Equational

Today I helped a student review his study options (Bachelor level). We discussed and looked at the courses the university offered in four areas: machine learning, computer science, cyber security, financial engineering. Debating the 'deeper analytical learnings', I mentioned the following: Machine Learning ML is much about models of models in a very mathematical sense. No one knows how to teach it that way (yet). One tends to learn more about ML tools and technics than theory. Computer Science Few model in computer science because expensive, very hard to manage and hard 'get right'.  However, applied math and crypto/blockchain domains are easier to approach in a 'modelled CS approach'. Functional programming is a highly effective way to be successful in doing that.  The CSL language from Elevence , a functional language, was a rare 'purely modelled CS effort' ( inspired by complementary higher-order type properties , now named DAML). It was also a rare e...

Use your brains when developing abstract innovation. It is a game of 'balance': you think-up what is needed, you set goals that take advantage of your thinking, then you work towards your goals. If on the way something does not fit, review your goals or thinking. It is an iterative effort, you try, you repeat, until it works. Here are the three iterative steps in more details: State what you believe is true Express implementation goals that will leverage your beliefs Check consistency of goals with respect to your environment and to underlying beliefs Correct your beliefs if inconsistencies are found between goals and environment Develop towards your implementation goals Check consistency of development with respect to environment and underlying goals and beliefs Correct goals or beliefs if inconsistencies found between development and environment At first, one tends often to 'juggle' and develop just one idea at a time, when developing this way. Yet with experience it ...

July 1 2015,  I moved into a single office room at the Zurich Technopark  as the sole founding employee of Elevence Digital Finance (11ce). I assembled my sit-stand-desk. I used my personal laptop to write the specs for an 'authenticated contract logic database'. Also, I setup my beamer and flip chart stand! I mention this because I found the following note today dated July 1, 2015, where I 'sold' those objects to 11ce: We used this beamer internally, yet more importantly, we used it to pitches the contract modelling language we developed that year. 11ce was crazy successful and acquired by Digital Asset in 2016 . All original content copyright James Litsios, 2022.

These are all pre-2000, and in chronological order: A 'Hunt the Wumpus' like maze adventure program on my Commodore P100 programable calculator. Given the max of 72 program steps and 10 memory cells of the P100, this was probably the first time I used a rudimentary hash noise function (in this case to generate the maze 'on the fly', and not need to store it). A primitive LISP like eval loop on my HP-41C, with symbolic derivatives and simplification. The integer part of the memory cells were the 'car' part, and the fractional part being the 'cdr' part (with an appropriate scaling). A Fortran 2d finite element solver, 'mesher' and plotter on my schools 'new' VAX/VMS. The only early program that I still have, as it is printed as an appendix to my 'hand typed' BS EE thesis. A bridge calculation: A two player 3d wireframe helicopter against tank simulator/shooter game (C and assembly, on my 4MHz Intel 8088 Cannon AS-100 The screen and ...