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This paper theorises about the behaviour of firms engaged in complex product systems innovation and engineering under the lean startup/minimum viable product process. In doing so, it fills a gap in the literature at the intersection of innovation management and behavioural economics. By deconstructing the concept of commercial value, we assemble, define and structure the relationships among seven values that innovation teams encounter along the path of innovation. Then, we demonstrate the usefulness of the proposed framework by applying it to the case of algorithmic financial systems. The model of capability developed for this domain may have broader applicability. For innovations where performance is probabilistic and achieves a steady state, capability can define what counts as “good enough” commercial value.

Lévy processes, which have stationary independent increments, are ideal for modelling the various types of noise that can arise in communication channels. If a Lévy process admits exponential moments, then there exists a parametric family of measure changes called Esscher transformations. If the parameter is replaced with an independent random variable, the true value of which represents a ‘message’, then under the transformed measure the original Lévy process takes on the character of an ‘information process’. In this paper we develop a theory of such Lévy information processes. The underlying Lévy process, which we call the fiducial process, represents the ‘noise type’. Each such noise type is capable of carrying a message of a certain specification. A number of examples are worked out in detail, including information processes of the Brownian, Poisson, gamma, variance gamma, negative binomial, inverse Gaussian and normal inverse Gaussian type. Although in general there is no additive decomposition of information into signal and noise, one is led nevertheless for each noise type to a well-defined scheme for signal detection and enhancement relevant to a variety of practical situations.

If we want to define a universal concept of information, we have to cover not only objective statistical information, but also subjective experiential and meaningful cognition as well as intersubjective meaningful communication in nature, technology, and society. In that case the main problem is to decide which transdisciplinary philosophy of knowledge framework the concept of information should be based on and integrated in. All the ontological attempts to create objective concepts of information result in concepts that cannot encompass meaning and experience of embodied living and social systems. There is no conclusive evidence that proofs that the core of reality across nature, culture, life and mind is purely either statistical or of a computational nature. Therefore the core of the information concept should not only be based on pure logical or mathematical rationality. We need to include interpretation, signification and meaning construction in our transdisciplinary framework for informa-tion as a basic aspect of reality alongside the physical, chemical and molecular biological. It is difficult to produce a pure quantitative statement independently of a qualitative analysis based on some sort of relation to the human condition as a semiotic animal. But this direction of research leads us out of the world of technology into the world of the living. To follow the transdisciplinary ambition in much information science and philosophy leading to cognitive science we need to include a phenomenological and hermeneutical ground in order to encompass a theory of interpretative meaning and signification to achieve a transdisciplinary theory of knowing and communication. This is also true if we start in cybernetics and system theory that also have transdisciplinary aspirations for instance in Bateson’s ecological concept of information as a difference that makes a difference and in Luhmann’s triple autopoietic communication based system theory, where information is always a part of a message. Charles Sanders Peirce’s pragmaticist semiotics differs from other paradigms in that it integrates logic and information in interpretative semiotics. I therefore suggest alternatively building information theories based on semiotics from the basic relations of embodied living systems meaningful cognition and communication. I agree with Peircean biosemiotics that all transdisciplinary information concepts in order to work across the natural, technical, social and humanistic sciences must be defined as a part of real relational meaningful sign-processes manifesting as tokens. Thus Peirce’s information theory is empirically based in a realistic worldview, which through modern biosemiotics includes all living systems.

The principal criteria Cn (n = 1 to 23) and grammatical production rules are set out of a universal computational rewrite language spelling out a semantic description of an emergent, self-organizing architecture for the cosmos. These language productions already predicate: (1) Einstein’s conservation law of energy, momentum and mass and, subsequently, (2) with respect to gauge invariant relativistic space time (both Lorentz special & Einstein general); (3) Standard Model elementary particle physics; (4) the periodic table of the elements & chemical valence; and (5) the molecular biological basis of the DNA / RNA genetic code; so enabling the Cybernetic Machine specialist Groups Mission Statement premise;** (6) that natural semantic language thinking at the higher level of the self-organized emergent chemical molecular complexity of the human brain (only surpassed by that of the cosmos itself!) would be realized (7) by this same universal semantic language via (8) an architecture of a conscious human brain/mind and self which, it predicates consists of its neural / glia and microtubule substrates respectively, so as to endow it with; (9) the intelligent semantic capability to be able to specify, symbolize, spell out and understand the cosmos that conceived it; and (10) provide a quantum physical explanation of consciousness and of how (11) the dichotomy between first person subjectivity and third person objectivity or ‘hard problem’ is resolved.

This study presents evidence that executable computer programs and human genomes contain similar patterns of repetitive code. When viewed with sequence visualization tools, these similarities are both striking and pervasive. The primary similarities are listed in order of scale: (1) homopolymers, (2) tandem repeats, (3) distributed repeats, (4) isochores, (5) and entire chromosome/file organization. Most strikingly, data visualization reveals that executable codes regularly make extensive use of tandem repeats which exhibit similar visual patterns as seen in higher genomes. In biology these tandem repeat patterns are normally attributed to replication errors, insertions, deletions, and substitutions. Similarly, on a larger scale, executable codes display regions with different ratios of 1's and 0's which parallel the isochore patterns within chromosomes, caused by local variation in the number of A/T vs. G/C. Further, blocks of data are stored at the beginning or end of a file, while the primary instructions occupy the middle of a file. This creates the same organizational patterns observed in human chromosome arms, where repetitive sequences are grouped near the telomeres and centromeres.

I propose that these similarities can be explained by universal constraints in efficient information encoding and execution. The genome may be viewed as the executable program that encodes life. Given the evidence that computer programs and genomes use many of the same patterns of organization, despite having very different context, it should be informative to explore the ways in which knowledge of computer architecture can be applied to biology and vice versa.