.

Their bet is that DNA could be programmed to track, identify and released inhibitors or blockers of cancer cells. DNA “nano-robots” have already shown experimentally they could track and destroy tumorous cells.



DNA-nanobots can solve complex problems like how, why and which cells turn into cancer cells more efficiently not because they have more “digital” power, but because they work in a non-digital, non-binary way, speaking cells’ (and tumors’) “natural language”.


The challenge that DNA tech presents is that we still can’t speak -or understand- fluently that “language”. DNA tech, however, may have to bypass the “digital conversion” we used with silicon-based chips and “stamped” micro-circuits and use the more fluid, multi-dimensional DNA architecture.



While integrated semiconductor circuits are like rails, DNA structures operate like growing tissues, changing as they move and evolve. Finding the way to engineer DNA -even without fully knowing how it works yet- might be the next step in dealing with living, open systems like our universe and our bodies.


Next generations might learn DNA coding as ours have learned digital. Thinking beyond binary and digital is the next big paradigm shift challenge.

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