The clue in your description is that you are a software engineer in management. I would guess that most if not all the other managers are from non-technical backgrounds. Thus they are directly or indirectly indoctrinated into MBA and/or McKinsey Management Consulting group-think. Only the insecure and their sychophants would instigate the sorts of practices that you describe.
Hate to put it bluntly, but you are attempting to swim against the tide by attempting any form of debate and examination of dissent. The management team around you have played their hand. It appears that you are vastly out-numbered.
You have two choices: go with the status quo; or the highway.
Sadly that is a very common situation. Thus even more fitting to celebrate those who are still working, learning and enjoying their programming careers.
The only Power based supercomputers I can think of are all from IBM. Does any other vendor use them?
Power CPUs tend to power either iSeries (latest iteration of AS/400 - System38 etc) systems or AIX based. The large AIX systems use lots of CPUs, cores and typically vPars - but I wouldn't call them supercomputers. Disk I/O is generally FC attached SAN, i.e. performance is achieved through off-loading. A typical SAN array contains gigabytes of caching memory, CPUs on each disk drive with yet more RAM and multiple optical FC links to each node.
I have worked for companies that used both. Based on those experiences:
Use Power RISC with AIX in established IBM user organisation that wanted to run Unix software so we ported existing software to AIX.
Use existing s390 system running several core systems, to run Unix partitions to deploy software already written for Unix in C.
I have never even heard of any company not already being an IBM account migrating to either of those systems. The capital and operating costs are typically far higher than for comparable performance x86 based deployments. Technical staffing is much harder still.
It's many years since I last saw or worked on a PDP-11. The only operational ones I know of are as embedded systems, that includes LSI-11 variants. That is, industrial and niche scientific applications.
I have worked extensively in finance and have never seen nor heard of a PDP-11 being used. A long time ago some DecSystems were in use. But those were all programmed in COBOL.
I'm struggling with your question, yet intrigued by the problem.
When you are new in an organisation, it is very common to feel awkward in making smalltalk and being remote would make it even more so. What technology are you conducting your conversations with? With Zoom you can read body language, etc. Using messaging alone provides far less clues.
I presume that you have been assigned a mentor and some tasks to perform. In which case, I would expect that your conversations pertain to the work you are doing and not shooting the breeze by the water cooler. Perhaps a good starting step would be to talk about aspects of the tasks at hand and then expand from there, asking about the decisions that led to the design / architecture / tool choices and from there the roles and personalities involved.
Yet another example of how clueless managements are. They are incapable of actually assessing value of the actual work performed. So they use proxy metrics like LoC, hours worked, in-person presence in the office.
If you want to paid very well, then churn out thousands of lines of rubbish code, be in the office for 70+ hours, attend their meetings, pay rapt attention to their PowerPoints and laugh at their jokes. Bingo!
Selling the vision is both an in-house as well as marketing aspect. When you have hundreds of people working on the product design and realisation, the CEO has to figure out how to make payroll, keep investors happy, get suppliers to extend greater levels of credit, ensure that manufacturing ramps up. Successful CEOs are not micromanagers. Steve Jobs is well known for providing scathing feedback, but not for actually sitting down and sketching out designs.
I did some work with SWI-Prolog. It is useful when the problem can be effectively translated into Prolog's preferred form of terms and rules. But the solver mechanism only solves a subset of logical inference needs. Prolog's use of logic in AI should not be conflated with the AI/ML systems which use networks of floating point operations, i.e. not boolean operations.
As always, best to choose the tool / language that best suits the problem.
There are many Common Lisp and Scheme environments. Many have excellent JIT compilers. They all have their relative strengths and weaknesses. So it really depends on your specific use case as to which environment has the best support. For me the biggest factor is that Lisp is very productive for use by a small and competent team. In those situations they tend to create a DSL and evolve the system. PG's essay describes the reason Lisp fails many projects in the section "The Blub Paradox".
United Nations has 193 member countries. Of those only a handful can lay claim to having one or more big open-source projects/libraries/languages. So the question does not relate solely to India.
Looking at what factors lead to such results might provide some insights as to what could be done to foster such contributions.
I know several very successful actuaries who also write a fair bit of advanced code. Insurance companies are always looking for quantitative improvements and it is far more expedient when the actuary doesn't have to explain (in excruciating detail) the requirements to a programmer without the same math chops.
One of my friends got his PhD in math a couple of years ago. He has since been working for various merchant banks and investment managers as a consultant. I have come across several other math majors in insurance industry as well.
Not exactly the answer you are looking, but in my view:
Academic research is focused on extending / expanding the knowledge in a very specific and often narrow field. The papers are written for other scholars working in the same or related fields. The desired result is the amplification of knowledge in that field.
Journalists are focused on disseminating information on timely matters to a broad audience. When journalists report on material from academic papers, then need to translate the material so that non-specialists can comprehend the core concepts presented in the papers. In order to do perform this role well, journalists need to have at least undergraduate level knowledge in the relevant fields.
Academic scholars have 10+ years experience in their specialist fields, there is no way that you can easily bridge the knowledge gap to that of the general public. That is why journalists are trained to write simply and to use a basic vocabulary.
It's far more than a nickel difference. Any useful private office is about 100 sq ft. In an open office you can do with about 20 sq ft per person. So you cram the workers into bull pens and the managers can have acres of offices with windows and still save money on mid-city rents.
My preference is to go to the pub to brainstorm over burgers and beer. I did work for a small biz where the owner would take us all out on Friday for that purpose. Most productive place I ever worked at. Eventually got bought out by a much bigger biz and it all went south.
Hate to put it bluntly, but you are attempting to swim against the tide by attempting any form of debate and examination of dissent. The management team around you have played their hand. It appears that you are vastly out-numbered.
You have two choices: go with the status quo; or the highway.