Analogies and synergies of Artificial Intelligence for Carbotopia

Artificial Intelligence started in 1956 by naming the theme anticipating what it started to become only recently! In a way it was a rather provocative working title at the time. In particular deterministic thinkers especially Germanics would just insist it to be a never deliverable daydream! Partly also because of the slight differences between the German perception of the word “Intelligenz” and its comprehensive much more organic meaning in the English language or American Politics.

Carbotopia™ seems to be facing a very similar misperception issue. Germanics just arrogantly interpret it as an admitted daydream, while historically the meaning of Utopia was more an Oasis kind of self- sustainable island state able to live without needing any imports. And that is what Carbotopia stands for in terms of our contemporarily most consummated anthropogenic resource. It’s Carbon, the one of the two basic building blocks of Nature which can store energy – the other one is water, luckily commonly just contaminated when used, but chemically kept unchanged in the contemporary loop. In contrary to the Carbon which mankind has taken the habit of discarding it after every single use by transformation into CO2 – which is a chemical change into a different aggregate – as if Carbon was a one-way package of energy! Since the recuperation of Carbon from CO2 is still a very inefficient option, it would be much wiser to just use Carbon most effectively only, or re-use it beyond its primary role for at least one more time. Properly done such practice can eliminate idling losses and 2.5-fold energy efficiency. Provided intelligence will outperform egotistic stakeholder interests AI’s victory in Alpha GO just a few years ago gives rise to hopes that Artificial Intelligence will finger point onto solutions so far withheld, blackmailed or made ridiculous by current eco-system profiteers by impartially identifying the best practices. For example Carbotopia™ which is just a novel combination of proven state of the art Technologies. Its result is a maximum rate of re-usable Carbon from any carbonaceous end of life-cycle feedstocks leaving the least CO2 transformation losses behind.

While expert systems and even symbol processing were always limited to the thinking pattern of their programmers, deep learning algorithms now demonstrated 60 years after John Mac Carthy had raised utopist expectations of Artificial Intelligence imaginations, the algorithms of Alex Krijewski and Joffrey Hinton resulted in a new unprecedented logic by conclusions off weighed Yes/No value matrix knots. So inputs, intermediate results and possible outputs can be recognized like rateable images. In contrast to symbolism which relies on perfect match of pre-described criteria for Yes/No, deep learning algorithms can prevent „taking a wrong turn“ at an imperfectly appearing criteria. So the system becomes capable of its own choice for the further direction of analysis and potential solution comparisons relatively to whether a rather Yes or No weighed intermediate result. It’s a little bit like the birds’ swarm orientation. This way a new criteria can become the destination, never considered by its programmers before.

I would call Carbon Efficiency such an example! Until three years ago I was modeling then not yet named Carbotopia™ Technology applications simply driven by the objectives of finding the highest added value from decomposed waste. After my life-experience of passing by a huge waste dump when exiting a High Tech Park through a „back-door“ in an emerging country, I had this dream, that all the clean-room factories there could use the Hydrogen our patented process could deliver from the Methane fraction of the landfill gas. After my former special materials company had been pirated away from me this memory enticed me to study feasibility. One ASEAN country even took the Captured Carbon part of my concepts for a National Initiative by some State owned peer companies on their own. So I had to move on and ended up investigating possibilities of then still unbranded Carbotopia™ Technology to provide for cleaner use of coal in China. But legislation there had already preempted most fields of coal use for possible plant scales of Technologies used by us. Nevertheless China taught me the term of Carbon Efficiency, which by original definition was rather meant as an Energy Efficiency extended by efforts of lowering electricity‘s average Carbon ratio through ambitiously emerging renewable Energy into its grids. However volatile Renewable Electricity without economic back-up solutions often showed adverse effects on idling rates of conventional power stations. And quite aggrieving Carbon Neutrality accounting inspired us to look at Carbon Efficiencies in comparison to most effective re-Use of Recycled Carbon. The results at first were unbelievable but indicated that Carbon Circularity together with all efficiency improvements and economically reasonable use of Carbon free Renewable Energies could actually facilitate fossil-free economies covering their Carbon needs from Recycling Carbon from all end of life-cycle carbonaceous residues not useful for agricultural composts. So in reality AI would weigh Carbon Efficiency as “the“ measurable benchmark for sustainability accounting!

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