Info about while True: learn():

Official game description:
**while True: learn()** is a puzzle/simulation game about even more puzzling stuff: machine learning, neural networks, big data and AI. But most importantly, it’s about understanding your cat.  
In this game, you play as a coder who accidentally found out that their cat is extremely good at coding, but not as good at speaking human language. Now this coder (it’s you!) must learn all there is to know about machine learning and use visual programming to build a cat-to-human speech recognition system.  
This game fits best for...  
\- People who want to know more about how machine learning and related technologies work  
\- Parents and teachers who are looking for a fun and easy way to make an intro to logical thinking, programming, and technologies for kids  
\- Programmers who want to learn new concepts that they can apply to their own coding  
\- Those who want to play games and not feel guilty about ‘wasting their time’ (although we believe you shouldn’t feel guilty at all while playing games!)  
\- Players who like to keep their brains busy and working in different ways, while still having fun  
\- Gamers looking to improve their problem-solving skills and feel immense sense of satisfaction and achievement that comes along with it  
\- People who like smart cats
**Learn how machine learning works in real life!**
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The game is loosely based on real-life machine learning technologies: from goofy Expert Systems to mighty Recurrent Neural Networks, capable of predicting the future. Don’t worry: it all plays out as a puzzle game. No coding experience required!
**Train yourself into a data science wizard!**
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Drag objects around your screen with a mouse! Connect them with lines (oh yeah)! Try. Fail. Optimize. Try again. Then press “Release” button and see that sweet pieces of data flow smoothly through your screen.
**Embrace an adventurous lifestyle of a machine learning specialist!**
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Designing a groundbreaking technology requires time, experience and money. That means you’ll have to work as a freelancer, with all the excitement that comes along with it. Receive emails! Accept contracts! Sit alone in a dark room for days without saying a single word! Socialize on forums! That’s what real data scientists do!
**Coding just got real!**
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Our quests are based on actual problems, solved by machine learning. This includes building a self-driving car (with your cat as a pilot). And if you really want to test your programming might, you can become a CTO of a startup: it’s your skills and your schemes against the savage laws of the market! Earn a fortune, flip off your bosses and become a tech guru… Or lose everything and crawl back to the doorstep of HR department: at least it was worth trying, right?
**Improve your gear, improve your life!**
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Once you ensure a stable cashflow, you’ll be able to buy yourself a bunch of fancy hardware to improve your performance. But it’s not just about the hardware! Buy yourself a new smartphone or a geeky figurine! Buy fancy outfits for your cat! Hell, you can even buy yourself an aloe!  
**Fun fact:** this is what machine learning specialists actually do. Now, you can become one of them (minus the money)! while True: learn() is the best game about being a data science specialist because no one else has been weird enough to make another one!

Release date: Jan 17, 2019

Categories: Puzzle Solving, Programming Logic, Educational Game, Node-based Architecture, Simulation, Grid-based Logic, Research and Discovery, Optimization Game


- Hardware Profile: No data
Feature extractions:
- Community Price: No data
- Playtime Metrics: No data
- Time-to-fun: No data
- Player Archetypes: No data


Below are summaries of things people say about the game per category.
Each point is assigned a weight that represents how often it is mentioned across all reviews.
What players like:
- Effective machine learning education (weight 0.85): The game is highly regarded for teaching machine learning and AI concepts in an accessible, beginner-friendly way. It simplifies complex topics and provides real-world applications, making it valuable for learners.
- Engaging puzzle mechanics (weight 0.83): Players consistently praise the puzzle gameplay as enjoyable, challenging, and varied. The design encourages optimization and creative problem-solving, making it satisfying and fun for both beginners and experienced players.
- Beginner-friendly learning (weight 0.72): The game is highly accessible to non-experts and beginners, with gradual difficulty progression and tutorials that help players grasp complex concepts without feeling overwhelmed.
- Relaxing and stress-free (weight 0.71): The gameplay is described as peaceful, calming, and satisfying, helping players unwind while still being engaging. The music and visuals contribute to a soft, unobtrusive atmosphere.
- Strong educational resources (weight 0.61): The game provides extensive educational materials, including articles, videos, and links to real-world resources. This reinforces learning and offers opportunities for deeper exploration of concepts.
- Charming cat-themed design (weight 0.23): The cat and coffee theme adds significant charm and humor, making the game more engaging and appealing, especially to cat lovers. The narrative and aesthetics enhance the overall experience.
- Realistic and practical concepts (weight 0.12): The game incorporates realistic scenarios and high-level concepts, making it relevant to real-world applications like data science and machine learning. This adds depth and practical value.

Common complaints:
- Poor puzzle design and guidance (weight 0.88): Players criticize the lack of hints, unclear mechanics, and inconsistent difficulty, leading to frustration. Many resort to trial-and-error due to vague instructions or missing feedback on mistakes.
- Repetitive and unengaging gameplay (weight 0.78): The gameplay loop is described as monotonous, with puzzles feeling repetitive or overly simplistic. Players lose interest due to minimal variation and lack of progression in complexity.
- Misleading educational claims (weight 0.66): The game fails to deliver on its promise of teaching programming or machine learning. Concepts are either too basic, disconnected from gameplay, or misrepresented, offering no meaningful learning value.
- Frustrating difficulty balance (weight 0.54): The game’s difficulty is either too low for experienced players or too high for beginners, with sudden spikes that alienate casual players. Lack of skip options exacerbates frustration.
- Unintuitive UI and mechanics (weight 0.14): The user interface is awkward, unreadable, or unintuitive, particularly with sliders and other interactive elements. Mechanics like reinforcement learning are poorly explained or obscure.
- Buggy and broken mechanics (weight 0.07): Technical issues and flawed mechanics undermine the gameplay experience. Some levels or systems are described as poorly executed or fundamentally broken.
- Limited replayability (weight 0.06): Players cannot replay or retry certain challenges (e.g., startups) without restarting the game, reducing long-term engagement and flexibility.

Gameplay feedback:
- Programming-themed puzzle mechanics (weight 0.99): The game centers on puzzles that incorporate programming concepts like node-based logic, optimization, and pattern matching. Players solve challenges using visual representations of algorithms, filters, and data routing.
- Educational machine learning focus (weight 0.82): The game teaches machine learning and AI concepts (e.g., CNNs, RNNs, decision trees) through puzzles and educational content. It gamifies theoretical knowledge, making it accessible to beginners.
- Gold medal optimization system (weight 0.68): Players are rewarded with bronze/silver/gold medals based on solution efficiency. Gold medals often require advanced optimization or creative problem-solving, adding replayability.
- Balanced mandatory/optional content (weight 0.53): The game offers a mix of mandatory (~40%) and optional puzzles, allowing players to choose their difficulty level while ensuring core concepts are covered.
- Data sorting and classification (weight 0.28): Core gameplay involves sorting shapes, colors, and data using logical operators. Puzzles emphasize classification, efficiency, and accuracy, often with constraints like speed or resource limits.
- Progression and upgrade mechanics (weight 0.16): The game features a progression system with unlockable upgrades (e.g., faster operators, speed boosts) to enhance puzzle-solving capabilities. This encourages long-term engagement.
- Parallel computing and logic tasks (weight 0.15): Advanced puzzles introduce parallel computing concepts, requiring players to manage multiple data flows or components simultaneously for optimal solutions.
- Story-driven AI learning narrative (weight 0.12): A unique storyline frames the gameplay, where players learn machine learning to communicate with a pet (e.g., decoding cat language). This adds context to the educational content.
- Customizable node-based puzzles (weight 0.07): Players can design custom nodes or encounter randomized elements in puzzles, adding variety and complexity to problem-solving scenarios.

Performance notes:
- Screen blinking problems (weight 0.03): Multiple users reported persistent screen blinking or flickering issues during gameplay, which disrupts the experience. This appears to be a graphical or rendering bug.
- Linux version stability confirmed (weight 0.03): Several players on specified Linux hardware configurations reported no technical issues, indicating good compatibility and performance for the native Linux build.

Recommendations:
- Not ideal for learning ML/programming (weight 0.46): Many reviews argue the game fails to teach practical machine learning or programming concepts, suggesting alternatives like online courses, tutorials, or other games (e.g., 'Human Resource Machine').
- Better alternatives exist (weight 0.34): Reviewers often compare it unfavorably to other puzzle or programming games (e.g., Zachtronics, 'Factorio', 'Shenzhen I/O'), citing deeper mechanics or more engaging gameplay elsewhere.
- Mixed recommendations (weight 0.29): Opinions are polarized: some highly recommend it for niche audiences (e.g., educators, cat lovers), while others advise avoiding it due to poor value or mechanics.
- Low-cost appeal (weight 0.05): Several reviews suggest the game is worth buying only when on sale, given its narrow focus and limited replayability.
- Educational improvements suggested (weight 0.05): Feedback includes requests for better in-game explanations (e.g., decision trees) or more practical applications of knowledge to enhance learning.

Other player notes:
- External AI learning links (weight 0.05): Multiple reviews mention external links to AI-related tools and educational resources, suggesting the game integrates or promotes supplementary learning materials. This may appeal to users seeking additional knowledge but could also distract from core gameplay.
- Superior to Cisco Packet Tracer (weight 0.03): Players describe the game as an improvement over Cisco Packet Tracer, a professional networking simulation tool. This suggests strong technical or educational value, particularly for users familiar with such software.
- Cats as a key feature (weight 0.03): Several players highlight cats as a notable or memorable aspect of the game, indicating their presence is either a positive or quirky design choice. This could enhance charm but may not align with all players' expectations.
- Academic risks of gameplay (weight 0.03): One review shares a personal story about negative academic consequences from playing similar games, warning others about potential distractions. This reflects a niche concern but may resonate with students or educators.

Emotions:
- Frustration (weight 0.22): Players experience frustration due to repetitive, confusing, or overly difficult puzzle mechanics, including arbitrary solutions for gold medals, lack of guidance, and sudden difficulty spikes. Bugs, cumbersome UI, and limitations in tools for optimization further exacerbate the issue, making progression feel punishing and unintuitive. The gameplay loop is often described as tedious, with unclear objectives and unrealistic or broken mechanics.
- Disappointment (weight 0.17): The game fails to meet expectations as an educational or puzzle experience, with players noting oversimplified or misrepresented AI/ML concepts, lack of depth, and repetitive gameplay. The gold medal system and predefined solutions undermine creativity, while the educational value is perceived as shallow or poorly integrated. Many feel the game does not deliver on its promises, leaving them unengaged or misled by its marketing.
- Enjoyment (weight 0.12): Players enjoy the game's engaging and intuitive puzzle-solving mechanics, particularly in the early stages, where the gameplay is described as fun, rewarding, and accessible. The cute aesthetic, humor, and educational aspects—such as teaching programming logic or CS concepts—contribute to a positive experience, especially for those new to the topics or playing with family.
- Satisfaction (weight 0.08): Satisfaction stems from the game's educational value and well-designed puzzles, which provide a clear and progressive learning curve. Players appreciate solving challenges through trial and error, discovering efficient solutions, and gaining new knowledge, even as experienced programmers. The balance between fun and education, along with helpful tutorials, enhances the overall experience.
- Amusement (weight 0.07): The game's humor, particularly its cat-themed elements, quirky NPCs, and satirical take on software development, amuses players. Creative details like hardware naming, job offer jokes, and playful mechanics (e.g., cats judging the player) add a lighthearted and entertaining layer to the gameplay.
- Appreciation (weight 0.04): Players appreciate the game's educational resources, such as articles, videos, and clear explanations of complex topics like machine learning. The developer's effort in creating a unique and thoughtful design, along with the game's role in popularizing AI/ML concepts, is widely recognized and valued.
- Curiosity (weight 0.03): The game sparks curiosity through its exploration of machine learning, programming history, and neural networks. Players are interested in learning more about these topics, engaging with additional resources, or progressing further to uncover new content, despite some uncertainty about the depth of the educational material.
- Confusion (weight 0.02): Confusion arises from unclear puzzle mechanics, lack of feedback, and poorly explained tutorials, particularly in later stages or advanced topics like reinforcement learning. Players struggle to understand the game's objectives, target audience, or how certain mechanics relate to real-world concepts, leading to frustration.
- Excitement (weight 0.02): The game excites players with its unique blend of puzzles and programming education, offering an immersive and engaging learning experience. The educational value, combined with effective teaching methods, makes it an appealing tool for both beginners and those looking to reinforce their knowledge.
- Nostalgia (weight 0.01): Nostalgic feelings are triggered by references to past experiences, such as StarCraft, GameMaker, or personal memories of learning programming. These elements resonate with players who have prior connections to the themes or tools featured in the game.
- Enthusiasm (weight 0.01): Players express enthusiasm for the game's learning opportunities, engaging gameplay, and the sense of growth it provides. The frequent restarts and progressive difficulty curve are seen as positive challenges, fostering a sense of accomplishment and motivation to continue.
- Surprise (weight 0.01): The game surprises players by exceeding expectations in terms of entertainment, depth, or educational value. Some note that it is more engaging or extensive than anticipated, offering a refreshing take on programming or puzzle games.
- Positive (weight 0.01): Players describe the game as interesting, educational, and fun, highlighting its ability to help with quick learning or mastery of programming concepts. The overall experience is seen as delightful and engaging, contributing to a positive reception.
- Approval (weight 0.01): The game receives approval for its accessibility to beginners, focus on logical thinking over syntax, and clear explanations of programming concepts. Players appreciate its suitability for those new to machine learning or coding, making it a recommended starting point.
- Boredom (weight 0.01): Boredom stems from repetitive gameplay, lack of variety in puzzles, and slow progression, particularly in the early hours. Players find the experience unengaging or monotonous, failing to hold their interest over time.
- Engagement (weight 0.01): The game engages players with its brain-teasing puzzles, which require creativity, time, and problem-solving skills. The rewarding nature of overcoming challenges and the dynamic results of solutions keep players invested in the gameplay.
- Love (weight 0.01): Players express strong affection for the game, praising its approach to teaching complex concepts through gamification, enjoyable mechanics, and overall design. The experience resonates deeply, fostering a sense of admiration for the developers' efforts.
- Anticipation (weight 0.01): Anticipation is driven by the potential for future use, such as in educational settings, or excitement about upcoming content in the game. Players look forward to progressing further or exploring additional features.
- Affection (weight 0.01): Affection is directed toward the game's cute UI, puzzle mechanics, or thematic elements like cats. Players develop a fondness for these aspects, enhancing their emotional connection to the experience.
- Recommendation (weight 0.01): Players recommend the game for its suitability as a simple puzzle experience or its educational value. Some encourage others to purchase it, highlighting its strengths in accessibility, fun, or learning potential.}