Developing The Accelerated Immersive Learning Process

The META-OBJECTIVE or LARGE GOAL of this activity is developing our Accelerated Immersive Learning Process. In order to develop this discipline … we need a more specific, practical project in which to develop the process. As part of this, we will want to be searching extensively, exhaustively for inexpensive demonstration or prototype-level projects and opportunities for involvement in development communities which are working in the area targeted by our Accelerated Immersive Learning Process. Of course, the exact content for any self-starting autodidact using a process like this would be adapted [by that autodidact] based on that individual’s prior experience and their particular learning requirements.

The more specific, more practical goal which we develop [see below at FUNDAMENTALS Heading] is about providing a comprehensive, but not exhaustive, curriculum that will enable the learner to build a solid foundation in what it means to think as a polyglot as we develop a working background inRust-Lang, WebAssembly, Tauri, ROS2, and distributed systems. In a nutshell, we want to develop the foundational skills for building fault-tolerant real-time operating systems for robot swarms operating in adversarial environoments.

How we LEARN immersively is the key to how we WILL think

We WILL think more intuitively … because become powerusers of AI assistants, along with the upgrades in AI assistants, WILL rewire our brains … in the same way that people who once could can no longer do math in their heads, because capable people are busy people who are counted on do other more demanding things now … memorizing factoids does not matter when we have things like Wikipedia and even better knowledge technology. Human brains ADAPT and they WILL ADAPT even further than we can now imagine, in the same way that working with spreadsheets and CAD tools rewired the brains of people who were machinists who were [descended from] farmers and blacksmiths who were [descended from] hunter-gatherers … we already know this from basic neuroscience: PROFICIENCY with the tool changes the physiological neurocognitive capacity of the tool user and tool builder.

We WILL think more intuitively … because AI assistants will handle the routine, tedious, and repetitive thinking for us. We WILL think more intuitively and that means that we need to get more serious about changing the way that we learn.

We WILL think more intuitively … for example, let’s start off with the seemingly outrageous claim that working in the realm of cognitive radio (CR) for autonomous real-time fault tolerant swarm robotics is actually a means of training for meditative awareness.

Yeah, that’s OBVIOUSLY a total stretch … humans do not THINK like computers … or do they? AT TIMES? Maybe we should ponder what kinds of human thinking and better awareness of cognitive strategies would actually help people to THINK HEALTHIER and live better …

How we LEARN immersively is the key to how we WILL think

We should never stop learning IMMERSIVELY … … in fact we should accelerate the plunge in immersive learning so that a portion of our brain is continually in that mode of learning how to speak, to hear, what to watch and how we learned to THINK and be aware of our cognitive strategies in our [first] native language.

Consider the following proposed 200-module training regimen [given below] for a year-long deep plunge off the deeper sort of deep ends into learning to think like a native in the Rust programming language with a focus on developing programming capabilities and toolchains for working in predictive fault-tolerance in real-time operating systems [RTOS] for swarm robotics which might include developing the capability to incorporate the latest thinking research to optimize cognitive radio for RT-FT swarm robotics.

Per the ORIGINAL PLAN for our immersive learning plunge, the modules almost appear to be designed to progressively build skills, starting with Rust fundamentals, then moving into lower-level systems concepts crucial for RTOS development, followed by a deeper plunge into embedded and real-time modules that dive deeper into the specifics of constrained environments and deterministic execution …

EXCEPT this is immersive training that gets more progressively immersive, so we’re certainly not going to just STICK WITH the original plan … we live in an AI-enabled age, so we are going to try to learn by IMMERSION … that means trying to skim over and grok the entire syllabus in a week or a couple weeks or maybe a month at most … but we are going to drink from the firehose.

Of course, it’s perfectly okay to revise/extend the syllabus as we go along BUT …

THE SYLLABUS BRINGS US BACK TO CENTER

At some point, when we have really squeezed all the just out of the ol’ lemon, we are going to ask our AI assistant an UPDATED VERSION of our original question to furnish us with a new, improved, updated syllabus although we will keep the old one for reference.

"Please develop a 200 module training regimen for a year-long deep dive into learning to program with Rust-Lang, including WASM, the Tauri application toolkit, ROS2 with Rust bindings and other intracies of Rust-Lang and getting closer to the machine. The general objective for this year-long training regimen should be in the realm of developing the capabilities and toolchain for developing fault-tolerant real-time operating systems for swarm robotics."

The POINT of this exercise is about developing the Diffversity aproach to IMMERSION learning … and overwhelming ourselves with an understanding of the topic … in order to be able to ask progressively better questions … in our FIRST revision of our 200-module syllabus, there are SIX different sections: 1)Fundamentals (50 modules), 2) Systems Programming (40 modules), 3) Embedded & Real-Time Systems (40 modules), 4)WebAssembly & Tauri (20 modules), 5) Robotics & ROS2 (30 modules), 6) Distributed Systems (20 modules). The first thing that we do is to skim over the outline syllabus and then start “putting some meat on the bones” of the outline, by adding some additional content to each of the sections … but as we do this, our understanding of the outline will change and we will start re-prioritizing the content of the Sections or even adding/subtracting Sections from the outline … we will keep the ORIGINAL outline here for reference, with REV1 as separate document with future REVS being increment in Semantic Versioning ##.##.## fashion … so this post [even if we update/clarify the above description] will be the ORIGINAL starting point, but we will always be working on the next new UPDATED rev of outline with CloudKernelOS even as we maintain archive of starting prior-to-next-rev points as cookie crumbs to follow back to the beginning.

Fundamentals (50 modules):

1-10: Rust basics - syntax, data types, variables, functions, control flow

11-20: Ownership, borrowing, lifetimes

21-30: Structs, enums, pattern matching

31-35: Error handling, Option, Result

36-40: Modules, crates, workspaces

41-45: Testing, debugging, documentation

46-50: Standard library, common collections

Systems Programming (40 modules):

51-60: Memory layout, pointers, unsafe Rust

61-65: Concurrency, threads, sync primitives

66-70: Parallelism, rayon, crossbeam

71-75: FFI, linking to C code

76-80: Allocators, custom allocators

81-90: Performance, profiling, optimization

Embedded & Real-Time Systems (40 modules):

91-100: Embedded basics, no_std, memory-mapped registers

101-105: Interrupts, exceptions, fault handling

106-110: Device drivers, I/O

111-120: Real-time scheduling, RTOS concepts

121-125: Time handling, clocks, timers

126-130: Predictability, worst-case execution time

WebAssembly & Tauri (20 modules):

131-135: WebAssembly basics, Rust to WASM

136-140: JavaScript interop, wasm-bindgen

141-145: Tauri fundamentals, project setup

146-150: UI development with Tauri

Robotics & ROS2 (30 modules):

151-160: Robotics fundamentals, kinematics, control

161-165: Sensors, actuators, interfacing

166-170: ROS2 architecture, nodes, topics

171-175: Navigation, path planning, obstacle avoidance

176-180: Computer vision, image processing

Distributed Systems (20 modules):

181-185: Distributed algorithms, consensus, gossip

186-190: Fault tolerance, replication, sharding

191-195: Networking, protocols, message passing

196-200: Security, authentication, encryption

WebAssembly and Tauri are included to enable UI development and potential off-loading of computation. The robotics portion covers essential concepts and ROS2 integration.

Distributed systems modules prepare for the challenges of swarm robotics, such as coordination, resilience, and security. Extensive practice projects and coding exercises should accompany the theoretical material.