#algorithm and flowchart

[giti-1]

PROGRAMMING COURSES LEVEL ONE

Course Curriculum

The logic and programming

Algorithms and Flow charts

Understanding source codes.

The types of variables, constants, logical

The Input/Output.

Programming procedure

Programming in VB.Net

Programming in Python

Introducing the Object Oriented Programming

The loops and their logic

Website: https://giti-edu.ch/ 

Call: +41 /22 301 22 44

[playstationvii]

Jest: A Concept for a New Programming Language

Summary: "Jest" could be envisioned as a novel computer programming language with a focus on humor, playfulness, or efficiency in a specific domain. Its design might embrace creativity in syntax, a unique philosophy, or a purpose-driven ecosystem for developers. It could potentially bridge accessibility with functionality, making coding intuitive and enjoyable.

Definition: Jest: A hypothetical computer language designed with a balance of simplicity, expressiveness, and potentially humor. The name suggests it might include unconventional features, playful interactions, or focus on lightweight scripting with a minimalist approach to problem-solving.

Expansion: If Jest were to exist, it might embody these features:

Playful Syntax: Commands and expressions that use conversational, quirky, or approachable language. Example:

joke "Why did the loop break? It couldn't handle the pressure!"; if (laughs > 0) { clap(); }

Efficiency-Focused: Ideal for scripting, rapid prototyping, or teaching, with shortcuts that reduce boilerplate code.

Modular Philosophy: Encourages user-created modules or libraries, reflecting its playful tone with practical use cases.

Integrated Humor or Personality: Built-in error messages or prompts might be witty or personalized.

Flexibility: Multi-paradigm support, including functional, procedural, and object-oriented programming.

Transcription: An example code snippet for a Jest-like language:

// Hello World in Jest greet = "Hello, World!"; print(greet); laugh();

A Jest program that calculates Fibonacci numbers might look like this:

// Fibonacci in Jest fib = (n) => n < 2 ? n : fib(n-1) + fib(n-2);

joke "What's the Fibonacci sequence? You'll love it, it grows on you!"; n = 10; print("The Fibonacci number at", n, "is:", fib(n));

Potential Domains:

Gamified education

Creative industries

AI-driven storytelling

Interactive debugging

Would you like me to refine or explore additional aspects?

Certainly! If we were to imagine Jest as the brainchild of a creative coder or team, their portfolio would likely include other innovative or experimental programming languages. Let’s expand on this concept and invent some plausible complementary languages the same inventor might have designed.

Related Languages by the Inventor of Jest

Pantomime

Description: A visual programming language inspired by gesture and movement, where users "drag and drop" symbols or create flowcharts to express logic. Designed for non-coders or children to learn programming through interaction.

Key Features:

Icon-based syntax: Conditional loops, variables, and functions represented visually.

Works seamlessly with Jest for creating visual representations of Jest scripts.

Sample Code (Visual Representation): Flowchart blocks: Input → Decision → Output.

Facet

Description: A declarative programming language focusing on creativity and modularity, aimed at artists, designers, and 3D modelers. Facet could integrate well with game engines and creative suites like Blender or Unity.

Key Features:

Embedded visual tools for shaders, animations, and simulations.

Simplified expressions for creative coding (e.g., animations and generative art).

Sample Code:

shape = circle(radius: 10, color: "blue"); animation = wave(shape, amplitude: 5, frequency: 2); render(animation, duration: 10s);

Quip

Description: A lightweight scripting language built for humor, similar to Jest, but more focused on natural language processing, chatbots, and interactive storytelling.

Key Features:

Syntax mirrors conversational English.

Designed for AI integration, especially in storytelling apps.

Sample Code:

character "Alice" says "Hello! What's your name?"; user_input -> name; character "Alice" says "Nice to meet you, {name}!";

Cryptic

Description: A language for designing cryptography algorithms and secure communications. Aimed at developers interested in blockchain, encryption, or cybersecurity.

Key Features:

High-level abstractions for cryptographic primitives.

Secure-by-design philosophy.

Sample Code:

key = generate_key(algorithm: "AES", length: 256); encrypted_message = encrypt("Hello, World!", key); print(encrypted_message);

Harmony

Description: A reactive programming language for building interactive user interfaces, designed to be highly interoperable with Jest and other tools in the suite. Perfect for web developers and app creators.

Key Features:

Two-way data binding with minimal boilerplate.

Component-based architecture.

Sample Code:

component Button { state: clicked = false; onClick() { clicked = !clicked; alert("Button clicked!"); } } render(Button);

Inventor’s Vision

The coder or team behind Jest and these complementary languages would likely be passionate about:

Accessibility: Making programming intuitive and fun for people of all skill levels.

Playfulness: Infusing coding with creativity, humor, and expressiveness.

Interoperability: Ensuring all their languages work well together for larger projects.

Would you like me to dive deeper into one of these languages, conceptualize others, or expand Jest further?

Expanded Concepts and Bridge Languages

Pantomime

Expansion: Adds support for AR/VR interfaces where users use gestures to program logic in 3D space. For example, drawing a loop physically creates a repetitive cycle.

Bridge Language: GestureScript: Converts AR/VR gestures from Pantomime into traditional code for broader applications.

Facet

Expansion: Enhanced for generative AI tools, allowing users to define complex artistic styles and AI-driven procedural designs.

Bridge Language: PixelForge: Focused on exporting Facet code into game engines, enabling real-time rendering pipelines for interactive environments.

Quip

Expansion: Includes pre-trained AI models for dynamic storytelling, allowing Quip scripts to evolve based on user interaction.

Bridge Language: Narrate: Combines Quip scripts with voice-to-text technologies for live storytelling in games or educational tools.

Cryptic

Expansion: Introduces quantum-safe cryptography primitives and allows simulation of blockchain-like ecosystems for testing purposes.

Bridge Language: CipherBridge: Translates Cryptic code into various blockchain frameworks like Ethereum or Solana.

Harmony

Expansion: Gains support for cross-platform development, allowing users to write code for web, mobile, and IoT devices simultaneously.

Bridge Language: Symphony: Converts Harmony components into platform-native scripts for seamless integration.

Additional Bridge Languages

Echo: Bridges Quip and Jest, enabling storytelling code to trigger functional scripts for immersive experiences.

Morph: A universal language that compiles any Jest family code into executable binaries for specific operating systems.

Thread: Integrates Cryptic and Harmony to build secure, reactive user interfaces for fintech applications.

Canvas: Bridges Facet and Pantomime to create interactive art in AR/VR, blending visual coding with gesture inputs.

Let me know if you'd like a deeper dive into any specific language or bridge concept!

Here's a detailed exploration of Echo, Morph, Thread, Canvas, and all previously mentioned languages, emphasizing their unique applications and advanced functionalities.

Expanded Bridge Languages

Echo

Purpose: Links storytelling elements in Quip with functional programming in Jest, enabling dynamic, immersive interactions between narrative and logic.

Key Features:

Story-driven logic triggers: e.g., a character’s dialogue prompts a database query or API call.

Integration with AI tools for real-time responses.

Use Case: AI-driven chatbots that incorporate both storytelling and complex backend workflows.

Sample Code:

story_event "hero_arrives" triggers fetch_data("weather"); response = "The hero enters amidst a storm: {weather}.";

Morph

Purpose: Acts as a meta-compiler, translating any language in the Jest ecosystem into optimized, platform-specific binaries.

Key Features:

Universal compatibility across operating systems and architectures.

Performance tuning during compilation.

Use Case: Porting a Jest-based application to embedded systems or gaming consoles.

Sample Code:

input: Facet script; target_platform: "PS7"; compile_to_binary();

Thread

Purpose: Combines Cryptic's security features with Harmony's reactive architecture to create secure, interactive user interfaces.

Key Features:

Secure data binding for fintech or healthcare applications.

Integration with blockchain for smart contracts.

Use Case: Decentralized finance (DeFi) apps with intuitive, safe user interfaces.

Sample Code:

bind secure_input("account_number") to blockchain_check("balance"); render UI_component(balance_display);

Canvas

Purpose: Fuses Facet's generative design tools with Pantomime's gesture-based coding for AR/VR art creation.

Key Features:

Real-time 3D design with hand gestures.

Multi-modal export to AR/VR platforms or 3D printers.

Use Case: Collaborative VR environments for designers and architects.

Sample Code:

gesture: "draw_circle" → create_3D_shape("sphere"); gesture: "scale_up" → modify_shape("sphere", scale: 2x); render(scene);

Deep Dive into Main Languages

Jest

Philosophy: A playful, expressive scripting language with versatile syntax tailored for humor, experimentation, and creativity.

Core Application: Writing scripts that blend functional programming with a whimsical, human-readable style.

Pantomime

Expanded Features: Includes AI-driven gesture recognition for predictive modeling and natural motion capture.

Advanced Use: Developing AR apps for rehabilitation therapy where exercises are coded as gestures.

Facet

Advanced Use: Procedural generation in games, defining terrains, weather systems, and NPC behaviors with artistic flair.

Quip

Advanced Features: Integrates pre-trained language models for nuanced, character-driven dialogue trees.

Advanced Use: Creating adaptive narratives in games where user decisions alter the story arc.

Cryptic

Advanced Features: Quantum-safe algorithms and AI-enhanced key generation for unbreakable security.

Advanced Use: Designing multi-layered blockchain ecosystems with Cryptic’s high-level abstractions.

Harmony

Advanced Features: Adaptive UIs that respond to user emotion, tracked via AI-enhanced cameras.

Advanced Use: Apps for mental health, where interfaces adjust to user stress levels.

Proposed New Bridge Languages

Chord

Bridges Harmony and Facet for designing interactive music-based visual art.

Use Case: Music videos where the visuals respond to real-time sound input.

Path

Links Cryptic and Canvas for secure AR/VR environments.

Use Case: Virtual meetings in secure, customized 3D spaces.

Fable

Connects Quip and Pantomime for storytelling via interactive gestures.

Use Case: VR education apps where lessons are taught through immersive narratives.

Would you like a specific implementation plan for any of these languages or applications?

[emptymanuscript]

We Proved It: AI Mastering Is A Waste Of Money

Ok, this is quite interesting all on its own. If you’re in to music creation it’s probably worth watching for that.

But my particular interest is AI and art. More specifically AI and Creative Writing which this is not about but which I think probably shows some good parallels.

I’ll be frank and admit I have not actually experimented with any AI Creative Writing software because I’m not really comfortable at this time with the ethics of using AI for Creative Writing. Even as I’m not really comfortable ignoring it for fear that there is a basic technological advantage in some kind of normalized usage as a tool for professionals somewhere in there that is in the process of development and will eventually be usable without all the ethical concerns and I’m falling behind out of puritanism. So that’s my bias warning. Most of what I see and know about AI says it is not ok to use AND I am very suspicious about that answer because I don’t feel ok getting my hands dirty to double check my assumptions. 

I will also clarify that I don’t think the issue is that AI can’t create art. I’m significantly more worried that it CAN, just at a totally unacceptable cost. Even if it can’t right now, the rate of advancement tells me that now is very much a temporary state. If it is allowed to develop and gets consistent use, especially in the way it has done so far (utterly ignoring legal and moral boundaries) it absolutely WILL EVENTUALLY be able to fulfill its promises. That “eventually” may even be uncomfortably SOON. But, as is, that will be a bad thing, not a good thing because of the total costs involved in allowing that to occur.

Watching this, though, makes me suspect that using AI for creating art is really just an act of not realizing that better and more ethical tools have already been made. People have simply made a LOT of tools over the years to help themselves and others out.

What I’m particularly reminded of watching this is Plotto.

Plotto is an OLD book at this point, originally published in 1928. Cook originally wrote Plotto for himself as a way to speed up and simplify his own writing because he got paid by the word, and not very much per word. He made a successful career for himself by writing (and publishing) quite a lot of stories, extremely fast.

Plotto is essentially writing a plot summary via flowchart. It is a writing algorithm for how to plot according to what has worked in the past (same as an LLM), written before such a thing was remotely possible with computers. If your not sure how to plot a story, it is probably just as good as AI without the attendant moral struggles.

While Plotto is the most detailed and finely delineated example I can think of off the top of my head, it isn’t remotely the only thing that can help you do on your own what AI is supposedly doing for you but probably better in everything but the shortest run. 

Nearly every book I keep on my Creative Writing Recommendations page can help in this kind of pattern assembly without all the downsides.

And, nothing will help you quite as much as taking your favorite stories (I highly recommend starting with your favorite movies rather than books or television shows because they will be the quickest structures to digest) and using those resources to back engineer the mechanics of a particular story. 

The particular benefit is that you will not be utterly reliant on the tool. You, yourself, will improve and be able to challenge and innovate patterns to achieve particular desired effects. And those skills will continue to benefit you (assuming you use them) even if AI eventually gets to whatever place it needs to get for it to be the better choice because you will be able to discern what it does best and what you need other things for because you’ll be an expert on what actually needs doing by that point.

It will help you even right now. One of the people I keep running into in the AI Writing space is a guy working on a vampire novel in a historical setting. However, that is an incredibly loose definition of a story space, since many, many kinds of radically different stories can fit that definition. Simply plugging what he plugs in to the AI is allowing the AI to choose most of the details of even what kind of story he is writing. It may have a somewhat consistent output with itself but he isn’t wielding the kind of control he thinks he is. He’s simply accepting that this is how a vampire story works when that isn’t true at all. And I strongly suspect he doesn’t know that because he hasn’t read enough vampire stories to know what even is possible. That’s not terribly important if you want to write the kind of vampire story the AI happens to pick. It is necessarily shooting yourself in the foot if you want to write something else.

Which is WHY it is helpful to back engineer a lot of stories. Not random ones, mind you, ones you like. The act of back engineering your tastes yourself, instead of simply letting someone or something else do it, is that you can figure out the breadth of it and what resonates with you. Which you will always do BETTER than the average, even if the average may sell better in general principle. The hardest thing any iteration of AI is going to have to do is learn you as an individual rather than simply assume you follow simple statistical likelihoods.

Statistically speaking, you like James Cameron’s 2009 movie Avatar. And that is the most likely kind of story you will most likely make the highest profit with. Great if Avatar actually is your favorite movie of all time. A huge problem if it isn’t and that isn’t what you want to write. The more LIMITS you place on your possibilities, the more likely you are to get the correct answer.

There is a reason that Michelangelo described the process of making his famous David statue as simply removing everything that was not David from the stone.

But you have to know what is dross and what is David for that to work. And AI can’t do that for you. It can only imitate the choices others have already made AND it has no idea WHY those choices were made, which is the most important determiner of what is junk to be cut away and what is story to reveal. If you don’t know why, you don’t know what to cut.

So, learn.

It’s going to cost you the same amount of money and time to learn how to prompt the AI well at the expense of learning how to create story well. You might as well learn what will benefit you both ways.

[madelinelovesick]

Saraverse: How to coin words for a conlang when you don't know how

The phonology of Saraverse Language I, shown previously in its phonemic inventories but also constituting phonotactics and an evolution behind the scenes, is currently being looked over together with an actual professional linguist, who I do plan to compensate for their work. However, even in an incomplete state, I am actively anticipating the next steps, such as morphology and lexicon.

If I were crafting a single personal language without much regard for naturalism except in superficial ways, then this blog post could basically end here: I would be picking words and their meanings purely based on personal appeal. However, Saraverse Language I is intended to be the first of many, to say nothing of the Madelineverse's secondary languages, and eventually, I will end up with a language whose phonaesthetics work internally, but just aren't appealing to me personally, and yet, I'll still need to actively work on the language, making judgments as to what would and would not fit in the lexicon.

For this, I need a methodology, and a whole array of methodologies can be ruled out immediately due to producing unnaturalistic results. One of those is, of course, turning the phonology into a computer program that spits out valid words while brushing its teeth, and then simply using those, one by one. Even worse are the approaches rooted in the modern notion of "machine learning".

Instead, a rudimentary methodology I have devised is as follows:

Two differences from how flowcharts normally behave must be noted:

Though there is a START node, eventually, you will reach a small circle, which calls you to pay attention to what else is going to it, and even (in case of "a need to translate a specific text to the conlang") what else the information you obtained can be useful for.

Many of these are continuous processes; they are "unlocked" in a sense when a conlang gets to that point, but they don't ever stop or conclude unless the conlang's development as a whole concludes.

With regard to the lexicon generation, since a conlang requires a lexicon of >100 words to be usable by the conlanger and >1000 to be usable by people other than the conlanger*, each step in the lexicon part is designed to be automated or, if it does require human intervention, need at most a few seconds per human decision.

So far, Saraverse Language I has progressed to a point where I have 128 "calls to the conlanger" words, and am actively working on methods to create an ordered list of those (by either the proto-form's appeal or the modern form's appeal), a process which involves researching sorting algorithms. However, the details of that involve serious high math and are most likely far too technical for even the most seasoned of conlangers.

See you next Monday.

* no, Toki Pona is not an exception. Though it has ca. 140 words actually used and understood in the language community, those often combine to lexicalised compounds, as demonstrated by the fact that <jan pona> doesn't mean "simpleton" nor "Toki Pona speaker", and neither does <tomo tawa> mean "one of those witch huts on a giant chicken leg that is able to move on its own".

[1o1percentmilk]

the issue with AI chatbots is that they should NEVER be your first choice if you are building something to handle easily automated forms.... consider an algorithmic "choose your own adventure" style chatbot first

it really seems to me that the air canada chatbot was intended to be smth that could automatically handle customer service issues but honestly... if you do not need any sort of "human touch" then i would recommend a "fancier google form"... like a more advanced flowchart of issues. If you NEED AI to be part of your chatbot I would incorporate it as part of the input parsing - you should not be using it to generate new information!

[usmlestike]

How to use Chatgpt for Studying

Struggling with dense textbooks and endless Qbanks? You’re not alone. Many USMLE aspirants now turn to smarter tools like ChatGPT to simplify their prep. In this comprehensive guide on how to use ChatGPT to study for USMLE, you’ll discover how to transform this powerful AI into your daily tutor. Whether you're brushing up on biochem or decoding clinical cases, ChatGPT could be the secret weapon that makes the difference.

What is ChatGPT?

ChatGPT is an advanced AI developed by OpenAI, designed to understand and generate human-like text. Unlike traditional search engines or static websites, it can hold interactive conversations, break down complex topics, and act like a study partner who never gets tired. For medical students, especially those preparing for the USMLE Steps 1, 2 CK, and 3, this means real-time clarification, instant question generation, and concept reinforcement—on demand.

Why Use ChatGPT for USMLE Preparation?

Medical students and international graduates (FMGs) often face challenges like limited mentorship, resource overload, or difficulty understanding USMLE-specific content. Here’s where ChatGPT comes in:

✨ Key Benefits:

Instant Clarification: Stuck on nephrotic vs. nephritic syndrome? ChatGPT can break it down with analogies, diagrams, and examples.

Tailored Learning: It adapts to your level—whether you're just starting Step 1 or polishing Step 3 CCS cases.

Speed + Simplicity: Ask it to summarize, quiz you, or create visuals. It cuts through hours of reading.

Once you learn how to use ChatGPT for studying, you’ll find that it not only saves time but also builds deeper understanding through interactive dialogue.

Using ChatGPT for USMLE Step 1

Step 1 is foundational, testing your knowledge in subjects like physiology, biochemistry, pathology, microbiology, pharmacology, and more. It’s often viewed as the most intimidating phase. Here's how ChatGPT helps you power through:

🔍 Best Ways to Use ChatGPT for Step 1:

Explain Concepts Gradually: Prompt it with “Explain the citric acid cycle like I’m in high school,” and then follow up with, “Now explain it for USMLE level.”

Generate Mnemonics: Ask, “Create a mnemonic for cranial nerves and their functions,” and ChatGPT will return creative, memorable hooks.

Practice with Questions: Request, “Give me 10 high-yield MCQs on microbiology with detailed answers.”

Using ChatGPT for USMLE Step 2 CK

Step 2 CK emphasizes clinical reasoning and decision-making based on patient vignettes. It requires more than just recall—it tests how well you can apply knowledge in real-world scenarios.

🩺 ChatGPT Tips for Step 2 CK:

Simulate Cases: “Give me a patient case with HPI, vitals, and labs,” and then ask, “What’s the most likely diagnosis?”

Build Differentials: Provide symptoms and request a differential list. Follow with, “How do I rule each out?”

Clarify Diagnostic Steps: For topics like pulmonary embolism or diabetic ketoacidosis, ask for diagnostic workups in a flowchart format.

Example Prompt: “Simulate a 28-year-old female with RUQ pain. Include history, labs, imaging findings, and ask me to decide the next step.”

By repeatedly practicing this way, your reasoning becomes more structured, and vignettes stop feeling like puzzles.

Using ChatGPT for USMLE Step 3

Step 3 tests clinical management and your ability to prioritize care. It also includes CCS (Clinical Case Simulation) scenarios, which can be tough to practice without dedicated software.

💡 How to Use ChatGPT for Step 3:

Walk Through Full Cases: Prompt: “Walk me through a 15-minute CCS on DKA,” and follow its guidance while asking “Why?” at each step.

Treatment Algorithms: Use prompts like, “What’s the stepwise management of unstable angina?”

Prioritize Interventions: ChatGPT can help with decision-making questions: “Which is the most urgent next step?”

Pro Tip: Add a timer when running these cases with ChatGPT to simulate exam pressure.

ChatGPT Study Hacks: Smarter, Not Harder

Beyond the core prep, ChatGPT offers some game-changing hacks to accelerate your learning:

🚀 Proven Hacks:

Act Like a Professor: Prompt: “Pretend you’re a professor explaining cardiac physiology. Then quiz me.”

Flashcard Generator: Say, “Create 10 flashcards on renal pathology,” and get ready-to-use Q&As.

Condensed Notes: Use: “Summarize this First Aid page into 10 bullet points,” for fast revision sessions.

Interactive Recall: Try “Ask me 5 rapid-fire questions on antibiotics. Then explain what I got wrong.”

These tactics keep your mind active and make studying less passive and more engaged.

Limitations You Should Know

While ChatGPT is an incredibly useful companion, it isn’t a perfect replacement for all resources.

⚠️ Caution Points:

Outdated Info: Always verify answers using First Aid, UWorld, or official guidelines.

No Visuals (Yet): For now, it doesn’t show diagrams or histology slides—supplement with resources like Pathoma or Sketchy.

Exam Format: It won’t fully replicate the NBME or UWorld style unless you prompt it specifically.

So, think of ChatGPT as your tutor, not your test simulator.

Ethical Use for Medical Students

As future healthcare professionals, ethical usage is key:

✅ Use ChatGPT to enhance understanding, not bypass learning.

❌ Never use it during exams or assessments.

✅ Combine it with trusted resources and mentorship.

This helps build habits aligned with the values of medical professionalism.

Conclusion

Preparing for the USMLE can be overwhelming—but it doesn’t have to be. When you learn how to use ChatGPT for studying, you're unlocking a dynamic, personalized, and time-saving study tool. Whether you’re revising for Step 1’s foundational concepts, drilling clinical vignettes for Step 2 CK, or walking through emergency scenarios for Step 3, ChatGPT adapts to your needs.

Used ethically and strategically, ChatGPT isn’t just a chatbot—it becomes your daily tutor, quiz master, and study buddy. Add it to your prep toolkit, and watch your confidence—and scores—grow.  For more details visit https://usmlestrike.com/total-cost-of-usmle-journey/

[savagegardensprogramming]

CodeBlock Maps - Introduction

Take a look at Exhibit A – Its what I call a Code Block-Map. This is my crown jewel. A graphical code construct suitable for management level programming. Sub-Level 2 of SavageGardens.

Exhibit B is the sketch programming language. Its what the bright minds at MIT are working on. Its a toy. Its impractical for professional use. I am well aware as to why. I conceived something similar almost 30 years ago. I bet I wasn’t the only one.

Exhibit C is the book I was first taught programming. This book takes the flow chart approach. It does not want you take write a single line of code until you’ve drawn a full flowchart of your program. Its a painstaking approach because it takes a long time to draw a flowchart compared to the functionality you get from it. Very good for learning flow of logic but impractical for professional uses. This is the reason why the sketch programming language is what it is. It sits on the same situation. It takes too long to draw. It also takes too long to drag and drop. Mind you in the future we will have eye tracking and dragging & dropping will be done at a fraction of a second. Still, this kind of language will remain impractical.

I been sitting on this situation for literally decades. My break thru was to break out of the box. Stop using graphics to represent details. Graphical code constructs are not suitable for representing details. Lets look at sketch again Exhibit B. You see how they mapped a graphical representation to individual code constructs. One graphical representation for the if statement. Another one for a repeat loop. Another one for an individual function call such as play, stop, set volume, etc. Those are details.

Stepping out of the box for me was when I realized that graphical code constructs are good for representing big pictures. Managing the big pictures. Metaphorically speaking. Step away from the forest and look at the landscape. At a higher level you can move a whole mountain from the right to the left, Put the lake right next to it. Have the river move down from the lake and curb to the left. Put a small town situated at the curb of river. And finally mark an X on the mountain where Smaug the dragon hangs out. The point is managing the big picture items as opposed little details.

If mind-maps and flowcharts got together. CodeBlock Maps would be their child. CodeBlock maps is basically a map of blocks of code. What it maps out is flow of logic. Let rectangles represent a block of code. The code can be it as simple as adding two numbers together. Or as complex an AI algorithm with millions of lines of code. Then interlink these rectangles indicating flow of logic. That is it. LISP is just commas and parenthesis. CodeBlock maps is just rectangles and lines.

Exhibit D CodeBlock Maps are made up of individual CodeBlock Cells. A rectangle is referred to as a cell. Anyways here are the individual parts of a code block cell. Most of it is verbiage. I would say the only thing that translates into code is the fact that its a cell, the interlinks and the type descriptor.

Exhibit E. There are different verbiage requirements depending on the situation. Here I have enumerated them all. But at the core they are all the same fundamental construct. A rectangle interlinked with lines.

Exhibit F is syntax diagrams represented as a code block map. Good for representing recursive descent graphically. Note that CodeBlock Maps are about making code look pretty. It turns out that beauty has a practical use in code comprehension. I suspect women will enjoy programming in SavageGardens.

In SavageGardens I have designated code block maps as a sub-language for code management but mind you its quite capable on its own. It is touring complete. As simple and powerful as LISP. Its good for encapsulation. Good for divide-n-conquer. Good for abstraction. It fullfills the goals I have set out for SavageGardens. It exploits the brain functions of memory recall. It is 2 dimensional. It is graphical in nature. Good for code comprehension. Good for code navigation. Does not hinder code efficiency. Not so good for code articulation but three out of four is not bad. It does work well with other languages. Hence good for management.

[marsiiiiii]

ok i know i reblogged this already but i want it to be at the top of my blog rn cause im using this as a base for my final project for my algorithms and computational logic class

im just going to make one boss' logic with an expert system, here's the flowchart so far

(the first check is to see if the boss is on 1hp, then he'll nuke you and himself, if you die you lose hehe)

Game idea: you've got a series of spells you can use, which you cast by typing them.

But enemy bosses can attack your keyboard. Your "E" key is disabled. FIREBALL is out. ICE9? Also out. Guess they're getting hit with SUMMON FROG.

The bosses can also drop traps on your keys. So if N is trapped, you can cast SUMMON FROG, but the N-trap will go off and you'll take damage.

An advanced late game spell is THESAURUS, which lets you reanalyze a spell. Can't do SUMMON NIGHT WOLF because your N key is broken? THESAURUS it and now it's CREATE DARK DOG.

Another enemy attack would be putting a counter on your keys. So if they put a 1 on your R, you can cast "FIREBALL" but "CIRCLE OF TERROR" is right out.

The two can be combined: a trapped counter only goes off if you type more than the counter. So a trapped 2 on your S means "HEAL SELF" is fine but "TRANSFORM SELF TO SERPENT" will activate the trap and you'll take damage.

One late game boss attacks you by cutting your keyboard in half, and which half works alternates between turns. You gotta figure out which spells you can use that turn.

You could do some fun gimmick-fights. Like a boss sweeps your keyboard off the table and makes you play scrabble instead: you have to spell spells to cast them.

Or wheel of fortune, where you have to get enough money to be able to buy vowels before you can cast spells with vowels in them. The puzzle on the board is a spell the boss is going to cast against you, so it's also a fight against time. If you correctly guess too many letters, they'll solve and you'll get hit with the spell.

I think the way it works is that you fight some mooks and then a boss, and each boss has a new spell they can cast against you.

But you can cast any spell you've seen used against you, so like you start with merely FIREBALL but the first boss hits you with HIGH JUMP, and now you can use that ability out of battle, cause it's a metroidvania of course, and now new areas are accessible.

But bosses can use "forbidden" spells against you, and they do it by typing words you can't.

Like the viking boss hits you with a OÄNDLIG FJÄRIL and you don't have that letter.

(later you can upgrade your keyboard to get access to some forbidden letters, but at great cost: you must sacrifice a letter to gain it, and you don't get to pick which letter the keyboard surgeon will take)

[mywordsolutionedu-blog]

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[codingprolab]

EEN 218 Lab #6 A Movie Repository II: Movies, Playlists, and Search Trees

In this assignment, you are going to complete your movie library, using Lab 4 as a starting point. You need to provide a report that shows (20pts): 1. Your class designs 2. The algorithms used a. This should be in pseudo-code or flowcharts, not just the code you ended up writing 3. Compiling instructions 4. Sample runs (screenshots are fine) Things to have (80pts): Part 1: Binary Search Tree for…

[eikooowie]

Let's forge a backstory for your Digimon Universe: Appli Monsters OC, Atena Meizen, and her Buddy Appmon, highlighting her German-American heritage!

Atena Meizen (アテナ 明善)

* Name Meaning: Her given name, Atena, evokes the Greek goddess of wisdom and strategic warfare, hinting at an intelligent and perhaps determined nature. Her family name, Meizen (明善), can be interpreted from Japanese as "bright good" or "clear virtue," suggesting a strong moral compass. The combination of a Greek first name and a Japanese-sounding last name playfully hints at a broader global connection, which aligns with her mixed heritage.

* Age: Around 13-14 years old, fitting the typical protagonist age range.

* Appearance: Atena's appearance could subtly blend her German and American roots. She might have the fair complexion and perhaps striking eye color common in some German lineages, combined with a more athletic build or a certain casualness in her style often seen in American fashion. Her hair color and texture could be a unique blend of both sides.

Backstory:

Atena was born in a bustling American city with a significant German-American community. Her mother is a German immigrant who works as a software engineer, known for her logical thinking and meticulous approach. Her father is an American history professor, passionate about storytelling and understanding different cultures.

Growing up, Atena was exposed to both the structured efficiency and rich traditions of her German heritage and the more laid-back, individualistic aspects of American culture. She learned to speak German fluently, enjoyed traditional German foods (especially her Oma's Apfelstrudel!), and participated in German cultural events. Simultaneously, she embraced American sports, enjoyed exploring the diverse landscapes of her home country, and developed a sharp, analytical mind.

This dual upbringing instilled in Atena a unique blend of logic and curiosity. She appreciates structure and planning but also has a strong desire to understand the "why" behind things. She can be both direct and thoughtful, sometimes surprising people with her insightful observations.

Her interest in the digital world stemmed from both her mother's influence in technology and her own innate curiosity about how things work. She wasn't just a passive user; she enjoyed tinkering with software and understanding the underlying systems.

Atena's encounter with her Buddy Appmon, likely happened when she was facing a complex problem or trying to organize a large amount of information. Perhaps she was feeling overwhelmed by choices or struggling to see a clear path forward. Her Buddy Appmon, whose name and App Genre we'll define next, manifested in her laptop or tablet, drawn to her need for clarity and order.

Let's define Atena's Buddy Appmon:

Given Atena's analytical and organized nature, and the potential for her name to subtly hint at strategy, a fitting Appmon could be:

* Name: Logimon (ロジモン) - Combining "Logic" and "Mon(ster)." Alternatively, Strategimon (ストラテジモン) - directly referencing "Strategy." Let's go with Logimon.

* App Genre: System or Utility (representing logic, organization, and problem-solving).

* Appearance: Logimon might have a design that incorporates geometric shapes, interlocking parts, or visual representations of flowcharts and algorithms. It could have a calm and collected appearance, with perhaps glowing lines or patterns that suggest data pathways.

* Personality: Logimon would likely be highly logical, analytical, and focused on efficiency. It might offer Atena clear and structured solutions to problems, sometimes in a very direct manner. It might not always grasp emotional nuances but would be fiercely loyal and dedicated to Atena's goals.

Their Partnership:

Atena and Logimon's initial interactions might involve Atena appreciating Logimon's straightforward approach while sometimes needing to remind it of the human element in situations. Logimon would learn to factor in Atena's broader understanding of the world beyond pure logic.

Atena's mixed heritage could influence their partnership in interesting ways. Her German side might appreciate Logimon's efficiency and structured thinking, while her American side might encourage her to explore more creative and unconventional solutions alongside Logimon's logical ones. Her ability to see things from different perspectives could help her and Logimon find innovative approaches to challenges.

Potential Story Arcs:

* Atena and Logimon might encounter Appli Monsters that represent chaos, misinformation, or illogical processes. Their journey could involve bringing order to these digital disruptions using their combined analytical skills.

* Atena's understanding of different cultural approaches to problem-solving (perhaps influenced by her exposure to both German and American methods) could give her a unique advantage in understanding the motivations and strategies of other Appli Monsters or even human antagonists.

* Atena's personal growth could involve learning to balance her logical side with her emotions and understanding that not everything can be solved with pure reason. Logimon might also learn to appreciate the value of human intuition and creativity.

* They might encounter situations where different systems or networks clash, and Atena's ability to understand and bridge these divides, influenced by her own bicultural experience, could be crucial.

This provides a detailed starting point for Atena Meizen and Logimon! Feel free to ask if you'd like to delve deeper into any of these aspects or explore other avenues for their backstory.

[aismallard]

The issue is "AI" is a branding term, largely riding off of science fiction talking about futuristic more-intuitive tooling. There is not a clear definition for what it is because it's not a technical term.

There are specific techniques and systems like LLMs (large language models) and diffusion models to generate images and the like, but it's not cleanly separated from other technology, that's absolutely true. It's also that predecessor systems also scraped training material without consent.

The primary difference here is in scale, in the sense of the quality of generated outputs being good enough that spambots and techbros and whoever use it, and in the sense that the general public is aware of these tools and they're not just used by the more technical, which have combined to create a new revolution in shitty practices.

Anyways I still maintain that the use of "AI" (and "algorithm") as general terms meant to apply this specific kind of thing is basically an exercise in the public attempting to understand the harm from these shitty practices but only being given branding material to understand what this shit even is.

Like, whether something is "AI", in the sense of "artificial intelligence", is very subjective. Is Siri "AI"? Is Eliza "AI"? Is a machine-learning model that assists with, idk, color correction "AI"? What about a conventional procedural algorithm with no data training?

Remember, a lot of companies "use AI" but it could just be they're calling systems they're already using "AI" to make investors happy, or on the other end that they're feeding into the ChatGPT API for no reason! What they mean is intentionally unclear.

And the other thing too is "algorithm" is used in the same kind of way. I actually differentiate between capital-A "Algorithms" and lowercase-a algorithms.

The latter is simply the computer science definition, an algorithm is a procedure. Sorting names in a phonebook uses a sorting algorithm. A flowchart is an algorithm. A recipe is an algorithm.

The other is the use usually found in the media and less technical discussions, where they use capital-A "Algorithm" to refer to shitty profit-oriented blackbox systems, usually some kind of content recommendation or rating system. Because I think these things are deserving of criticism I'm fine making a sub-definition for them to neatly separate the concepts.

My overall point is that language in describing these shitty practices is important, but also very difficult because the primary drivers of the terminology and language here are the marketeers and capitalists trying to profit off this manufactured "boom".

I just have to share this beautiful thread on twitter about AI and Nightshade. AI bros can suck it.

[aitoolswhitehattoolbox]

Staff Engineer Software

Job Description:JOB SUMMARY:Software engineers apply the principles of software engineering to the design and development of software systems, features and tools which enable Fanatics businesses, platforms, and operations. SWE employ the use of diagrams, flowcharts, development of complex algorithms and software code in the development process.GENERAL DUTIES & RESPONSIBILITIES: Partner with…

[renatoferreiradasilva]

Vector Geometry Applied to the Study of Oriented Areas in Parallelograms

Author: Renato Ferreira da Silva

Tools: ChatGPT and DeepSeek

1. Introduction

Vector geometry is a fundamental tool for solving complex problems in an elegant and systematic way, especially in contexts involving oriented areas and proportional relationships. This article explores a classical problem in vector geometry: calculating the oriented area of a quadrilateral (MPNQ) within a parallelogram (ABCD), defined by vectors (\mathbf{u}) and (\mathbf{v}). In addition to the mathematical solution, we discuss its pedagogical relevance and applications in fields such as computer graphics and financial education, integrating insights from recent research.

2. Mathematical Context

Problem Definition

In the parallelogram (ABCD), the points (M), (N), (P), and (Q) are defined as:

(M): divides (AB) in a (2:1) ratio ((\vec{AM} = \frac{2}{3}\mathbf{u}));

(N): located on (BC) such that (\vec{BN} = \frac{5}{8}\mathbf{v});

(P): midpoint of (AD);

(Q): intersection of the diagonals (vector average of (\mathbf{u}) and (\mathbf{v})).

The oriented area of the parallelogram is given by (\mathbf{u} \times \mathbf{v} = 864), and the goal is to compute the area of (MPNQ).

3. Methodology and Calculation

Vector Coordinates

Using a coordinate system with origin at (A(0,0)):

(M = \left(\frac{2}{3}u_1, \frac{2}{3}u_2\right)),

(P = \left(\frac{v_1}{2}, \frac{v_2}{2}\right)),

(N = \left(u_1 + \frac{5}{8}v_1, u_2 + \frac{5}{8}v_2\right)),

(Q = \left(\frac{u_1 + v_1}{2}, \frac{u_2 + v_2}{2}\right)).

Oriented Area via Vector Product

The oriented area of (MPNQ) is computed using the formula: [\text{Area} = \frac{1}{2} \left( M \times P + P \times N + N \times Q + Q \times M \right),] where (\times) denotes the determinant (the 2D cross product).

Partial Results:

(M \times P = \frac{1}{3}(\mathbf{u} \times \mathbf{v})),

(P \times N = -\frac{1}{2}(\mathbf{u} \times \mathbf{v})),

(N \times Q = \frac{3}{16}(\mathbf{u} \times \mathbf{v})),

(Q \times M = -\frac{1}{3}(\mathbf{u} \times \mathbf{v})).

Total Sum: [\frac{1}{3} - \frac{1}{2} + \frac{3}{16} - \frac{1}{3} = -\frac{5}{16},] [\text{Final Area} = \frac{1}{2} \cdot \left(-\frac{5}{16}\right) \cdot 864 = \boxed{-135}.]

4. Discussion and Applications

Proportional Invariance

The ratio (\frac{5}{32}) between the areas of (MPNQ) and (ABCD) is constant, independent of (\mathbf{u}) and (\mathbf{v}). This invariance stems from the fact that the point positions are defined by fixed proportions (e.g., (\frac{2}{3}), (\frac{5}{8})), illustrating the robustness of vector-based approaches to geometric problems.

Pedagogical Relevance

The integration of vectors into high school education, as proposed by Assemany (webpage 1), facilitates the understanding of concepts like translations, rotations, and oriented areas. The use of flowcharts connecting content (e.g., trigonometry, affine functions) reinforces the importance of a unified mathematical approach.

Applications in Computer Graphics

Vectors and matrices are essential for 3D modeling, geometric transformations, and rasterization. For example, the graphics pipeline (application → geometry → rasterization) relies on vector operations to render complex objects. In this context, oriented area calculations can assist in collision detection and optimization of rendering algorithms.

Connection to Financial Education

The analysis of oriented areas can be adapted into risk metrics for financial charts, such as relationships between price and moving averages. The proportional invariance (\frac{5}{32}) may serve as a filter to identify market patterns and trend shifts.

5. Conclusion

The calculation of the oriented area of (MPNQ) illustrates the power of vector geometry in solving structural problems. The constant ratio (\frac{5}{32}) emphasizes the mathematical elegance of proportion-based methods, with applications extending beyond the classroom to fields such as computer graphics and financial analysis. The integration of innovative pedagogical methodologies, like those proposed by Assemany, and the use of mobile technologies, highlights the need to modernize mathematics education to prepare students for multidisciplinary challenges.

[skellish]

And it's like. Thats just it, you have to doubt everyone and play detective all the time. Every interaction I have with a neurotypical, I have to keep my Internal Flowchart of Normal Words and Manerisms in my head at all times, and be on constant lookout for any little sign in someone's face, body language, words, tone, etc, just to have a "normal" conversation.

Some are easier than others. Ones where you can just copy and paste your pre-made phrases and responses into the template of your interaction usually go pretty well, and I would seem not weird, just it's exhausting. Always running a probability generator in your head and trying to match the same social cues as your peers. What comes naturally to them, I've had to learn through trial and error my whole life. It just makes being genuine so difficult because you have to filter yourself through this screen so much that what comes out is just. Artifical. To the point where it's hard sometimes to find where the Social Algorithm ends and your actual personality begins.

Anyway i love laois so much. He's some of the best autistic rep I've seen in a while, and I envy his passion and fearlessness in displaying who he actually is, despite the hurt that it brings him.

Thinking about a certain scene in Dungeon Meshi that completely encapsulates the Autistic experience of making friends as an adult and how hard it is to try and navigate it without ending up getting hurt.

Like IDK about y'all, but this is a common problem ALOT of Autistic Adults face when trying to make friends with other people, because unlike children who aren't good at keeping their opinions to themselves, Adults ARE. In society, we're even encouraged to "keep the peace" "be polite" and etc, which commonly leads to awful scenarios as shown above when Laois finds out his buddy has come to resent who Laois is without actually telling him. All too often the friends that we love to hang out with, people that we're so happy to spend time with, don't feel the same way and in many cases, come to blame us for our social cues or lack thereof.

And when/if we do eventually find out how our friend feels, Dungeon Meshi hits us with another painful panel of how that usually ends up playing out.

It's hard for Adults with Autism to make friends, and even harder to maintain them because alot of the ways Neurotypicals tell other Neurotypicals that they don't like a certain behavior is by quietly disengaging. Whether that involves having one sentence answers, going quiet, or having a certain tone in their voice, all those things signal annoyance or disapproval, but for the Neurodivergents, those subtle cues are completely missed.

And yet when we inevitably discover we DID do something, it is natural to ask "well why didn't you tell me?" because in our minds, it should've been the next step in the equation. However for the Neurotypicals, that's NOT something to bring up. Its important to be SUBTLE about the issue at hand and rely on signals to tell the other person. Blame is placed on us for not noticing the "obvious" signs of disapproval rather than the idea of talking it out as such things are uncomfortable and harder to do. Alot of the time what ends up happening is resentment due to the idea that it was "obvious" and the fact one didn't notice indicates a deliberate ignorance rather than a complete unawareness. It ends up calling into question our quality as a person and our sincerity. We get called "fake" or "malicious" or even "stupid" for failing social cues rather than questioning the decision to be indirect and vague.

For a manga about exploring the dungeon, it seems that the artist would rather explore very real and prevalent dynamics in society with the adventuring premise as a backdrop. I felt VERY seen in these panels, and many others, because it happens so suddenly and dare I say it, plainly. There's no dramatic build-up or spectacle made and in essence, it just Happens.

I think that's what makes the scene hit even harder. It seemingly comes out of nowhere for Laois, like how it always comes out of nowhere for alot of people, and it's never a dramatic twist either. It's always mundane and hurtful. A sudden unforeseen bump in the road that ends up calling into question one's entire friendship with someone and consequent other friendships. It asks "what if other friends feel the same. What if the people that I really like actually hate me and I don't know it?" Or at least that's what I came away with after reading the chapter. I've been where Laois was and the only reason I'm not there now is because I lost the naivete I had and doubt everyone else's sincerity.

[pastirc]

Staggering omission of women's crucial contributions to computer programming and tech in general. "In 1945, six women pulled off a computing miracle. They programmed the world’s first computer—with no manuals, no training. Then, a SINGLE assumption erased them from tech history for decades. The story of how ONE photo nearly deleted computing’s female founders.

"Kathy Kleiman, a young programmer, found old photos of women standing beside ENIAC—the first general-purpose computer. When she asked who they were, curators said: “Probably just models”... But Kleiman had a feeling they were something more:

"They weren’t models. They were the world’s first programmers. [After Ada Lovelace, that is.] First, they were hired as “human computers” to calculate missile trajectories during WWII. Then chosen for a top-secret project unlike anything before:

"Program ENIAC—a machine the world had never seen. It was 8 feet tall, 80 feet long, and weighed over 60,000 pounds. The engineers built the hardware... But someone had to figure out how to make it do anything:

"That job fell to six women: Betty Holberton, Jean Bartik, Kay McNulty, Ruth Teitelbaum, Marlyn Meltzer, and Frances Spence. But there was a problem... They weren’t even allowed to touch the machine: Security restrictions kept them out of the ENIAC lab. They had to write programs using only blueprints and logic diagrams. No manuals. No programming languages... So how do you code something no one’s ever coded before?

" By inventing the process from scratch. They built algorithms, flowcharts, and step-by-step routines—on paper. Then, once granted access, they programmed ENIAC by physically rewiring it. And that’s where things got even harder: There was no keyboard. Programming meant plugging thousands of cables into the right configuration—by hand. It was almost impossible to program. But they pulled it off anyway:

"On February 14, 1946, ENIAC was unveiled to the public. It could do 5,000 calculations per second—1,000× faster than anything before. It made headlines across the country... But the real story was missing:

"The six women who made ENIAC work weren’t invited to the demo. Photos of the machine appeared in newspapers... But the people who programmed it? Not even named. The credit went to the engineers who built the hardware. Why were the programmers ignored? Because back then, programming wasn’t seen as valuable work... And that perception had lasting consequences:

" Since women were doing it, people assumed it was secretarial—just “wiring” or “filing.” Even though it required complex math and problem-solving... Soon, the field of programming would be rewritten entirely: As computing grew in importance, men took over. The image of the “male genius coder” replaced the women who pioneered the field.

"But what happened to the ENIAC six after ENIAC? They kept building. Betty Holberton wrote the first software application.

Jean Bartik worked on memory systems.

Kay McNulty helped invent reusable code, or “subroutines”...

So why don’t we learn about them in school? Because for decades, their names were forgotten. It wasn’t until the 1980s when Kleiman found them and recorded their stories. By the time they were publicly honored in 1997... Most were in their seventies.

" In that gap, tech culture had completely changed. A field launched by women had become a boys’ club... But what if we hadn’t erased the founders? Women have always been a part of the history and story of computing.

"And it's still important to make sure computer science education is accessible to all students today. So how do we build a future that reflects that? By making stories like ENIAC’s part of the canon—not the footnotes.

"By teaching that the first coders weren’t just women—they were visionaries. By showing every girl in tech: you’re not an exception... You’re part of a legacy... "

Look at this link to see video clips. I'll post a talk by Kathy Kleiman who rediscovered the work these women did, which had been totally buried by the 80s. She went to the 40th anniversary of ENIAC looking for the women in those pictures, found them, and uncovered the whole story.