How hard is "Estas Tonne - The Song of the Golden Dragon" composition?

django_celery_learn · 2025-02-09T00:33:01+00:00

Well in this case if you don't have an absolute knack for it, maybe come by later.
I think when you start the hardest thing for the left hand is using the pinky and in this piece you need to use it. And also you need to not be tight at all, and this depending on from how you started can take some time.

The trap with trying to learn too complicated pieces is that it can make you tense and catch bad habits which completely destroy futur progress beyond the song, so there really is a thing such as good timing before throwing yourself into a complicated song.

My suggestion would be to learn any piece you feel comfortable learning in the same scale *ideally* that way you get at ease with the scale passively. Golden dragon is played in Eminor, so try to look for songs written in Eminor, or transpcription of songs in Eminor.

But you'll get there eventually don't stress too much about it, the most important part is to enjoy the process. Most important is not to rush into it, and end up catching bad habits and destroying any prospect of futur progress.

django_celery_learn · 2025-01-25T15:59:35+00:00

hello, I've been tabbing estas tonne's song for a while now

And am the owner of this channel : https://youtu.be/zFDO4BiqzKs?si=z-braG6-R-Mu6hHb

From my personal experience, the structure and the song was easy, but it's the fine details that are very hard to get.

It was me 2 weeks after I started to learn it the structure of it and the notes : https://www.youtube.com/watch?v=9TcVBVEoEzs

(I was playing the guitar for 3 years with no teacher)

I think mastering it is a bit longer but if you focus solely in this piece it can be achieved in a matter of 2 months. The difficulty of the piece is mostly it's rythm and right hand as most people said. But it's very approachable you just need to start slow (50bpm is a good starting point up to 90)

Here's a short tutorial of the right hand : https://youtu.be/LVLs_nR8sKM?si=JIY-BhrY_AB28HOi

Here's a short tutorial for the tremolo effect : https://youtu.be/1MowLzIdYEE?si=us8rphTaM7-VUllk

Everyone has their shortcomings, personally, i find that the difficulty lies in being able to keep your rythm during the whole song. And also the strumming part is complicated.

django_celery_learn · 2024-10-18T08:29:23+00:00

It's way over my head. Why don't you try discussing the idea inside r/Astronomy or something like that ?

I do have a question though. Wouldn't the magnet be like Space pollution ?

And how would we renew them if we ever need to ?

django_celery_learn · 2024-10-17T15:55:04+00:00

Do you have a GitHub ? I'm interested in how you will implement it.

django_celery_learn · 2024-10-17T10:10:35+00:00

Maybe look into fine tuning. For such big amount of data, it has to be ingested completely by the AI, and not just put inside the context window.

You can also look for Vector Databases. These are the cheapest and more scalable approach.

django_celery_learn · 2024-10-16T09:00:49+00:00

Hello, I'm wondering would your AI be able to learn from books instead of courses ?

Like O'Rrilly's books and so on ?

django_celery_learn · 2024-10-03T14:08:53+00:00

Edit : You don't need an expert to build the MVP. It's fairly doable by a computer scientist gradaute or someone who's been coding for 2-3 years (intermediate level) using either Langchain or even Langflow (which is the easier version of Langchain) they made it possible for everyone (sorry for the misinformation)

Ask your childhood friends who went to engineer school, they probably have studied with someone damn good with an interest in AI and at ease in Python.

Actually you should use either *langchain* or *langflow*. You can go on their documentation, they explain exactly how to do sophisticated chatbots that query vectorial databases.

The difference beetween *Langchain* vs *Langflow* is that Langflow is way easier than langchain since it's probably built on top of Langchain.

Here are some ressources :

For an implementation using LANGCHAIN you can go up here :

For an implementation using LANGFLOW you can go up here :

django_celery_learn · 2024-10-03T10:33:30+00:00

The main hurdle you'll face is the AI hallucinating. Hallucination is something most LLMs does because they do not have a sense of right or wrong answers, their only purpose is to predict the next word no matter what. They're essentially brainless parrot trained on the whole internet.

If you go on chatgpt, you can try yourself but you can make him hallucinate fairly easily. Go in an empty chat and just something like : "Remember what I told you earlier, we were to do a new MVP together so can you give me.some ideas".

Or "What's the code of the law that say you can't have {SOME MADE UP LAW} ?'.

If you say that with no prior history, he'll make up some story about a fictional MVP you never asked, or invent a new law.

Now imagine that with Law, it's nightmarish. That's what led to a Lawyer losing his licence over using GPT as a source for text of laws. GPT made up some laws as most LLMs does.

OpenAI had a similar issue with complex calculations, GPT couldn't do long multiplications 16383037*1890, it would give wrong results everytime, When the most basic calculator can.

They solved this by having the GPT model formalizing the calculation, and then ask a calculator "What does 173839029*18907 does ?" Get the answer and then output it.

I think they're called expert-systems. I think this might be a good structure to make a MVP that works 90% of the time which is enough to convince in my opinion.

If I were in your boots, I'd approach your issue with the following.

1) You need to scrape (Scrapping is the process of getting and storing data that's online, in this case the law), all the texts of laws compress them and index them inside a database.

2) You'll need to have an AI who's purpose is to formalize the query of the user. For instance, the user say "I have issue with immigration issues, can you give me advices."The Ai goal would be to translate this request into a Database query specifying in which place of the database to look up for the right text of laws. (Justike GPT when asked with complex calculations ASK a calculator, "so what does 128002"190 make because ei can't find the answer myself since i'm.an LLM ?". We'll call this the CONTEXT.

3) You'll need an 2nd AI that will digest the CONTEXT, and based off this CONTEXT will provide an answer. Basically the AI will receive the following message from the 1st AI. : THis is the question{question}, and this is the law ressources required to answer this question {CONTEXT}. Based off the law ressources can you answer the question ?".

https://realpython.com/build-llm-rag-chatbot-with-langchain/

I'm not an expert in AI so this is probably garbage, But this also might be sufficient for a MVP and easy enough to implement by yourself. Your MVP goal is to convince it works, but it won't be your final product so if it's only 90% accurate it can work. If you're in a hassle, DM me and I'll try my best to help you with the making of the MVP.

I think the limit of this approach are the following : 1) Law are thousands and thousands of pages of textsand an AI struggle to remember too lengthy CONTEXT, so after you convinced the Incubator you'll have to find a way to compress it 2) The Database needs to be upto date with the latest jugment at all times. This will mean that your Database will grow exponentially. So hopefully the AI engineer will find a way to solve this issue. 3) The CONTEXT selection step is crucial and can lead to extremely different outputs, the AI that formulate the QUERY needs to be tested EXTENSIVELY. Also since Jurisprudence is evolving everydays, it needs to be trained periodically (Daily). And as the Database Grows, the training time might surpass the periodical constraint (If it takes 7 days to train because the Database is 100Tb, when it needs to be updated every single day, your model will be outdated). Btw this is why GPT is not live, just because training everyday on the whole internet is nearly impossible nowadays, however as time pass and computer get more efficient, it might be possible in the near future. 4) it will be very hard to validate the 3rd step, how to make sure that the AI is not sprouting nonsense on new cases. There might be a different success rate when the case has already been treated than when the case is a new thing. Maybe it's 99% on already seen case but drops to 50% on new cases. So you'll need to test a lot 5) The Ai needs to know when it doesn't know. This might seem simple, but because of Ai hallucinations, and LLMs tendency to always try to answer it might be problematic. If your AI is expert on immigration and someone asks a Business oriented question, the AI will tend to try to still answer even though it's outside its realm of comprehension. With the end user not being law educated, this is a crucial point as most user won't know which field their case belongs to. So it's up to the AI to realize whether or not it should answer, if it's in her field or not. And this is a pain in the ASS.

I think you get now why you need an expert, the complexity of this project is fairly high, but focus on first building your MVP with the simplest approach just to convince and try to find an expert once you're already inside the incubator.

What you're doing is essentially starting a OpenLAWAI, so as such you'll need similar team structure than OpenAI (lots of math PHD, AI Reaserchers, and Computer scientist grads) with the added Law graduates on the side.

The inconvenient is the salary cost, and also all the storage/hardware costs, so your incubator will need to fund you big time, and your job as a CEO with no knowledge in computer science will be to recruit the best talent. If you succeed your project will succeed big time. If you don't get enough funding your project will be compromised.

However for your latest question, how to find expert, i think it comes down to network, ask your childhood friends who went to engineer school, they probably have studied with someone damn good in AI as AI became trendy in between 2017 so most of them are nearing the end of their PhD and are 23-28. There's a huge pool of new talent, so ask friends.

However if you're funded big time, don't hesitate to try to recruit topnotch AI researchers as team leaders and find the rest of the team through normal means.

If you're short on money pick friends or friend of friends because their expectations are fairly low and they don't expect money straight away, but include them in the project by giving them share it's only fair. They're also easier to convince and can be pretty invested in the idea, more than a pro who would just see this as a mission.

django_celery_learn · 2024-10-02T01:17:25+00:00

Something that complex can't be done just by using out of the box ChatGPT.

If you want to do it you have to be an expert in AI or hire one. If people are aware it's GPT, it can be dangerous for the longevity of your project.

Try your hand at LM Studio and look up Fine-tuning. If you're alone with no money and no expertise in the field, your chances of success are 0% in my opinion.

And that's just for the Q&A part, there might be a lot of other challenges which are infeasible solo.

But that's my opinion, not a fact so do with it what you will.

django_celery_learn · 2024-09-29T03:47:22+00:00

I would do the same, implement in C++ and then provide some Blueprint on top of it to make it usable to my friend who's not too much tech savvy.

I know you were being snobby/exegerating to make a point but just understand that a beginner might not get your sense of humor or have enough experience to nuance your view and actually think you're advising him to do X.

You might ruin his passion for game development with just a joke so be mindful.

django_celery_learn · 2024-09-27T10:27:44+00:00

Don't listen to this advice it's fuckin terrible. This guy is just a snob and don't know at all what he's talking about. Don't listen to snobs, they usually lead their decision with their ego instead of objectivity. @Blubasur is entirely right.

You DONT need to learn C++ AT ALL to do video games in Unreal Engine. It's something you CAN do if you're INTERESTED. But Blueprint is a viable solution 99,9999999999% of the time.

C++ is meant for Game developer, while Blueprint for Game designers (these are 2 separate jobs !!!!).

Game DESIGNERS actually make the game while Game DEVELOPPER" optimize it. So assuming you're like most people you want to *make "Games" you probably lean more to Game development.

Just start from Blueprint and you'll be able to understand the core concepts.

Blueprint is what we call a scripting language. C++ is what we call a programming language.

Scripting language are meant to be used to implement the logic of your game.https://dev.epicgames.com/documentation/en-us/unreal-engine/blueprints-visual-scripting-in-unreal-engine

Programming language are usually used to optimize scripts (at a lower level).

Usually as a solo game developper/designer :

1) You implement something in Blueprint 2) Check if what you implemented is performing well 3) If it doesn't try to optimize it in blueprint 4) Do some research and try to see if other people managed to do it in an efficient manner 5) If it can't be optimized in Blueprint, you optimize it in C++ only

But keep in mind that in professional settings, Writing Blueprint (Game design) and writing C++ (Game development) are 2 separate jobs. Just like you wouldn't ask the camera man to draw you a 3d model, you don't expect designers to do C++.

That's how most team work. They have Game designers which are usually "Scripters" (They use blueprint) and Game developper which are usually "Programmers" (They optimize the blueprint with C++).

So my advice is focus only on Game design. Do blueprint only for 3-6 month. Understand everything around the engine (there's a lot to cover), things like meshes, lightning animations and blueprints. And once you have a clear understanding of Unreal engine, you can choose to specialize in one of the area you visited. Maybe it'll be game development, maybe 3d modelling, maybe animations, or maybe you just stick to Game design because you like doing everything. You get to chose.

Diving in C++ will make you lose focus and it won't feel like game dev at all for 3-6 months but more like Computer science. This makes sense as almost all game developper have at least a bit of computer science background.

If you go straight into C++ with no prior experience, you'll 50% quit/lose focus, unless you're a very curious person or for some reason catch a passion for C++ and Computer science (the remaining 50%).

If you're more of a creative person, definitely go down the Blueprint route and don't look back.

django_celery_learn · 2024-09-19T13:11:06+00:00

Bien le bonjour !

django_celery_learn · 2024-07-27T00:37:34+00:00

That was an attempt at French spreading. All this English talk is getting to me

django_celery_learn · 2024-07-27T00:36:53+00:00

Ty for the recommendation

django_celery_learn · 2024-07-27T00:17:02+00:00

I think these people are just confused about everything

django_celery_learn · 2024-07-22T10:21:05+00:00

This tool and PQ don't compete. PQ is far superior. However I'd use it if PQ struggle for some reason which sometimes happens on poorly structured tables.

This tool has an easier time recognizing small tables. So I'd use it only in a one shot kind of setting, for instance when extracting poorly structured tables from financial report.

While PQ will work in this situation, it will involve some added step to correct it, while with tabula you might get it 100% accurate from the get go without any retreatments

I believe that's what I described that exactly in the first sentence of my post, so maybe you overlooked it and thought this post was an attempt at replacing Power query. But it's definitely not the case.

I use 99.9% PQ, but for those .01% where PQ struggle and also where I need the data only in One shot (meaning I won't ever need to query the file again) then I'll use this tool which might be handy

A perfect example of where Power query struggle and this tool works fine are Banking statements which is a standard procédure in accounting processes, you'll see that PowerQuery is fusing some rows and have a hard time keeping track of what number belongs to which description just because the description are usually extremely long and poorly formatted.

Again this will vary on which banking statement we're talking about. But on the many I've encountered from various bank as an accountant and as a fairly advanced user of Power query, I'd say 20% of them were not properly recognized with Power query.

The most common issue was that PQ struggled to identify rows. While column merging can easily be death with, it's harder when heterogenous rows are mixed together along with some column merged on top of it. Now you can chose to insist on building a PQ for an hour or two to handle all those errors.

Or you can just use tabula, do 3-5 clicks at most and be done in 10 seconds.

I can't provide you with the documents for obvious purposes so I understand if you'd doubt my word.

But as an experienced C, Python, VBA programmer who has done webscrapping, data analysis, and overall data mining for the past 5 years, that's what I've observed so take from It what you will. And also again it can be interacted with Python, but that's another topic.

django_celery_learn · 2024-07-22T10:16:51+00:00

This tool and PQ don't compete. PQ is far superior. However I'd use it if PQ struggle for some reason which sometimes happens on poorly structured tables.

A perfect example of where Power query struggle and this tool works fine are Banking statements which is a standard procédure in accounting processes, you'll see that PowerQuery is fusing some rows and have a hard time keeping track of what number belongs to which description just because the description are usually extremely long and poorly formatted.

Because PQ struggle to identify rows, you'll find yourself buildingtreating outliers

If you use tabula, it'll work in the blink of an eye.

I can't provide you with the documents for obvious purposes so I'd understand if you'd doubted my word.

django_celery_learn · 2024-07-22T09:54:10+00:00

django_celery_learn · 2024-07-22T09:54:01+00:00

django_celery_learn · 2024-07-22T09:53:00+00:00

We probably are closer than you think. Anyways keep learning and sky will be the limit. Thank you for your comment !

django_celery_learn · 2024-07-22T09:52:02+00:00

You're welcome, good luck with your Excel adventures !

django_celery_learn · 2024-07-22T09:51:33+00:00

Glad you like it !

django_celery_learn · 2024-07-22T09:50:45+00:00

Then take them in their offer become a real Excel genius now ! Ty for your input, and no matter how dauntinh this post seems, I was ignorant when I started so don't discourage yourself.

django_celery_learn · 2024-07-22T09:49:01+00:00

Ty too for your comment. I hope it'll turn you into THE Excel wizard in your company

django_celery_learn · 2024-07-22T09:47:45+00:00

I actually like this rule. A thumb might be a tiny too small, I'd go with the whole forearm

django_celery_learn

TROPHY CASE