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Can I Teach Myself to Play the Piano with AI?

Some people might be skeptical if they could teach themselves how to play piano with AI. MuseFlow makes it easy for you by having artificial intelligence and machine learning serve the process of learning in two unique ways - music generation AI, and pattern recognition machine learning. It does the work for you to make learning a lot more fun, effective, and efficient. It does this by incorporating AI into the core of its pedagogy. The folks over at MuseFlow are making efforts to improve their algorithms every single day. Let’s take a deeper dive into this, and how artificial intelligence and machine learning are improving the way we learn piano.

Try MuseFlow today. It's free for 7 days!

Music Generation AI

There are few music apps out there that have generative AI imbedded within them. MuseFlow’s approach to learning involves giving you music you’ve never seen before, that never repeats, and is at your level of skill. You can choose from a myriad of levels on the level roadmap. Unit one starts with just one note, three rhythms, and two hands, and ends with two octaves (14 notes), four rhythms, and two hands. But how does MuseFlow give you music that never repeats? Surely that would be impossible with the amount of music that would need to be written!

MuseFlow's level roadmap to show that you can choose where to start given your experience level. All this in service of learning how to play piano with AI.
You choose where to start. With MuseFlow’s roadmap, you can find music that’s at your skill level and dive right in there without having to start from a specific spot in the curriculum.

The team over at MuseFlow is constantly improving its music generation artificial intelligence  algorithm so that it gives you the best quality sheet music as a constant stream until you pass the level. By using generative AI for sheet music, MuseFlow’s team sets the parameters for each level, then unleashes the artificial intelligence to start generating music for you to play!

A pic of music being generated by MuseFlow's AI. This is what you would play!
Music continues to flow until you get 95% accuracy for four lines of music. At that point, you pass the level!

MuseFlow’s team is constantly training the AI with what they call, “Phrase Tinder”. If a phrase of music passes the rigorous tests of it sounding good enough to play and is exercising the new skill of a certain level, they swipe right. If a phrase is not good enough to play or isn’t useful, they swipe left. This method of training allows the computer to understand what is good and what is bad so it can create new and original pieces that fit within the guidelines of the curriculum, and are fun to play!

A banner that says "learn piano, find your flow." with a link to signup for MuseFlow to learn piano!

Pattern Recognition AI & Machine Learning

As you play, MuseFlow can see what you’re playing in relation to the music that’s on the screen. If you’re consistently messing up a note or rhythm, or even a series of notes or series of rhythms, it will gently give you more phrases of music that have those patterns in them. It can even recognize the intersection of rhythms and notes! It does this all in the background so your flow isn’t interrupted. You as the student wont even know it’s going on.

An image of a young woman sitting at a piano with MuseFlow in front of her and she's smiling using MuseFlow's AL to learn how to play piano.
As you play, MuseFlow is listening to you and adjusting the music to suit your needs. You wont even know it’s happening!

This teaching method enables MuseFlow to monitor each micro-skill you learn, such as individual notes and rhythms, along with their various combinations. MuseFlow adjusts the music and increases exposure if it detects that your proficiency in any specific micro-skill is lower than the others. Once you effortlessly and unconsciously bring that micro-skill up to standard with the rest, MuseFlow reduces its exposure back down to parity with the other micro-skills it is tracking.

One of MuseFlow's readouts that show your progress as you learn to play the piano using MuseFlow's artificial intelligence. It shows the current level you're on, how much time you practiced this week in minutes, and how long it took you to play each level this week.
Soon, you’ll even be able to see a readout of your practice sessions! How long you played each level, and what micro-skills are needing work. But again, you won’t have to choose which to work on. MuseFlow knows and will adjust with that info in mind.

Conclusion

Unlike traditional music education environments and methods, the folks at MuseFlow, Inc. are committed to creating a safe, reliable space for you to learn and grow without the outside pressures of  anyone looking over your shoulder. As students, we need to feel like we can fail without any judgment. MuseFlow inspires you to learn, motivates you to learn, all with artificial intelligence and machine learning as assistants in the background, listening and adjusting the sheet music to suit your needs without any judgement. MuseFlow answers the question “can I teach myself how to play piano with AI” with a resounding YES! With its pattern recognition algorithms and music generation, MuseFlow’s AI is set to revolutionize music education for the better, and become the forerunner in the industry as the best new way to learn piano.

Check out MuseFlow for yourself for FREE!

Online Piano Lessons for Beginners: 4 Reasons Why MuseFlow is the Best Software

Do you want to learn piano but you're not sure where to start? That's ok, most people in the beginning feel this way. Finding the right method can be an overwhelming and hard decision. If you're looking for the best and most engaging online piano lessons for beginners, MuseFlow is the perfect solution. We listed 4 quick reasons why the new app stands out as the best software to start your piano journey.

Try the 7-day free trial right now! 

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1. Achieving Flow State - More Important Than you Think

MuseFlow’s unique approach to learning is purposely made to help you achieve a flow state—an optimal psychological state for learning. You have probably been there before, where you're fully immersed in an activity - and you even lose track of time... Achieving flow state is crucial for making learning both enjoyable & efficient. MuseFlow, Inc., The software company based out of California, has created an app that tailors each lesson to your skill level. This is to make sure that the material is challenging enough to keep you engaged BUT not so difficult that you become frustrated. This is really important for you to want to keep learning!

This balance is essential for beginners like you, who might otherwise feel overwhelmed. By keeping you in the flow state, MuseFlow makes practicing piano a really delightful experience. This in turn promotes consistency & faster learning. The app’s intelligent design adjusts to your progress, helping you stay in the zone (flow) and making your practice sessions both more productive and more fun.

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2. Expert Founders with Music Backgrounds

Another one of the key strengths of the innovative software is its team of founders. They all come from rich musical backgrounds. This is important, because the app is designed with a deep understanding of music education and the challenges beginners face. 

  • Steven Gizzi, Chief Executive Officer, is a composer and music educator with credits for clients like LEGO, Cartoon Network, DreamWorks, and Facebook Watch.
  • Patrick Boylan, Chief Operating Officer, is a multi-instrumentalist and producer specializing in musical theater and jazz piano.
  • Tucker Dean, Chief Data Scientist, is a data scientist with a knack for integrating machine learning with practical applications.
  • Steven Staley, Chief Technology Officer, is an infrastructure engineer with experience in building full stack applications.
  • Andrew Urbanowicz, Chief Information Officer, is a full stack developer with a background in mathematics and computational physics.

You can easily tell that their collective expertise makes sure that MuseFlow is not just another generic learning app but a comprehensive and well-thought-out tool specifically designed to help beginners learn piano.

This is a link for someone to click to sign up for MuseFlow! It allows them to start a free trial right here, and right now...

3. Free Online Piano Lessons for Beginners

A major advantage of MuseFlow is its accessibility. MuseFlow offers a 7-day free trial. This allows beginners to explore the app and experience its benefits without any financial commitment. This trial period is perfect for those who are just starting and want to test different learning methods. The reason for the free trial is, the team feels so confident you will love it!!

During the free trial, users can access various levels and tutorials. These provide a solid foundation in piano basics. This feature answers the question, "Are there online piano lessons for beginners?" with a definite YES. It's an excellent way for newcomers to get a feel for the app’s unique approach and see tangible progress in a short amount of time. It's really the most fun way to play piano!

4. Comprehensive Learning Tools to Make it Fun

The piano software for beginners, provides a comprehensive suite of learning tools that go further than traditional methods that you might have tried... Each lesson is accompanied by quick, engaging, interactive tutorials to ensure that beginners understand the necessary concepts & techniques before diving in. Real-time feedback is important. And it's done by advanced pattern recognition algorithms helps users identify and correct mistakes instantly. Of course, this is crucial for effective learning.

The app also features a gamified learning experience, turning each lesson into a fun and interactive game. Just like when you play a video game. By earning points and progressing through levels, students always say that they stay motivated & excited about their learning journey. This innovative new approach for beginners to learn piano makes the often tedious process of practicing piano a lot more rewarding.

Additionally, MuseFlow is continuously expanding its features. This is all done based on users feedback, so it keeps getting better and better with your input as the fuel! Future updates will include advanced curriculum options, enhanced practice modes for ear training, chord and scale exercises, and rhythm drills. A new repertoire library & a music theory section with personalized exercises will further make the learning experience the best out there. The goal is for students to develop a well-rounded skill set and be able to play the songs that they want to play. Anyone should be able to go to a piano and play their song of choice, an indescribable amazing feeling. With these amazing tools, it's by far the best piano learning app.

Conclusion

As discussed above, anyone that is searching for the best online piano lessons for beginners, MuseFlow is the top choice. Its unique ability to help learners achieve a flow state and the expertise of its music-savvy founders make it different from any other app. Additionally, the accessibility of free online piano lessons for beginners, and its comprehensive learning tools make it stand out!

MuseFlow’s new innovative approach to piano education really makes sure that beginners not only learn the fundamentals but also enjoy the process, keeping them motivated and eager to progress. The best software for online piano lessons for beginners...

Try it right now for FREE.

Best Piano Teaching App: 4 Reasons Why MuseFlow is the Best

If you're looking for the best piano teaching app to elevate your piano playing skills, then you have found it! Look no further than MuseFlow... With so many bad apps available, finding the right one can be tough. This new AI based app stands out as the best new software for pianists. Have a quick look at these 4 great reasons why its the best piano teaching app for you:

Try the 7-day free trial right now.

1. Experience the Power of AI for Personalized Learning

MuseFlow uses advanced AI technology to offer a real personalized learning experience. This is a must for any app in 2024. Unlike traditional piano lessons that follow a rigid complicated curriculum, this new technology adapts to your individual progress & learning style. This AI-driven personalization makes sure that each lesson is tailored to your current skill level... This provides just the right amount of challenge to keep you engaged without feeling overwhelmed. Because feeling overwhelmed will make you feel frustrated very soon after!

The app tracks your performance in real-time. It analyzes your strengths & identifying areas that need improvement. This intelligent feedback system helps you make steady progress. It also makes sure that you're always working on the skills that will most benefit your own unique development. By customizing each lesson to fit your needs, MuseFlow makes learning piano more fun & enjoyable than ever before! 

2. Smart Gamification to Keep You Motivated

MuseFlow turns piano learning into an engaging and interactive game. Just like your favorite video games that you can't stop playing. They do it through the innovative use of gamification. Have you heard of that? The piano app integrates gamification deeply into the learning process... Each new rhythm and note you learn is treated as a level you need to pass. So practice feels like a series of fun challenges. This works better than a frustrated teacher telling you what to do.

The app provides immediate feedback on your accuracy & tempo, with color-coded notes and a scoring system that makes each practice session really exciting. By transforming the learning process into a game, MuseFlow keeps you motivated and happy. The goal of this is to make you stick with your practice routine and it's easier than ever and more fun than ever to learn to play piano with AI. They know how easy it is to fall of your routine. This approach makes the question, "Is there a fun piano teaching app?" easy to answer with MuseFlow.

best-free-piano-teaching-app
A banner that says "learn piano. Find your flow." and some more text that says "click here to start your free trial". A user can click on this banner and be taken to the signup page of MuseFlow to start their learning journey!

3. Very User-Friendly Design

One of many standout features of MuseFlow is its smart and user-friendly design. What does that mean? Well, the app is designed to be both visually appealing and functional. This really creates an optimal learning environment. The intuitive layout makes it easy to navigate through your lessons, practice sessions, and progress tracking. The way it should be done.

The design philosophy of the California based app is focuses on making the learning experience as seamless and enjoyable as possible! The new app uses carefully chosen colors and a clean interface to help maintain your focus on playing, without unnecessary distractions. This thoughtful design enhances your ability to learn and enjoy the process, setting MuseFlow apart from other piano teaching apps. You can see it in more detail below and on the product page.

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4. Free Piano Teaching App  

MuseFlow offers a generous 7-day free trial. This allows you to explore its features without any financial commitment. Try it first and see if you love it. This trial period is perfect for anyone looking for a free piano teaching app to get started with. During the trial, you can access various lessons and interactive tutorials that provide a strong foundation in piano basics and you can get familiar with how it works.

A really great way to experience the app's unique approach & see real progress.. in a short amount of time. The trial also answers the question, "Are there free online piano lessons for beginners?" with a confident yes. By offering this above mentioned no-cost entry point, MuseFlow makes high-quality piano education accessible to EVERYONE.

best-piano-teaching-app-free-museflow

Conclusion

For anyone that is seeking the best piano teaching app, we're happy to say that MuseFlow is the best app! Its AI-driven personalized learning, engaging gamification, smart design, and free trial features make it the best choice for you. MuseFlow’s innovative approach to piano education ensures that students not only learn the fundamentals but also enjoy the process, keeping them motivated and excited to progress. It's like a video game that you keep wanting to get better at, the best part is while you advance you learn how to play the piano.

Learn to Play Piano with AI: 4 Reasons Why You Need MuseFlow

Are you curious about how to learn to play piano with AI? Then you're at the right spot! Technology is revolutionizing education, especially in 2024... and piano learning is no exception. MuseFlow is currently the best, offering a new innovative app that makes learning piano fun, efficient, and personalized. Check out these 4 reasons why this new app is the best to help you learn to play piano with AI!

Try it right now for free

learn-to-play-piano-with-ai

1. AI-Driven Personalization for Optimal Learning

People who are learning how to play piano LOVE MuseFlow. One of the main reasons why is the AI-driven personalization. This is amazing because it makes sure that your learning experience is tailored specifically to your unique needs. As you might know, traditional piano lessons follow a generic (and often boring) approach. The piano AI app uses advanced algorithms to analyze your progress and adjust the difficulty level accordingly. This means that whether you're a beginner struggling with basic notes or an advanced player refining complex pieces, the software adapts to keep you challenged but NOT overwhelmed. This keeps the learning experience fun and not frustrating.

This personalized should answer the question "Is there a way to learn to play piano with AI?" with a strong YES. The AI monitors your playing style, identifies areas for improvement, and provides custom exercises to help you progress faster than with conventional methods. This level of customization makes learning a lot faster and also more enjoyable.

learn-to-play-piano-with-ai-free

2. A User-Friendly Design - Making it Fun to Learn to Play the Piano

One of the most important aspects of a successful learning app is its design, yes it's that important! MuseFlow excels in this area with its immersive and user-friendly interface... The app's design is both visually appealing & functional. This provides a pleasant learning environment that keeps distractions away. The intuitive layout makes it easy to navigate through lessons, practice sessions, and progress tracking. The goal is to get you into that beautiful flow state where learning becomes very easy.

The great design philosophy really makes sure that the learning experience is seamless & enjoyable. If you pay close attention, you will see that the colors are thoughtfully chosen. The clean user-interface helps maintain your focus on playing, allowing you to fully immerse yourself in the music. This exact attention to detail in the design increases your ability to learn and enjoy the process. No other apps on the market, makes learning piano with AI so easy! Just look at the screenshot below.

how-to-learn-to-play-piano-with-ai
Click here to start your free trial! Start your MuseFlow free trial right now for 7 days free!

3. Engaging Gamification Keeps You Motivated!

The Los Angeles based engineering team made learning piano into an engaging and interactive game. They integrate gamification deeply into the learning process. Each new rhythm and note is a level you need to pass, and your performance is tracked in real-time with color-coded notes and a scoring system. Just how you want to keep playing a video game is how you want to keep playing the piano.

Another great feature is that the software gives immediate feedback on accuracy and tempo. This turns practice sessions into a fun challenge. This approach also keeps you motivated and eager to improve.. and this makes it easier to stick with your practice routine. By making the learning process feel like a game, the AI tech answers the works better than a traditional piano teacher. That's why so many users call MuseFlow the best piano learning app.

learn-to-play-piano-with-ai

4. Comprehensive Learning Tools & Features

MuseFlow offers a wide range of tools & features to support your piano learning journey. The app provides quick tutorials before each level, ensuring you understand the key concepts and techniques needed to succeed. Real-time feedback with pattern recognition algorithms. This helps you identify and correct mistakes instantly, allowing you to improve quicker that traditional lessons!

Moreover, MuseFlow is continually expanding its features to provide even more value... Planned updates include advanced curriculum options, AI-driven pattern recognition for even deeper personal insights, and new practice modes for ear training. These comprehensive tools support your journey and make sure that you develop a well-rounded skill set - from technical proficiency to musical understanding.

learn-to-play-piano-with-ai

Conclusion

In conclusion, if you're wondering how to learn to play piano with AI, MuseFlow is the best app on the market. As mentioned above, its AI-driven personalization, engaging gamification, immersive design, and comprehensive learning tools create the best possible learning experience in 2024. MuseFlow makes learning piano not just effective but also really really fun and enjoyable. We promise it will keep you motivated and accelerate progress quickly.

Try the Piano App right now for free

The Best Piano Learning App in 2024: 5 Reasons Why MuseFlow Leads the Way

Are you looking to learn piano in a fun, engaging, and effective way? Then you have found the perfect solution! In 2024, the best piano learning app is MuseFlow. This innovative app combines technology with a very deep understanding of musical education like no other. Below are 5 quick reasons why MuseFlow is the best software for learning piano this year.

Try MuseFlow for Free Right Now

the-best-piano-learning-app

1. AI-Driven Personalization

The California based company stands out due to its AI-driven personalization. It tailors each lesson to your specific skill level. Traditional piano lessons often follow a one-size-fits-all approach, which can often leave students feeling frustrated or bored. MuseFlow, on the other hand, uses sophisticated algorithms to continuously adapt to your unique progress. Whether you’re just a beginner or an advanced player, the technology makes sure that each lesson is perfectly suited to your current abilities. This will keep you challenged and engaged, and also won't leave you frustrated.

best-free-piano-learning-app

2. Gamified Learning Experience

One of the most unique aspects of MuseFlow is its gamified learning experience. The piano app transforms the process of learning piano into a fun game! This means each new rhythm and note you learn is a level you need to pass. Unlike other outdated apps that rely on superficial stars and badges, here the gamification is deeply integrated into its teaching method. This could not be done by a human teaching you piano lessons... Every note you play counts towards your overall score - with real-time feedback that shows your accuracy and tempo. This new engaging approach makes practice sessions feel like a lot of fun & like a rewarding challenge rather than an annoying chore!

the-best-free-piano-learning-app
Someone can click this link to be taken to the start free trial page of MuseFlow so they can learn piano for free!

3. Immersive & Beautiful Design

Learning an instrument should be an enjoyable experience. MuseFlow's design really reflects that. The app has an immersive &visually appealing interface that makes practicing a pleasure and fun. Unlike other apps with outdated and often complex designs, the best piano app on the market has an interface that is both beautiful and user-friendly. The carefully curated colors, icons, and layout are designed to be easy on the eyes. This is actually really important to staying on the app and enjoying to learn to play piano! It allows you to focus on your playing without distractions. This attention to detail in the design enhances the overall learning experience, making it more enjoyable for you..just look at the screenshot below.

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4. Focus on Sight Reading

MuseFlow prioritizes sight reading. This is a crucial skill for any pianist. Sight reading is the ability to read & play music at first sight - representing the "floor" of your musical ability. Many traditional teaching methods focus heavily on the "ceiling" of a student's ability—what they can achieve with extensive practice. This AI Piano learning app emphasizes improving your sight reading skills. It really allows you to reach true musical fluency faster. By mastering sight reading, you can quickly progress to playing songs with greater musicality & expression.It makes the learning process more enjoyable and less frustrating...

Another great bonus of the software is that is has an innovative way to generate an infinite amount of new music at YOUR level. This means you will always have fresh material to practice, ensuring that your skills continue to improve without the monotony of repeating the same exercises. This is huge, because all other apps only have the same material you can practice.

the-best-piano-learning-app-for-free
This is a banner that someone can click to be brought to the page to start their free trial if they'd like after reading this blog post. You can click here to start learning piano today!

5. Comprehensive Learning Tools for Your Musical Education

This new app is not just about playing notes... it offers a comprehensive suite of tools to enhance your musical education. What does that mean? Well, the app includes tutorials before each level to really make sure that you understand the key concepts & techniques. Real-time feedback from pattern recognition algorithms helps you identify and correct mistakes instantly. This helps you learn faster. Moreover, MuseFlow is continuously expanding its features, with plans to introduce advanced curriculum options, AI pattern recognition for deeper insights, and new practice modes for ear training, chord and scale exercises, and rhythm drills.

The software will soon feature a repertoire library where you can apply your sight reading skills to your favorite songs, and a music theory section with personalized exercises to expand your knowledge.

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Conclusion

In 2024, MuseFlow is the best piano learning app available for many reasons! It offers you a unique blend of AI-driven personalization, smart gamified learning, immersive design, helps you focus on sight reading, and offers comprehensive learning tools. By combining these unique elements, the app provides you with a fun, engaging, and highly effective way to learn piano. The best part is, whether you’re a beginner looking to start your musical journey or an experienced player trying to refine your skills, MuseFlow is your best friend to help you achieve your musical goals. 

Try MuseFlow's free Trial Right Now.

Is There A Fun Way To Learn Piano?

Let’s explore what it means to find the joy in learning a new instrument, and ask ourselves is there a fun way to learn piano? We’ll talk about what it looks like to have fun while you learn an instrument, and explore some options to enhance the process for any student.

If you’re interested in trying out our piano education app for yourself, please visit beta.museflow.ai and try MuseFlow for free! Otherwise, continue reading to find out what it’s all about.

What is Flow State?

Flow state is a radical idea coined by the Sociologist and Author Mihaly Csikszentmihalyi. It’s that groove you get into where you're doing a task and you lose track of time. The task is usually just a bit of a challenge, but not too challenging that you feel overwhelmed by the task; just hard enough to keep you moving forward and easy enough to know you’re doing well. A lot of professional athletes and musicians find flow in their work, but we at MuseFlow believe we can also tap into it during the learning process. Even for beginners!

MuseFlow's level roadmap showing the different states of the levels - complete, in progress, and not started. This type of open world learning allows you to drop into flow state as quickly as possible.s
MuseFlow meets you where you’re at, and lets you try out every level to find the perfect Goldilocks level for you - not too easy, not too hard.
Start you free trial today! Click here to get MuseFlow for 7 days.

What is Gamification?

Gamification is the application of game-like elements to anything from teaching and learning, to motivating yourself to to the dishes. The old world way of adding game-like elements to an activity involves points and score cards, badges and stars. At MuseFlow, we’ve changed it up a bit by making the entire activity of learning how to play piano a game; not with superficial stars and badges, but by making each new rhythm and note you learn a level that you need to pass.

Notes on screen show the different states of the notes - green, red and yellow. The accuracy displayed on screen is 96%, and the tempo is 72bpm, the goal tempo of the lesson. This is the UI for the lesson page in MuseFlow.
MuseFlow is a game in itself. Every note you play counts towards your overall score. Red is 0, yellow is 1/2 a point, and green is 1 point.

Once you’ve completed 4 phrases at 95% accuracy at the goal tempo of the level, you pass that level! And are moved onto the next.

A modal on top of the lesson page says "Level Complete!" with a button that says "next level" and another one that says "back to roadmap"
Each level is composed of tiers. Once you pass a tier, you move onto the next. So on and so forth until you complete the level!

This creates an entirely new and fun way to learn piano; not with superficial badges and stars, but by having gamification at the core of the entire method.

What is Immersive Design?

Not a lot of people think about this, but design is incredibly important in making the learning process a success. A stark, boring, bright environment, we’ve found, is not the optimal setting to learn music. Because of that, we’ve made our interface beautiful.

We care deeply about the experience our users go through while exploring and learning with MuseFlow. Thus, we’ve made it a tenant of ours to make everything in MuseFlow as beautiful as possible.

A young, hip, woman sits on a piano bench in front of her piano with a tablet where the music usually rest. On the tablet is the UI for MuseFlow. She's about to start practicing.
Our colors, icons, and user experience are all carefully curated to balance ease on the eyes and simplicity, with engaging content. We aren’t flashy! The journey is supposed to inside of your head, not on the page.
Click here to start your 7-day free trial! MuseFlow can help you learn piano with gamification and through sight reading,

What Is Sight Reading?

Sight reading is the act of reading music at first sight. There are two thresholds in music education - one is what you can play without any practice, the other is what you can play with an indefinite amount of practice. We call the first one the “floor” of your ability, and the second one the “ceiling” of your ability.

A simple graphic that says "ceiling = muscle memory" and "floor = true fluency"
Sight reading is the floor of your music ability. That is what we consider to be true musical fluency.

Too many teachers and music education methods focus on the ceiling of a student's ability. We at MuseFlow, instead, think a more fun way to learn piano is by focusing on the floor of a student's ability during lessons. Increasing a student's sight reading skill gets them to perfecting the musicality of songs (the fun part of playing songs) faster, instead of spending hours and hours on the technique of simply being able to play the song. That gets boring quickly. It gets frustrating, and students drop out of music lessons because of it.

About 50% of music students drop out of music activities by the time they turn 17. We aim to make that number much smaller.

There hasn’t ever been a way to generate an infinite amount of music at your level of playing… until now. We at MuseFlow have invented a way to give you music you’ve never seen before, that never repeats, and is at your level. The music continues to generate until you get 4 phrases of music at 95% accuracy. At that point, you’ve successfully mastered that new skill!

Sight reading is the key here. We’re teaching through sight reading, instead of teaching through songs. After you’ve mastered that new skill through sight reading, you then can apply that skill to songs that get unlocked in your repertoire section inside of MuseFlow.

Conclusion: Why MuseFlow?

These are the reasons why MuseFlow is quickly becoming the most fun way to learn piano. Its inventive way of blending sight reading, flow state, gamification, and immersive design allows students to find the joy of learning an instrument better than ever before. With our new approach to music education, we can revolutionize the music education industry for the better.

Try it out for free at beta.museflow.ai. We can’t wait to hear your feedback as we make music education available and engaging to all students!

Empowering Beginner Musicians: Blending Sight Reading and Flow State

Greetings to all the passionate music teachers!

As music aficionados, we understand the profound joy of playing an instrument — a pursuit that’s both challenging and immensely rewarding. However, conveying this love to young students can be a different tune altogether.

Today, let’s delve into the art of sight reading and how embracing flow state through sight reading can bring the joy back to the musical journey for beginners.

Sign up for MuseFlow by clicking here!

Sight Reading: The Gateway To Musicianship

Mastering sight reading isn’t just about learning new music faster; it makes learning new music more fun. Fluent sight reading shortens the journey to playing notes correctly, leaving more brain space and time to focus on musicianship and expression.

Yet, traditional teaching methods often don’t teach sight reading. They focus on learning new songs instead. As the songs get harder, students’ skills don’t increase at a relative rate. Because they’re only exercising that new skill in that one specific context of that one specific song. It doesn’t become ingrained in them to the point where they can effortlessly apply the new skill when encountering it in a different piece of music.

As the gap widens, students lose motivation as pieces get harder to practice. They then spend hours repeating the same song over and over to perfection, and get bored with the slow progress, never really feeling what it’s like to be perfectly challenged by something to where it’s fun to practice it! With this way of teaching, it’s either too hard or too easy. Never right in the middle.

Flow State: The Key To Sight Reading

Enter the realm of flow state, coined by psychologist Mihaly Csikszentmihalyi. It’s that magical state of total focus and concentration, familiar to musicians during jam sessions and concerts. It’s that Goldilocks zone of “not too hard, not too easy.”

What if we applied the concept of flow to beginning music education by making sight reading the engine of learning and mastering a new skill? And what if we’re were able to start a student right where the challenge meets their skill level so that they’re concentrating and engaged for hours, but still enjoying the practice?

A young woman smiling, sitting at a piano with MuseFlow on an iPad in front of her.
By combining flow state and sight reading, we can create a new way of teaching music.

Introducing MuseFlow: Learn Music Through Flow

MuseFlow emerges as a solution that combines sight reading and flow state. It systematically teaches fundamental concepts through sight reading by ensuring that each lesson consists of new, manageable music at a specific skill level. No repetition. Instead, it’s a continuous stream of never before seen music that challenges and exercises the new skill, pushing them just beyond their comfort zone.

As their teacher, place your students in the lesson that challenges them just enough (accuracy is displayed on screen. You want to keep them right around 85% for optimum flow). Once they hit 95% accuracy and sustain that for four phrases, they’ve successfully mastered that new skill!

MuseFlow will send you weekly progress reports so you can see if they’re practicing throughout the week and how long they spend on each lesson. Once a student passes a lesson, they can immediately apply the new skills they’ve learned to fresh pieces you assign.

A data dashboard with important teacher info-graphs on students’ practice sessions.
MuseFlow’s weekly progress reports.
Learn piano and find your flow with MuseFlow's 7-day free trial... try it now! Click here!

Reframing The Learning Process

MuseFlow reframes the learning process so students can learn a new skill outside of a prescribed song they’d otherwise have to repeat over and over ad nauseam. They learn the new skill in a flow state, creating a positive connection between the new skill and the process of learning. Then when they apply that new skill to music that’s right at their difficulty level, they’ll be able to learn that song much faster, more thoroughly, and more enjoyably. This will allow you, their teacher, to focus on refining the fun parts like musicianship and expression in the songs you assign at their in-person lesson.

Consider this quote Kyle, one of MuseFlow’s current users:

“MuseFlow is like having a gym partner who guides you through a workout they’ve already planned out. I don’t have to spend time or energy coming up with exercises to train and wondering if it’s optimal, I can just follow along and focus solely on execution. There’s such an overload of information when it comes to learning piano that it’s so taxing (especially if you struggle with perfectionism) to come up with a routine alone. MF takes away a little bit of that decision making and it’s honestly so refreshing.”

In conclusion, combining flow state and sight reading opens a window to a richer and more enjoyable learning experience by inspiring and captivating on a fundamental level. With Museflow, we can shift from a song-first approach to the transformative combination of sight reading and a flow state-first methodology.

MuseFlow is empowering music teachers to revolutionize music education from the ground up. We, as teachers, know the benefits of music education. Now let’s bring it to every student we can.

Curious about whether MuseFlow is right for your students? Visit www.museflow.ai/teachers to schedule a demo. With a MIDI keyboard and a computer, you can try out our current version at beta.museflow.ai. We can’t wait to hear your feedback as we make music education available and engaging to all students!

The Floor-Ceiling Model of Skill Acquisition

Is your music practice building true fluency, or is it just training muscle memory?

When we think about how to get better at a musical instrument — or any skill-based activity — the natural strategy that comes to mind is repetition. Repeat, repeat, repeat, until you’ve finally mastered it.

This is the tried-and-true method, and is absolutely correct. As a matter of fact, that’s the whole definition of practice — “performing an activity repeatedly or regularly in order to improve or maintain one’s proficiency.”

But we need to be careful with how we approach our practice sessions. If you spend all of your time practicing specific pieces, you will eventually master those songs but you won’t necessarily have gotten better at playing music in general. Effectively, all you’ve done is train yourself to regurgitate an exact sequence of notes, without any variation. An impressive feat, to be sure, but it hasn’t increased your musical fluency at all.

Learning a musical instrument of course requires maintenance and repetition, but we have to be careful that we don’t practice old things so much that we forget to work on new things. If you only ever practice the same things, you never really grow or improve. It would be like attempting to become fluent in English by memorizing a Shakespeare monologue, and nothing else.

Learn piano for free with MuseFlow! Click here to start your 7-day free trial. Find your flow with Sight Reading!

Practice vs. Learning

Brad Harrison, a composer and educator who runs an excellent music education YouTube channel, insightfully describes the difference between practice and learning. Practice is trying to get better at things you already basically know how to do. By contrast, learning is the acquisition of new knowledge or skills, and the process of becoming familiar with new material. For example, playing through a piece of music for the first time would fall under “learning,” but each repetition after that would fall under “practice.” Both steps are important, but they are focused on very different goals. Regardless of where you are in your music learning journey, it’s essential that you maintain a healthy balance between practice time and learning time.

By making a habit of learning new things, you’ll develop the meta-skill of learning how to learn. This will make you a better musician and will even help you play old repertoire better. You’ll realize that every new challenge is just a puzzle to be unlocked and understood, and you’ll have the confidence to tackle that puzzle.

If you only play the same songs over and over again, you won’t grow or improve. You’ll either get bored and quit, or you’ll get stuck when confronted with a new challenge because you only know how to do what you already know how to do. Even when you do finally master a new song, the satisfaction of learning it will eventually fade away and you’ll feel stuck again. True musical fluency is the ability to quickly learn and master whatever you want, without needing to practice it for weeks or months on end.

The Floor and Ceiling of Competency

This brings me to an idea that I’ve been formulating over the past several years of working with music students. I think that the way we normally think about the concept of one’s skill level in a certain field needs to be expanded.

Imagine that a person’s skill level can be visualized as a vertical range, with a floor and a ceiling. The ceiling represents the level of music that a person could play well, given an indefinite (but not infinite) amount of time to practice. This could be represented by the hardest piece you’ve ever performed at a recital or competition, for example.

Alternatively, the floor represents the level of music a person could play well (not necessarily perfect, but certainly passable) on the first time they ever see it. This activity is what we call sight reading — reading on sight without any prior preparation. This could be represented by the average piece that you could find sheet music for and play today, without much practice.

A list of different pieces of music repertoire that fall on a spectrum of difficulty, some in the “easily playable” zone, some in the “possible with practice” zone, and some in the “too difficult” zone.
An example of where different songs may fall in a person’s floor-ceiling range.

Any piece of music that’s below the floor of your skill level is well within your ability to play without any practice. Any piece of music that falls somewhere between your floor and your ceiling can be reasonably mastered through dedicated practice — the closer it is to your ceiling, the longer it will take. The amount of time it would take to learn a piece in this range roughly equates to the amount of time it would take to work your way from the floor up to the difficulty level of the piece in question.

Most people spend the majority of their practice time endeavoring to raise their ceiling, tackling ever harder and harder songs that take them weeks, months, or even years to learn properly. This seems like a fine endeavor, at first glance. Ideally, by raising the ceiling of one’s ability, the floor would also rise by the same amount.

An adjusted image of the same repertoire pieces on the difficulty spectrum, now with a raised floor and ceiling.
Floor and ceiling both moving upwards at the same rate. “Minuet in G” is now within your wheelhouse, while “Fantaisie-Impromptu” is now within reach after months of practice.

Unfortunately, this isn’t what actually happens. A person’s “floor level” is much more difficult to raise than their “ceiling level”, and it doesn’t happen automatically just by practicing more ceiling-level material. As a result, most music students don’t spend nearly enough time working on raising their floor.

The result is that a person’s ceiling moves up at a much faster rate than their floor, creating a wider and wider gap between them. This means that as they start working on more challenging material, each new song they attempt to learn will take longer and longer to master. This happens to everyone — it’s perfectly natural!

A graph of how a person’s “ceiling level” and “floor level” increase over time as they get better. The ceiling level trend line moves up much faster than the floor level trend line.
Over time, the gap gets wider and wider. If you continue working on repertoire pieces at the top of your range, you will find that you start getting stuck for longer and longer.

Pretty soon, practice sessions have transformed from a fun learning opportunity into a constant source of frustration and stress that takes up all of their time. Students very quickly find themselves too far outside their comfort zone, without the necessary skills to learn increasingly advanced material in a natural, stress-free way.

This is because a musician’s floor level is actually a far more accurate barometer of overall musical competency than mastery of a song that has been meticulously practiced over and over again for months. In other words, a person’s floor level represents their degree of true musical fluency.

A musician’s “ceiling level” is mostly accessible through intense practice and muscle memory, whereas their “floor level” is easily accessible at any time, without preparation.
If you were in a foreign country and didn’t speak the language, would you rather be confined to a small selection of phrases from a guidebook, or be able to adapt to any spontaneous conversation that arises?

Music lessons often focus on the ceiling of someone’s playing ability, but all professional standards for working musicians place much greater emphasis on a minimum floor threshold of musicianship. It doesn’t matter how good you are after weeks or months of practice — it matters how good you are right now, at a moment’s notice.

So it’s important that you take some time to work on pushing your floor up, even though it might seem like the musical material you’re practicing is dropping way down in complexity as a result. It doesn’t mean you’ve gotten worse, it just means that you’re focusing on a part of your musicianship that you don’t normally focus on!

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Achieving Musical Fluency

So how does one actually raise the floor of their skill level then? Here are some specific areas of focus that are most helpful in improving overall musical fluency.

  1. Sight Reading
    Sight reading is the cornerstone of elevating your floor. It’s the ability to play a piece of music on the first try, without prior practice. Dedicate time regularly to sight read different pieces, varying in styles and difficulty. This sharpens your adaptability, reinforcing the fundamental skill of playing music fluently from the very first encounter.
  2. Technique Exercises
    Technique exercises might not be as glamorous as performing a complex piece, but they are the building blocks of musical proficiency. Focus on scales, arpeggios, and finger exercises. These not only enhance your technical skills but also contribute significantly to your floor level. A strong technical foundation ensures that you can handle a broader range of musical challenges.
  3. Music Theory
    Music theory is often neglected, but it serves as a compass in your musical journey. Understand the relationships between notes, chords, and progressions. It provides a roadmap, allowing you to navigate unfamiliar musical territories effortlessly. The more intimately you understand the language of music, the more confident and fluent you become.
  4. Ear Training
    Cultivate your ability to listen critically and reproduce what you hear. Ear training is fundamental to musical fluency as it enhances your capacity to recognize tones, intervals, and harmonies. Start with simple exercises like identifying intervals and progress to more complex tasks. This skill not only raises your floor level but also opens doors to improvisation and playing by ear.
  5. Diversity of Repertoire
    Instead of getting stuck in the loop of practicing the same songs repeatedly, diversify your repertoire. Explore different genres, time periods, and difficulty levels. The more varied your musical vocabulary, the more adaptable you become. This approach aligns with the idea that every new challenge is a puzzle to unlock and understand.

These five areas are what I call the fundamental “food groups” of musicianship. I’ll be going into more depth about each of these in future posts.

Building a well-rounded practice routine is important, and methods with which to do so are well-documented. That being said, it is much harder to be intentional about raising one’s floor level than you might expect.

MuseFlow: Raising the Floor

At MuseFlow, we’re building solutions to this very problem. The app guides users through a continuous sequence of sight reading exercises, increasing complexity by one skill at a time. By constantly playing new material that they’ve never seen before, MuseFlow users have a unique opportunity to hone their ability to read and play music fluently.

In this way, our curriculum ensures a balanced approach between practice and learning. It guides you through a variety of musical challenges, preventing you from getting stuck repeating the same pieces over and over again. This diversity cultivates a well-rounded skill set, and raises the overall floor of your musical ability.

While our main focus is currently on sight reading training, we have lots of exciting new features coming later this year, including technique, music theory, and ear training exercises, as well as a repertoire library and practice assistant. Stay tuned for more updates about all that and more, coming soon!

If you’re looking for a practice tool to help you improve your musical skills, and haven’t been able to find a system that truly delivers the results you’re looking for, consider trying out MuseFlow. Just head on over to https://museflow.ai to sign up for our web app and start your 2-week free trial today.

It’s time to break free from the frustrations of repetitive practice and finally achieve the level of musical fluency you’ve been striving for. Happy playing!

Unlocking the Brain Benefits of Flow State in Early Music Education

Flow state can change the way we teach early music education!

Have you ever felt frustrated or bored while learning to play an instrument? This usually happens because students don’t always feel like they’re in flow state when practicing and learning — that mental zone where time seems to vanish and you become utterly absorbed in the activity. Learning to play an instrument isn’t just about mindless practice; it’s a complete brain workout! Sometimes, the mental gymnastics required to master an instrument can be challenging, pushing students to their limits.

Today, let’s delve into the fascinating world of flow state. We’ll discover how it’s reshaping the way students approach learning an instrument, and why it’s vital for nurturing young musicians who often find the journey too difficult or anxiety-ridden.

Click this link to be taken to the sign in page where you can start to learn piano with MuseFlow, the app that teaches piano through sight reading and flow state, using gamification...

Flow State: A Brain Booster for Young Musicians

Mihaly Csikszentmihalyi’s groundbreaking work in his book Flow: The Psychology of Optimal Experience uncovered the concept of flow state. While it’s often associated with professional musicians and athletes, it can be a game-changer for budding musicians too.

Getting into flow state during music education is like unlocking a secret door to peak performance and enhanced learning. It is a state of complete concentration, where the outside world fades away and the music becomes the sole focus. It’s an optimal mental state where creativity and skill meld seamlessly, leading to a truly immersive musical experience. Flow typically occurs when the challenge of a task matches a student’s skill level. When the challenge is too low, a student might feel bored, and when it’s too high, they may become anxious.

In the world of music, entering flow state often involves selecting pieces of music that are just challenging enough to stretch a student’s ability, but not so difficult that they become frustrated. This is a lot harder than you might think, given the many variables of musical complexity within a single piece of music.

Bridging the Dropout Gap in Early Music Education

Traditional early music education isn’t all sunshine and harmonies. In fact, dropout rates among young music students are alarmingly high (~50% before they reach the age of 17). The typical grind of discipline and hard work can turn the sweet symphony of learning into a sour note.

So, how do we keep students engaged and passionate about music? The answer lies in integrating flow state into the early stages of learning an instrument. Positive feedback is also crucial. When students feel tangible progress in their education, they’re more likely to enter flow state. And when they receive praise for their efforts (not their achievements), they’re more likely to create positive feedback loops of internal motivation. This combination makes learning something new deeply engaging and gratifying.

The Art of Sight Reading: A Gateway to Flow State

One of the most effective ways of reaching flow state while learning an instrument is through sight reading. Sight reading is the act of reading and playing music at first sight. Sight reading pushes students to train their reading and playing skills without relying on muscle memorization, which often becomes a crutch when practicing a single song repeatedly. If the challenge is in the “Goldilocks zone” of their skill level (not too hard, not too easy), then flow state is engaged.

Sight reading, if personalized to a student’s skill level, allows them to drop into flow, immersing them in the process of learning.

What if there was a way to make early music education more engaging, gratifying, and effective?
What if there was a way to make early music education more engaging, gratifying, and effective?
Try MuseFlow for free! Click here to sign up for your 7-day free trial and start learning piano with gamification and flow state!

MuseFlow: Your Gateway to Flow State Learning

Enter MuseFlow, a web app set to transform how students learn piano, especially in the early stages. Instead of assigning one piece of music which exercises many skills all at once — thus making it hard to isolate practice on a specific technique — MuseFlow guides students through new rhythms and notes in isolation first, then embeds that new skill into the rest of their musical knowledge later on, all while immersing them in a constant stream of new music.

In the first level, students learn how music is written, basic rhythms, their first note, and how that one note is played in both hands. Then, they simply start playing. The metronome sets the pace, a guiding cursor shows the next note, and they play each note on the spot while sight reading.

Rather than playing a passage of music, stopping, then repeating that same piece of music over and over again until it’s perfect, MuseFlow pushes students to keep playing no matter what. Getting stuck on previous mistakes is one of the most common ways for students to get knocked out of flow state and lose motivation. In MuseFlow, new music will continue to appear and help them hone their skills in ever-changing contexts, instead of stopping the flow to go back and repeat music they’ve already played.

A cursor shows students what to play next, and they figure it out along the way through sight-reading.
A cursor shows students what to play next, and they figure it out along the way through sight reading.

This is the heart of flow state — that groove that students find themselves in, where time seems to fade away and the joy of learning takes center stage. It becomes just about passing each level, mastering each small new concept, one by one. They start to recognize those aha moments: “Oh my gosh, I’m getting it! I’m really getting it!” When they eventually pass the level, they experience a rush of dopamine and feel a sense of achievement that propels them forward on their musical journey.

Every level students pass gives them that dopamine hit and sense of achievement.
Every level students pass gives them that dopamine hit and sense of achievement.

Why Flow State Learning Matters

Csikszentmihalyi’s research reveals that being in a state of flow can turbocharge the learning process. It’s not only about making learning more enjoyable — it also boosts information retention. By weaving flow state into MuseFlow, we’re tackling the dropout crisis head-on. When students are deeply engaged in the process of learning an instrument, it boosts their motivation, achievement, and enjoyment of learning.

Curious about what MuseFlow has to offer? Visit www.museflow.ai to find out more. If you have a MIDI keyboard and a computer, try out the beta version at www.beta.museflow.ai. We can’t wait to hear what you think and set out on this musical journey with you!

Analyzing User Data with Custom AWS Pinpoint Events, Kinesis, Lambda, Eventbridge, Glue, and Athena

Side note: This pipeline was created for use in a project I’ve been working on with a few friends called Museflow.ai, where we’re trying to combine flow state, gamification, and (eventually) AI to make learning the piano effortless. Feel free to try out the prototype!

If you’re reading this you’re most likely already aware of AWS’s many useful cloud features which make them one of the leading destinations for cloud native applications. AWS’s about page now simply says that they offer “over 200” services, because even they have stopped counting. Today I’ll be focusing on a combination of services which you may or may not have heard of: Pinpoint, Kinesis, Lambda, Eventbridge, Glue, and Athena. That sounds more like a secret pass phrase than a list of technologies, and maybe it is, because together they unlock the ability to analyze your user data as your users interact with your application—or at least I hope.

My goal in writing this will be to put these services together like lego pieces to arrange a data pipeline that pushed events like logins, sign ups, or really any custom event you choose, to a glue table for you to slice and dice with SQL in Athena. From my understanding of how these services interact with one another, it should very well be possible. I’ll be writing this article in 3 parts:

  • Architecture Overview
  • Pinpoint setup (with Cognito)
  • Front end setup (React)
  • Data pipeline
  • Athena/Glue

I’ll be using a combination of two infrastructure frameworks to accomplish my setup: AWS SAM and Terraform. I prefer SAM for developing serverless applications for how easy it makes development and deployment, and I like Terraform for shared infrastructure. Configuration values can be shared between these two frameworks using Parameter Store. This project will require both as I’ll be developing a serverless data pipeline in addition to some other infrastructure.

If you want to try our MuseFlow for free, you can click here and you'll be taken to the sign up page where you can create an account and start learning MuseFlow with gamification, AI, and flow state!

Architecture Overview

Here’s a quick flow diagram to illustrate the frankenstein of services I will be putting together to achieve this goal:

To quickly walk through the purpose of each service, pinpoint will be used to collect event data. It offers a convenient way to send events from my user’s application to our backend data lake. It offers a plugin connection to Kinesis that I would otherwise have to manually create. Kinesis similarly plugs directly into Eventbridge. Eventbridge acts as a trigger for my Lambda which will map events to correct S3 buckets. The reason I’ll be using different S3 buckets for different events is to provide a separate schema for each. Glue expects all events in an S3 bucket to hold the same schema in order to partition them into a table, which I will then be able to query with SQL using Athena.

AWS Pinpoint Setup

Our first order of business is setting up Pinpoint. Since the project I’m setting this up for is a React project, I’ll be showing my frontend client examples in React. The Pinpoint infrastructure setup will be in Terraform.

Terraform

1resource "aws_pinpoint_app" "pinpoint_app" {
2    name = var.app_name
3}
4
5data "aws_iam_role" "pinpoint_to_event_stream_role" {
6  name = var.pinpoint_role_name
7}
8
9resource "aws_pinpoint_event_stream" "pinpoint_event_stream" {
10  application_id         = aws_pinpoint_app.pinpoint_app.application_id
11  destination_stream_arn = aws_kinesis_stream.event_stream.arn
12  role_arn               = data.aws_iam_role.pinpoint_to_event_stream_role.arn
13}
14
15resource "aws_ssm_parameter" "client_id" {
16    # checkov:skip=CKV2_AWS_34: Does not need to be encrypted
17    name        = "/${var.org_name}/${var.environment}/pinpoint/application_id"
18    description = "Pintpoint application id"
19    type        = "String"
20    value       = aws_pinpoint_app.pinpoint_app.id
21
22    tags = {
23        environment = var.environment
24    }
25}
26
27resource "aws_kinesis_stream" "event_stream" {
28  name             = "${var.app_name}-app-event-stream-${var.environment}"
29  retention_period = 48
30  encryption_type = "KMS"
31  kms_key_id = "alias/aws/kinesis"
32
33  shard_level_metrics = [
34    "IncomingBytes",
35    "OutgoingBytes",
36    "ReadProvisionedThroughputExceeded",
37    "WriteProvisionedThroughputExceeded",
38    "IncomingRecords",
39    "OutgoingRecords",
40    "IteratorAgeMilliseconds"
41  ]
42
43  stream_mode_details {
44    stream_mode = "ON_DEMAND"
45  }
46
47  tags = {
48    Environment = var.environment
49  }
50}

This creates an AWS Pinpoint application and an event stream I can use to send Pinpoint Events. Not in the above snippet is the role by pinpoint to send events to Kinesis. I create all my IAM roles in a different, global Terraform workspace specific to IAM. I use template files which inherit variables like account id from a global variables file, but here’s the JSON template I use:

The assume-role policy:

1{
2	"Version": "2012-10-17",
3	"Statement": [
4        {
5            "Effect": "Allow",
6            "Action": [
7                "sts:AssumeRole"
8            ],
9            "Principal": {
10                "Service": "pinpoint.amazonaws.com"
11            },
12            "Condition": {
13                "StringEquals": {
14                    "aws:SourceAccount":"${ACCOUNT_ID}"
15                }
16            }
17	    }
18    ]
19}
20

and the policy attachment:

1
2{
3	"Version": "2012-10-17",
4	"Statement": [
5      {
6        "Effect": "Allow",
7        "Action": [
8            "kinesis:PutRecords",
9            "kinesis:DescribeStream"
10        ],
11        "Resource": "arn:aws:kinesis:us-west-2:${ACCOUNT_ID}:stream/org-name-app-event-stream-dev"
12      },
13      {
14        "Effect": "Allow",
15        "Action": [
16          "kms:DescribeKey"
17        ],
18        "Resource": [
19          "arn:aws:kms:us-west-2:${ACCOUNT_ID}:key/<kms kinesis key ID>"
20        ]
21      }
22    ]
23}

Now, once I run the Terraform I can see the following in my AWS console when I navigate to https://us-west-2.console.aws.amazon.com/pinpoint/home?region=us-west-2#/apps.

All projects Terraform pic in AWS...

Once you click on the project, the important part is the event stream in settings, which should be enabled.

MuseFlow's AWS setup and how it works...
Event streams for MuseFlow

Now that my event stream is enabled, I can almost start sending events.

Learn piano. Find your Flow with Flow State and MuseFlow. Cognito helps with your event stream, and MuseFlow uses both! Take a read of the article to find out more. And sign up if you'd like to try it for free for seven days!

Cognito Identity Pool

Before I can start sending events, my front end needs a way to connect to my AWS resources using AWS credentials. To do that, you need a Cognito Identity Pool. Cognito Identity Pools, not to be confused with User Pools, allow one to provide guests and authenticated users with the credentials needed to access AWS resources. They’re provided permissions like anything else in AWS — with an IAM role. However, the assume role permissions is a bit unique. You’ll be specifying a Cognito identity as a federated identity. Here’s what that looks like:

1{
2  "Version": "2012-10-17",
3  "Statement": [
4    {
5      "Effect": "Allow",
6      "Principal": {
7        "Federated": "cognito-identity.amazonaws.com"
8      },
9      "Action": [
10        "sts:AssumeRoleWithWebIdentity",
11        "sts:TagSession"
12      ],
13      "Condition": {
14        "StringEquals": {
15          "cognito-identity.amazonaws.com:aud": [
16            "us-west-2:<your cognito identity pool id>"
17          ]
18        },
19        "ForAnyValue:StringLike": {
20          "cognito-identity.amazonaws.com:amr": [
21            "authenticated",
22            "unauthenticated"
23          ]
24        }
25      }
26    }
27  ]
28}

As you can see, you’re providing the specific cognito identity with permission to assume the role. This can be with anauthorized access — which would be to send events before a user has logged in — or authorized access, which requires a cognito JWT token.

You then give your role permission to send events to pinpoint, by attaching a policy that looks like this:

1{
2	"Version": "2012-10-17",
3	"Statement": [
4      {
5        "Effect": "Allow",
6        "Action": [
7            "mobiletargeting:UpdateEndpoint",
8            "mobiletargeting:PutEvents"
9        ],
10        "Resource": "arn:aws:mobiletargeting:*:${ACCOUNT_ID}:apps/<your pinpoint app ID>*"
11      }
12    ]
13}

This is the part that had me confused for a while: you have to specify both unathenticated and authenticated if you want to be able to send sign up events (because the user hasn’t signed in yet). Also, You will need to attach the IAM role to the cognito identity pool for both authenticated and unauthenticated access. Here’s the Terraform:

1resource "aws_cognito_identity_pool" "users" {
2  identity_pool_name               = "users_identity_pool"
3  allow_unauthenticated_identities = true
4  allow_classic_flow               = true
5
6  cognito_identity_providers {
7    client_id               = aws_cognito_user_pool_client.users.id
8    provider_name           = "cognito-idp.${var.region}.amazonaws.com/${aws_cognito_user_pool.users.id}"
9    server_side_token_check = false
10  }
11
12  supported_login_providers = {}
13
14  saml_provider_arns           = []
15  openid_connect_provider_arns = []
16}
17
18resource "aws_cognito_identity_pool_roles_attachment" "main" {
19  identity_pool_id = aws_cognito_identity_pool.users.id
20
21  roles = {
22    "unauthenticated" = local.identity_pool_role_arn,
23    "authenticated" = local.identity_pool_role_arn
24  }
25}

Something to note about the above. Once your user logs in they will switch from an unauthenticated session to an authenticated session which will change the session ID.

React Setup

I’ll be using the AWS Amplify project to instrument Pinpoint into my frontend code. They provide several useful Javascript libraries for implementing AWS services. If you haven’t heard of Amplify, it’s a framework for developing applications on AWS, similar to Firebase. It’ll get you up and running quickly with AWS infrastructure using Cloudformation. However, I tend to use Terraform for my infrastructure, so I just use the front end libraries they provide.

However, since they intend people to utilize their libraries with Amplify, they can be a bit cagey in the docs with regard to setting it up without Amplify. All of their docs expect you to import the configuration from a file created by the CLI called “aws-exports”, like so:

1import { Amplify, Analytics, Auth } from 'aws-amplify';
2import awsconfig from './aws-exports';
3Amplify.configure(awsconfig);

But I don’t really want to do that. Luckily, I was able to find the full expected configuration in one of the library tests which lead me to this config:

1import { Amplify, Analytics} from 'aws-amplify';
2
3Amplify.configure({
4  Auth: {
5    region: region,
6    userPoolId: cognitoUserPoolId,
7    userPoolWebClientId: cognitoClientId,
8    identityPoolId: awsIdentityPoolId,
9    identityPoolRegion: region
10  },
11  Analytics: {
12    AWSPinpoint: {
13      appId: awsPinpointApplicationId,
14      region: region
15    },
16  }
17});

I won’t get into the userPoolId and userPoolWebClientId — that’s for Cognito user authentication and could easily be a second post. With this set up, I can then run the following in my sign up function:

1import { Analytics } from 'aws-amplify';
2...
3return signUp(values)
4  .then(result => {
5    Analytics.record(signUpEvent({email: values.email}))
6  })
7  .catch(err => {
8    setAuthErrors(handleAuthErrors(err))
9  });

Which uses a defined event function which looks like this:

1export interface EventAttributes {
2  [key: string]: string;
3}
4export interface EventMetrics {
5  [key: string]: number;
6}
7export interface AnalyticsEvent {
8  name: string;
9  attributes?: EventAttributes;
10  metrics?: EventMetrics;
11  immediate?: boolean;
12}
13export const signUpEvent = ({ email }: {email: string}): AnalyticsEvent =>({
14  name: "SignUpEvent",
15  attributes: {
16    email
17  }
18})

Finally, I can see events filtering into the kinesis stream:

How MuseFlow processes incoming data

Now on to the data pipeline.

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Data Pipeline

In order to sent my events from the pinpoint kinesis stream to S3, I’m going to take advantage of Eventbridge Pipes. Pipes allow you to send events to Eventbridge with additional features like filtering on specific event types and event enrichment. This is the serverless part of the setup, so I’ll be using AWS SAM.

You can install sam with Pip or any of the options here. I’ll be using pip and a python virtual environment. First, I’ll create my virtual env, then I’ll install sam into it.

mkvirtualenv pinpoint-event-pipeline
pip install aws-sam-cli

After a lengthy install I’m ready to run sam init --name pinpoint-event-pipeline . Or, if you already have a SAM repo setup you like, go ahead and copy everything over.

Eventbridge Pipes

Eventbridge pipes allow you to filter and enrich events on the way to eventbridge from a variety of source types. One of those source types is a kinesis stream, which is why I chose it for this project.

the series of events from Source to Target in MuseFlow's Eventbridge Pipeline.

The following CloudFormation is what I used to create my pipe:

1  Pipe:
2    Type: AWS::Pipes::Pipe
3    Properties:
4      Name: kinesis-to-eventbridge
5      Description: 'Pipe to connect Kinesis stream to EventBridge event bus'
6      RoleArn: !GetAtt PipeRole.Arn
7      Source: !Sub arn:aws:kinesis:us-west-2:${AWS::AccountId}:stream/my-org-app-event-stream-${Environment}
8      SourceParameters:
9        FilterCriteria:
10          Filters:
11            - Pattern: '{"data":{"event_type":["SignUpEvent"]}}'
12            - Pattern: '{"data":{"event_type":["SignInEvent"]}}'
13        KinesisStreamParameters:
14          StartingPosition: LATEST
15          BatchSize: 1
16          DeadLetterConfig:
17            Arn: !GetAtt PipeDLQueue.Arn
18      Target: !Sub 'arn:aws:events:us-west-2:${AWS::AccountId}:event-bus/my-org-events-${Environment}'
19      Enrichment: !GetAtt TransformerLambda.Arn
20      EnrichmentParameters:
21        InputTemplate: '{ "data": <$.data> }'

Obviously, I cut a lot of the template out for brevity, including the code for deploying my “enrichment” lambda as well as DLQ and Pipeline role. The full template can be found here.

In the above Pipe resource, I’ve defined a filter that only allows events that I’ve defined to pass through to my lambda — specifically only the “SignUpEvent” and “SignInEvent” event types I’ve defined. I’ve also defined an enrichment lambda — which I’ve called a “transformer” lambda because I’ll be using it to transform events into the format I’d like to have sent to my backend. At first, I just used the lambda to print the event to get an idea of how the data is shaped when it gets to my lambda, and without much time passing, I can see it in my Cloudwatch logs:

Pipe resources and SignupEvents in MuseFlow

Unfortunately, at this point I hit a wall. I would like to send the event along its way to Eventbridge (see the target of my Eventbridge Pipe). From there I would be able to create a rule which triggers on arrival of sign in/sign up events. Unfortunately, while I’m able to see the events recieved in the Eventbridge metrics — I’m not able create an event rule that triggers. I’m even using the generated schema from Eventbridge’s handy tool which scans your events:

The Schema MuseFlow uses and what is in our Eventbridge...

The point of sending the event to event bridge was to create the potential for an event driven approach that would allow me to feed more than one data source from eventbridge. Eventually, if I want to also send data to a realtime database, like Timescale, I would be able to create a second output lambda to route data to that database as well. However, for now my goal is to view my data in Athena. So, instead of routing my event to eventbridge and creating an eventbridge rule to trigger an S3 upload lambda, I’m going to make the lambda the target of my Eventbridge pipe.

This will involve editing the Pipe config like so:

  # Target: !Sub 'arn:aws:events:us-west-2:${AWS::AccountId}:event-bus/museflow-events-${Environment}'
  # for now - just point to the output lambda instead of pushing to eventbridge first.
  Target: !GetAtt PinpointOutputLambda.Arn

There are plenty of tutorials on how to set up a lambda with AWS SAM, so I won’t be going over that here. But, there are some gotchyas in the setting up the event pipe and athena backend. You need to make sure your Pipe has permission invoke each lambda (the validator and the final target), and your lambdas need permission to post to the final S3 buckets which will make up your Athena tables. Your lambda invoke permissions will look like this:

Resources:
  TransformerLambdaInvokePermission:
    Type: 'AWS::Lambda::Permission'
    Properties:
      FunctionName: !GetAtt TransformerLambda.Arn
      Action: 'lambda:InvokeFunction'
      Principal: 'pipes.amazonaws.com'
      SourceAccount: !Ref 'AWS::AccountId'
      SourceArn: !GetAtt Pipe.Arn
  OutputLambdaInvokePermission:
    Type: 'AWS::Lambda::Permission'
    Properties:
      FunctionName: !GetAtt PinpointOutputLambda.Arn
      Action: 'lambda:InvokeFunction'
      Principal: 'pipes.amazonaws.com'
      SourceAccount: !Ref 'AWS::AccountId'
      SourceArn: !GetAtt Pipe.Arn

In addition to the above you’ll want to provide the following permissions to the “output lambda” — or the lambda that your Eventbridge Pipe is targeting:

- Effect: Allow
  Action:
    - s3:PutObject
    - s3:AbortMultipartUpload
  Resource: 
    - !Sub 'arn:aws:s3:::museflow-sign-up-events-${Environment}'
    - !Sub 'arn:aws:s3:::museflow-sign-in-events-${Environment}'
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Transformation/Validation Lambda

Now, I’ll get a bit into the lambda code. My first lambda has two purposes: Validate the incoming event, and transform the event into a truncated version containing only the necessary pieces. The transformer lambda handler looks like this:

1import urllib.parse
2import os
3import traceback
4from utils.logger import logger
5import json
6from aws_xray_sdk.core import patch_all
7from aws_xray_sdk.core import xray_recorder
8from main.transformer import transform_event
9
10logger.info('Loading function')
11env = os.getenv('Environment', 'local')
12TracingOff = os.getenv('TracingOff', False)
13
14def handler(event, context):
15    log.info(json.dumps(event))
16    log.info(context)
17    env = os.getenv("Environment")
18    s3_endpoint_url =  os.getenv('S3EndpointUrl')
19    region = os.getenv("AWSRegion")
20
21    log.info(f"region: {region}")
22    log.info(f"s3_endpoint_url: {s3_endpoint_url}")
23    validated_events = []
24    for evt in event:
25        try:
26            # print(evt['data']['event_type'])
27            transformed_evt = transform_event(evt)
28            json_dict = json.loads(transformed_evt.model_dump_json())
29            validated_events.append(json_dict)
30        except Exception as e:
31            if env != "local" and not TracingOff:
32                subsegment_ref = xray_recorder.current_subsegment()
33                if subsegment_ref:
34                    subsegment_ref.add_exception(e)
35            log.exception(e)
36            log.error('failed_to_validate_event', evt=json.dumps(evt))
37    try:
38        return validated_events
39    except Exception as e:
40        log.error(e)
41        traceback.print_exc()
42        raise e # re-raise for Lambda console

Each event is run through a transformation function called “transform_evt”. That function looks like this:

1def transform_event(event):
2    if event['data']['event_type'] == 'SignUpEvent':
3        return SignUpEvent(**({
4            "event_type": event['data']['event_type'],
5            "datetime": event['data']['endpoint']['EffectiveDate'],
6            "session_id":  event['data']['session']['session_id'],
7            "email": event['data']['attributes']['email'],
8        }))
9    elif event['data']['event_type'] == 'SignInEvent':
10        return SignInEvent(**({
11            "event_type": event['data']['event_type'],
12            "datetime": event['data']['endpoint']['EffectiveDate'],
13            "session_id":  event['data']['session']['session_id'],
14            "email": event['data']['attributes']['email'],
15            "id": event['data']['attributes']['id'],
16            "is_test_user": event['data']['attributes']['is_test_user'],
17            "user_type": event['data']['attributes']['user_type'],
18        }))

Each event is being validated by its respective Model, which I’ve written using Pydantic, a rather convenient python validator. Something to point out in the above model is that I’m using the “effective date” portion of the event as the timestamp. It seemed as good an option as any.

Here’s the model I’m using for my SignUpEvent:

from pydantic import BaseModel, Extra, EmailStr, field_serializer
from datetime import datetime
from typing import Literal


class SignUpEvent(BaseModel):
    class Config:
        extra = Extra.forbid
    @field_serializer('datetime')
    def serialize_dt(self, dt: datetime, _info):
        return dt.strftime('%Y-%m-%dT%H:%M:%S.%f')[:-3] + 'Z'
    event_type: Literal['SignUpEvent']
    datetime: datetime
    session_id: str
    email: EmailStr

In order for an event to be processed it must conform to the expected schema. Additionally, I’m serializing the date to remove the last 3 0's that get appended to the end when Pydantic prints the date into JSON. Something else to note is that The Amplify library which I’m using to send these events doesn’t accept null values. So, to compensate for that I wrote the following validator, which allows for nulls:

1def coerc_string_to_null( string_val: Any):
2    val = None if string_val == 'null' else string_val
3    return val
4
5class MyClass(BaseModel):
6   ...
7   _my_value_validator = validator('my_value', pre=True, allow_reuse=True)(coerc_string_to_null)
8   my_value: Union[str, None)
Learn piano and find your flow with MuseFlow. The app that teaches you through Lambda's and cognito. We host all our music on AWS and grab it through event streams to give you music you've never seen before through sight reading!

“Output” Lambda

Now, we can discuss what I’m calling the “OutputLambda”, which is responsible for taking the validated and transformed event, and sending it to the Athena backend. After this section I’m going to go over actually creating the Athena backend, but for now it should be noted that there is an S3 bucket for each event type. Here’s the handler code for the output lambda (I’ve removed some extraneous code that’s pretty much the same as the last one):

1def get_date_details(datetime_str):
2    dt = datetime.strptime(datetime_str, '%Y-%m-%dT%H:%M:%S.%fZ')
3    return (dt.day, dt.month, dt.year)
4...
5try:
6  s3_client = boto3.client('s3', endpoint_url=s3_endpoint_url)
7  for evt in event:
8      with tempfile.TemporaryDirectory() as temp_dir:
9          id=str(uuid.uuid4())
10          schema = transform_event_schema(evt)
11          parquet_out(evt, schema, f'{temp_dir}/evt_parquet_{id}.parquet')
12          s3_bucket = bucket_map[evt['event_type']]
13          day, month, year = get_date_details(evt['datetime'])
14          s3_put_object(s3_client, s3_bucket, f'year={year}/month={month}/day={day}/{evt["event_type"]}{id}.parquet', f'{temp_dir}/evt_parquet_{id}.parquet')
15  return {
16      "statusCode": 200,
17      "headers": {
18          "Content-Type": "application/json"
19      },
20  }

As you can see I’m calling a new transform function on each event — but this time it’s called transform_event_schema . That’s because I’m taking each event and creating a parquet schema. You can use JSON for Athena, but Parquet is more efficient, which may save you some $$. Here’s the code for my parquet schema generator:

1import pyarrow as pa
2import pyarrow.compute as pc
3
4def transform_event_schema(event):
5    if event['event_type'] == 'SignUpEvent':
6        return pa.schema([
7            ('datetime', pa.timestamp('s', tz='UTC')),
8            ('event_type', pa.string()),
9            ('session_id', pa.string()),
10            ('email', pa.string())
11        ])
12    elif event['event_type'] == 'SignInEvent':
13        return pa.schema([
14            ('datetime', pa.timestamp('s', tz='UTC')),
15            ('event_type', pa.string()),
16            ('session_id', pa.string()),
17            ('email', pa.string()),
18            ('id', pa.string()),
19            ('is_test_user', pa.bool_()),
20            ('user_type', pa.string())
21        ])

It’s a bit verbose and frankly, kind of strangely formatted, but that’s the gist. What isn’t pictured here is an example of an int, for which you might use pa.int64() . You can read more about parquet data types here.

Once my parquet schema is created, I can write it to S3. Unfortunately, I couldn’t easily figure out a way to transform the event into parquet and write directly to S3 from memory, so instead I created a file in a temp directory. It’s important to use a temp directory because Lambdas can potentially use the same context with the same temp. The code I used to write the parquet file looks like this:

1from json2parquet import write_parquet, ingest_data
2
3def parquet_out(json_blob, schema, path):
4    # table = pa.Table.from_pydict(json_array, schema)
5    # pq.write_table(table, path)  # save json/table as parquet
6    date_format = "%Y-%m-%dT%H:%M:%S.%fZ"
7    record_batch=ingest_data([json_blob], schema,date_format=date_format)
8    write_parquet(record_batch, path,compression='snappy', use_deprecated_int96_timestamps=True)

I used a nifty library called json2parquet. The one part that’s worth calling out here is use_depreciated_int96_timestamps=True . From the json2parquet docs:

“If you are using this library to convert JSON data to be read by Spark, Athena, Spectrum or Presto make sure you use use_deprecated_int96_timestamps when writing your Parquet files, otherwise you will see some really screwy dates.”

Fair enough.

The final bit of info worth sharing is that when you write these files to S3 you’ll want to do so in binary. Here’s the function I used to read the parquet file and push it to S3:

1from smart_open import open
2
3def s3_put_object(client, bucket, key, file_path):
4    file = open(file_path, 'rb')
5    content = file.read()
6    tp = {'min_part_size': 5 * 1024**2, 'client': client}
7    uri = f's3://{bucket}/{key}'
8    with open(uri, 'wb', transport_params=tp) as fout:
9        logger.info(f"pushing to s3 {uri}")
10        fout.write(content)
11    file.close()

smart_open is utility library which allows you to read and write from S3 like a native file system using the “open” function. As you can see, I’m specifying b for ‘binary’.

And that’s pretty much it. After deploying, I can go log into my app and watch my function invocation metrics:

Data that is coming in and our of our smart_open utility library set up.

And check out their corresponding evens in S3:

Events corresponding to the days in MuseFlow and our eventbridge.

You might have also noticed the slightly specific path I chose for these events. This is actually a way that Glue will partition your tables by date automatically (More info in the AWS docs here), which brings us to our next section: Glue/Athena.

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Glue/Athena

AWS Glue is a pretty nifty tool with a lot of data-centric features. One thing it works well with is Athena — a Serverless query engine that allows you to query against a multitude of sources, one of which being a Glue table.

In order to create Glue tables based on your S3 data, you’ll need to create what’s called a “Glue Crawler” which will read all of your data in an S3 bucket and place it into a glue table. Now, what’s really nifty about these crawlers is that you don’t even have to create the tables yourself. The crawler will infer the schema of your table based on the format of the data in the S3 bucket. You saw the schemas earlier in my output lambda. So, all you need to do is define an Athena database and one crawler per S3 bucket. Here’s the Terraform I wrote to create them:

1locals {
2  glue_role         = data.aws_iam_role.glue_role.arn
3}
4
5data "aws_iam_role" "glue_role" {
6  name = var.glue_role_name
7}
8
9resource "aws_glue_catalog_database" "this" {
10  name         = var.database_name
11  description  = var.database_description
12  parameters   = var.parameters
13}
14
15resource "aws_glue_crawler" "this" {
16  for_each = var.tables
17  name                   = "${var.database_name}_${each.key}_glue_crawler_${var.environment}"
18  description            = "${var.database_name} glue crawler for table ${each.key} ${var.environment}"
19  database_name          = aws_glue_catalog_database.this.name
20  role                   = local.glue_role
21  schedule               = "cron(0 1 * * ? *)"
22  configuration = jsonencode(
23    {
24      Grouping = {
25        TableGroupingPolicy = "CombineCompatibleSchemas"
26      }
27      CrawlerOutput = {
28        Partitions = { AddOrUpdateBehavior = "InheritFromTable" }
29      }
30      Version = 1
31    }
32  )
33  s3_target {
34    path = each.value.location
35  }
36}
37
38resource "aws_athena_workgroup" "athena" {
39  name = var.aws_athena_workgroup_name
40
41  configuration {
42    enforce_workgroup_configuration    = true
43    publish_cloudwatch_metrics_enabled = true
44
45    result_configuration {
46      output_location = "s3://${var.s3_query_result_bucket_name}/output/"
47
48      encryption_configuration {
49        encryption_option = "SSE_S3"
50      }
51    }
52  }
53}

Not provided above is the config for the S3 Athena query output bucket. Make sure that when you do create the output bucket, you provide a bucket policy that gives access to athena via “athena.amazonaws.com”. For reference, here are the variables I provided to the above template:

1{
2  "environment": "prd",
3  "database_name": "org_name_analytics_prd",
4  "database_description": "org_name athena analytics db",
5  "glue_role_name": "org_name-main-prd-glue-role",
6  "s3_query_result_bucket_name": "org_name-athena-output-prd",
7  "aws_athena_workgroup_name": "org_name-analytics-prd",
8  "tables": {
9    "org_name_sign_in_events": {
10      "description": "org_name app sign in events table prd",
11      "location": "s3://org_name-sign-in-bucket-prd/"
12    },
13    "org_name_sign_up_events": {
14      "description": "org_name app sign in events table prd",
15      "location": "s3://org_name-sign-up-bucket-prd/"
16    }
17  },
18}

In this config each key is the name of a table/crawler. Two things are important to mention. Athena only takes underscores and letters as table names, and you need to end your s3 bucket location with a slash: “/”.

As you can see, I provided a role to be used by the glue crawler. You should make sure that role has permissions to access to each of the S3 buckets you create to hold your parquet events, like so:

1{
2 "Version": "2012-10-17",
3 "Statement": [
4        {
5            "Effect": "Allow",
6            "Action": [
7                "glue:*",
8                "lakeformation:*"
9            ],
10            "Resource": [
11                "*"
12            ]
13        },
14        {
15            "Effect": "Allow",
16            "Action": [
17                "s3:GetObject",
18                "s3:ListBucket"
19            ],
20            "Resource": [
21                "arn:aws:s3:::org_name-sign-up-bucket-prd",
22                "arn:aws:s3:::org_name-sign-up-bucket-prd/*",
23                "arn:aws:s3:::org_name-sign-in-bucket-prd",
24                "arn:aws:s3:::org_name-sign-in-bucket-prd/*"
25            ]
26        }
27    ]
28}

Finally, with all this in place I can visit the Athena console and write a query:

How MuseFlow's Athena in AWS works.

One thing to note is that you should select the correct working group on the top right, because that’s what actually configures the output bucket. Otherwise, you’ll be asked to configure a new one.

A closeup of our Primary source in MuseFlow's AWS Athena
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Conclusion

This was a fun project. I’ve wanted to set up an Athena pipeline for a while, but never had a good reason. With an easy to create Athena pipeline, I’ll be able to easily and cheaply store data for use in ML, business analytics, or any other analytics I’d like to do.

Some closing thoughts. As you saw in the image of my lambda invocation metrics, this process doesn’t batch at all. That means potentially a single invocation per event. This could potentially get rather costly, so a way to mitigate this might be to place an SQS queue between my event pipe and my lambda. Additionally, Crawlers will re-crawl all of your data daily. This can also be costly, but an alternative might be to use event driven crawlers which would prevent re-crawling of data.

Hope this was an enjoyable and instructive read. If you’d like to follow me for more tech articles, feel free to follow me here or add me on Linkedin: https://www.linkedin.com/in/steven-staley/

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Can I Teach Myself to Play the Piano with AI?

Some people might be skeptical if they could teach themselves how to play piano with AI. MuseFlow makes it easy for you by having artificial intelligence and machine learning serve the process of learning in two unique ways - music generation AI, and pattern recognition machine learning. It does the work for you to make learning a lot more fun, effective, and efficient. It does this by incorporating AI into the core of its pedagogy. The folks over at MuseFlow are making efforts to improve their algorithms every single day. Let’s take a deeper dive into this, and how artificial intelligence and machine learning are improving the way we learn piano.

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Music Generation AI

There are few music apps out there that have generative AI imbedded within them. MuseFlow’s approach to learning involves giving you music you’ve never seen before, that never repeats, and is at your level of skill. You can choose from a myriad of levels on the level roadmap. Unit one starts with just one note, three rhythms, and two hands, and ends with two octaves (14 notes), four rhythms, and two hands. But how does MuseFlow give you music that never repeats? Surely that would be impossible with the amount of music that would need to be written!

MuseFlow's level roadmap to show that you can choose where to start given your experience level. All this in service of learning how to play piano with AI.
You choose where to start. With MuseFlow’s roadmap, you can find music that’s at your skill level and dive right in there without having to start from a specific spot in the curriculum.

The team over at MuseFlow is constantly improving its music generation artificial intelligence  algorithm so that it gives you the best quality sheet music as a constant stream until you pass the level. By using generative AI for sheet music, MuseFlow’s team sets the parameters for each level, then unleashes the artificial intelligence to start generating music for you to play!

A pic of music being generated by MuseFlow's AI. This is what you would play!
Music continues to flow until you get 95% accuracy for four lines of music. At that point, you pass the level!

MuseFlow’s team is constantly training the AI with what they call, “Phrase Tinder”. If a phrase of music passes the rigorous tests of it sounding good enough to play and is exercising the new skill of a certain level, they swipe right. If a phrase is not good enough to play or isn’t useful, they swipe left. This method of training allows the computer to understand what is good and what is bad so it can create new and original pieces that fit within the guidelines of the curriculum, and are fun to play!

A banner that says "learn piano, find your flow." with a link to signup for MuseFlow to learn piano!

Pattern Recognition AI & Machine Learning

As you play, MuseFlow can see what you’re playing in relation to the music that’s on the screen. If you’re consistently messing up a note or rhythm, or even a series of notes or series of rhythms, it will gently give you more phrases of music that have those patterns in them. It can even recognize the intersection of rhythms and notes! It does this all in the background so your flow isn’t interrupted. You as the student wont even know it’s going on.

An image of a young woman sitting at a piano with MuseFlow in front of her and she's smiling using MuseFlow's AL to learn how to play piano.
As you play, MuseFlow is listening to you and adjusting the music to suit your needs. You wont even know it’s happening!

This teaching method enables MuseFlow to monitor each micro-skill you learn, such as individual notes and rhythms, along with their various combinations. MuseFlow adjusts the music and increases exposure if it detects that your proficiency in any specific micro-skill is lower than the others. Once you effortlessly and unconsciously bring that micro-skill up to standard with the rest, MuseFlow reduces its exposure back down to parity with the other micro-skills it is tracking.

One of MuseFlow's readouts that show your progress as you learn to play the piano using MuseFlow's artificial intelligence. It shows the current level you're on, how much time you practiced this week in minutes, and how long it took you to play each level this week.
Soon, you’ll even be able to see a readout of your practice sessions! How long you played each level, and what micro-skills are needing work. But again, you won’t have to choose which to work on. MuseFlow knows and will adjust with that info in mind.

Conclusion

Unlike traditional music education environments and methods, the folks at MuseFlow, Inc. are committed to creating a safe, reliable space for you to learn and grow without the outside pressures of  anyone looking over your shoulder. As students, we need to feel like we can fail without any judgment. MuseFlow inspires you to learn, motivates you to learn, all with artificial intelligence and machine learning as assistants in the background, listening and adjusting the sheet music to suit your needs without any judgement. MuseFlow answers the question “can I teach myself how to play piano with AI” with a resounding YES! With its pattern recognition algorithms and music generation, MuseFlow’s AI is set to revolutionize music education for the better, and become the forerunner in the industry as the best new way to learn piano.

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Online Piano Lessons for Beginners: 4 Reasons Why MuseFlow is the Best Software

Do you want to learn piano but you're not sure where to start? That's ok, most people in the beginning feel this way. Finding the right method can be an overwhelming and hard decision. If you're looking for the best and most engaging online piano lessons for beginners, MuseFlow is the perfect solution. We listed 4 quick reasons why the new app stands out as the best software to start your piano journey.

Try the 7-day free trial right now! 

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1. Achieving Flow State - More Important Than you Think

MuseFlow’s unique approach to learning is purposely made to help you achieve a flow state—an optimal psychological state for learning. You have probably been there before, where you're fully immersed in an activity - and you even lose track of time... Achieving flow state is crucial for making learning both enjoyable & efficient. MuseFlow, Inc., The software company based out of California, has created an app that tailors each lesson to your skill level. This is to make sure that the material is challenging enough to keep you engaged BUT not so difficult that you become frustrated. This is really important for you to want to keep learning!

This balance is essential for beginners like you, who might otherwise feel overwhelmed. By keeping you in the flow state, MuseFlow makes practicing piano a really delightful experience. This in turn promotes consistency & faster learning. The app’s intelligent design adjusts to your progress, helping you stay in the zone (flow) and making your practice sessions both more productive and more fun.

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2. Expert Founders with Music Backgrounds

Another one of the key strengths of the innovative software is its team of founders. They all come from rich musical backgrounds. This is important, because the app is designed with a deep understanding of music education and the challenges beginners face. 

  • Steven Gizzi, Chief Executive Officer, is a composer and music educator with credits for clients like LEGO, Cartoon Network, DreamWorks, and Facebook Watch.
  • Patrick Boylan, Chief Operating Officer, is a multi-instrumentalist and producer specializing in musical theater and jazz piano.
  • Tucker Dean, Chief Data Scientist, is a data scientist with a knack for integrating machine learning with practical applications.
  • Steven Staley, Chief Technology Officer, is an infrastructure engineer with experience in building full stack applications.
  • Andrew Urbanowicz, Chief Information Officer, is a full stack developer with a background in mathematics and computational physics.

You can easily tell that their collective expertise makes sure that MuseFlow is not just another generic learning app but a comprehensive and well-thought-out tool specifically designed to help beginners learn piano.

This is a link for someone to click to sign up for MuseFlow! It allows them to start a free trial right here, and right now...

3. Free Online Piano Lessons for Beginners

A major advantage of MuseFlow is its accessibility. MuseFlow offers a 7-day free trial. This allows beginners to explore the app and experience its benefits without any financial commitment. This trial period is perfect for those who are just starting and want to test different learning methods. The reason for the free trial is, the team feels so confident you will love it!!

During the free trial, users can access various levels and tutorials. These provide a solid foundation in piano basics. This feature answers the question, "Are there online piano lessons for beginners?" with a definite YES. It's an excellent way for newcomers to get a feel for the app’s unique approach and see tangible progress in a short amount of time. It's really the most fun way to play piano!

4. Comprehensive Learning Tools to Make it Fun

The piano software for beginners, provides a comprehensive suite of learning tools that go further than traditional methods that you might have tried... Each lesson is accompanied by quick, engaging, interactive tutorials to ensure that beginners understand the necessary concepts & techniques before diving in. Real-time feedback is important. And it's done by advanced pattern recognition algorithms helps users identify and correct mistakes instantly. Of course, this is crucial for effective learning.

The app also features a gamified learning experience, turning each lesson into a fun and interactive game. Just like when you play a video game. By earning points and progressing through levels, students always say that they stay motivated & excited about their learning journey. This innovative new approach for beginners to learn piano makes the often tedious process of practicing piano a lot more rewarding.

Additionally, MuseFlow is continuously expanding its features. This is all done based on users feedback, so it keeps getting better and better with your input as the fuel! Future updates will include advanced curriculum options, enhanced practice modes for ear training, chord and scale exercises, and rhythm drills. A new repertoire library & a music theory section with personalized exercises will further make the learning experience the best out there. The goal is for students to develop a well-rounded skill set and be able to play the songs that they want to play. Anyone should be able to go to a piano and play their song of choice, an indescribable amazing feeling. With these amazing tools, it's by far the best piano learning app.

Conclusion

As discussed above, anyone that is searching for the best online piano lessons for beginners, MuseFlow is the top choice. Its unique ability to help learners achieve a flow state and the expertise of its music-savvy founders make it different from any other app. Additionally, the accessibility of free online piano lessons for beginners, and its comprehensive learning tools make it stand out!

MuseFlow’s new innovative approach to piano education really makes sure that beginners not only learn the fundamentals but also enjoy the process, keeping them motivated and eager to progress. The best software for online piano lessons for beginners...

Try it right now for FREE.

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Best Piano Teaching App: 4 Reasons Why MuseFlow is the Best

If you're looking for the best piano teaching app to elevate your piano playing skills, then you have found it! Look no further than MuseFlow... With so many bad apps available, finding the right one can be tough. This new AI based app stands out as the best new software for pianists. Have a quick look at these 4 great reasons why its the best piano teaching app for you:

Try the 7-day free trial right now.

1. Experience the Power of AI for Personalized Learning

MuseFlow uses advanced AI technology to offer a real personalized learning experience. This is a must for any app in 2024. Unlike traditional piano lessons that follow a rigid complicated curriculum, this new technology adapts to your individual progress & learning style. This AI-driven personalization makes sure that each lesson is tailored to your current skill level... This provides just the right amount of challenge to keep you engaged without feeling overwhelmed. Because feeling overwhelmed will make you feel frustrated very soon after!

The app tracks your performance in real-time. It analyzes your strengths & identifying areas that need improvement. This intelligent feedback system helps you make steady progress. It also makes sure that you're always working on the skills that will most benefit your own unique development. By customizing each lesson to fit your needs, MuseFlow makes learning piano more fun & enjoyable than ever before! 

2. Smart Gamification to Keep You Motivated

MuseFlow turns piano learning into an engaging and interactive game. Just like your favorite video games that you can't stop playing. They do it through the innovative use of gamification. Have you heard of that? The piano app integrates gamification deeply into the learning process... Each new rhythm and note you learn is treated as a level you need to pass. So practice feels like a series of fun challenges. This works better than a frustrated teacher telling you what to do.

The app provides immediate feedback on your accuracy & tempo, with color-coded notes and a scoring system that makes each practice session really exciting. By transforming the learning process into a game, MuseFlow keeps you motivated and happy. The goal of this is to make you stick with your practice routine and it's easier than ever and more fun than ever to learn to play piano with AI. They know how easy it is to fall of your routine. This approach makes the question, "Is there a fun piano teaching app?" easy to answer with MuseFlow.

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A banner that says "learn piano. Find your flow." and some more text that says "click here to start your free trial". A user can click on this banner and be taken to the signup page of MuseFlow to start their learning journey!

3. Very User-Friendly Design

One of many standout features of MuseFlow is its smart and user-friendly design. What does that mean? Well, the app is designed to be both visually appealing and functional. This really creates an optimal learning environment. The intuitive layout makes it easy to navigate through your lessons, practice sessions, and progress tracking. The way it should be done.

The design philosophy of the California based app is focuses on making the learning experience as seamless and enjoyable as possible! The new app uses carefully chosen colors and a clean interface to help maintain your focus on playing, without unnecessary distractions. This thoughtful design enhances your ability to learn and enjoy the process, setting MuseFlow apart from other piano teaching apps. You can see it in more detail below and on the product page.

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4. Free Piano Teaching App  

MuseFlow offers a generous 7-day free trial. This allows you to explore its features without any financial commitment. Try it first and see if you love it. This trial period is perfect for anyone looking for a free piano teaching app to get started with. During the trial, you can access various lessons and interactive tutorials that provide a strong foundation in piano basics and you can get familiar with how it works.

A really great way to experience the app's unique approach & see real progress.. in a short amount of time. The trial also answers the question, "Are there free online piano lessons for beginners?" with a confident yes. By offering this above mentioned no-cost entry point, MuseFlow makes high-quality piano education accessible to EVERYONE.

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Conclusion

For anyone that is seeking the best piano teaching app, we're happy to say that MuseFlow is the best app! Its AI-driven personalized learning, engaging gamification, smart design, and free trial features make it the best choice for you. MuseFlow’s innovative approach to piano education ensures that students not only learn the fundamentals but also enjoy the process, keeping them motivated and excited to progress. It's like a video game that you keep wanting to get better at, the best part is while you advance you learn how to play the piano.

Try MuseFlow for Free!

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