#mathematic (vfx)

[tangibletechnomancy]

The AI Boom and the Mechanical Turk

A hidden, overworked man operating a painting, chess-playing robot, generated with the model Dreamlike Diffusion on Simple Stable, ~4 hours Created under the Code of Ethics of Are We Art Yet?

In 1770, an inventor named Wolfgang von Kempelen created a machine that astounded the world, a device that prompted all new understanding of what human engineering could produce: the Automaton Chess Player, also known as the Mechanical Turk. Not only could it play a strong game of chess against a human opponent, playing against and defeating many challengers including statesmen such as Benjamin Franklin and Napoleon Bonaparte, it could also complete a knight's tour, a puzzle where one must use a knight to visit each square on the board exactly once. It was a marvel of mechanical engineering, able to not only choose its moves, but move the pieces itself with its mechanical hands.

It was also a giant hoax.

What it was: genuinely a marvel of mechanical engineering, an impressively designed puppet that was able to manipulate pieces on a chessboard.

What it wasn't: an automaton of any kind, let alone one that could understand chess well enough to play at a human grandmaster's level. Instead, the puppet was manipulated by a human chess grandmaster hidden inside the stage setup.

So, here and now, in 2023, we have writers and actors on a drawn-out and much needed strike, in part because production companies are trying to "replace their labor with AI".

How is this relevant to the Mechanical Turk, you ask?

Because just like back then, what's being proposed is, at best, a massive exaggeration of how the proposed labor shift could feasibly work. Just as we had the technology then to create an elaborate puppet to move chess pieces, but not to make it choose its moves for itself or move autonomously, we have the technology now to help people flesh out their ideas faster than ever before, using different skill sets - but we DON'T have the ability to make the basic idea generation, the coherent outlining, nor the editing nearly as autonomous as the companies promising this future claim.

What AI models can do: Various things from expanding upon ideas given to them using various mathematical parameters and descriptions, keywords, and/or guide images of various kinds, to operating semi-autonomously as fictional characters, when properly directed and maintained (e.g., Neuro-sama).

What they can't do: Conceive an entire coherent movie or TV show and write a passable script - let alone scripts for an entire show - from start to finish without human involvement, generate images with a true complete lack of human involvement, act fully autonomously as characters, or...do MOST of the things such companies are trying to attribute to "AI (+unimportant nameless human we GUESS)", for that matter.

The distinction may sound small, but it is a critical one: the point behind this modern Mechanical Turk scam, after all, is that it allegedly eliminates human involvement, and thus the need to pay human employees, right...?

But it doesn't. It only enables companies to shift the labor to a hidden, even more underpaid sector, and even argue that they DESERVE to be paid so little once found out because "okay okay so it's not TOTALLY autonomous but the robot IS the one REALLY doing all the important work we swear!!"

It's all smoke and mirrors. A lie. A Mechanical Turk. Wrangling these algorithms into creating something truly professionally presentable - not just as a cash-grab gimmick that will be forgotten as soon as the novelty wears off - DOES require creativity and skill. It IS a time-consuming labor. It, like so many other uses of digital tools in creative spaces (e.g., VFX), needs to be recognized as such, for the protection of all parties involved, whether their role in the creative process is manual or tool-assisted.

So please, DO pay attention to the men behind the curtain.

[sirfrogsworth]

In this one I tried to blend my LED light panels with the outdoor light.

And then I thought I'd try to explore the world of LUTs a bit more.

A "look up table" is a special mathematical model that emulates a certain color profile. In the early days of digital effects you had to scan film into the computer, do your VFX wizardry, and then print back onto film. They would use a film emulation LUT to make sure the output looked the same as the original developed film.

Now LUTs are often used to make digital photos and video footage look like various film stock. They are different than color grading because they can create a consistent look throughout every scene. Color grading can require tweaks every time there is a lighting change, but LUTs are much more adaptable. LUTs aren't a substitute for color grading, as both are usually necessary. But they can be a great shortcut to get you a certain look and they can also help you get consistency even when you use different cameras with different color science.

The LUT I used for the second photo was for Kodak 5205 film stock. Which is the same film stock they used on the Taken movies.

Did I look like I had a very particular set of skills?

[abbas6355]

Drake - First Person Shooter ft. J. Cole

Director - Gibson Hazard EP/Producer - Liam Akiva EP - Christian Tyler Executive Producer /Creative Direction- Drake, qJamil "Big Juice" 'Davis Creative Direction - Jack Bannon & Reduciano  Production Company - House of Hazard x Denim Line Producer - Cam Frengopoulos & Alex Dall’Orso Associate Producer - Jackie De Niverville Production Manager - Trevor Evoy Production Coordinator - Amber Warus Cinematographer - Bobby Shore 1st AC - Dave Stuart B-Unit Director - Nick Dean Production Designer - Electa Porado Gaffer - Jordan Heguy Key Grip - Todd N Thompson Editors - Gibson Hazard & Jack Bannon Sound Design - Chris Smith & Jack Bannon 3D Animation Lead - Reduciano VFX - Mathematic  VFX - Karen Arakelian VFX - Pendulum VFX - Scissor Films VFX - Black Hat VFX - Aid6n.edits Colourist - Dante Pasquinelli Graphic Design - Alessandro Comotti Special thanks to Scotiabank Arena, House of Hazard, OVO, Dreamville and Vanessa Hoffer

full video

[maacsatara]

Understanding Dynamics: Cloth, Hair, and Fluid Simulations

The field of animation and visual effects (VFX) has seen significant advancements over the years, with dynamics simulations being one of the most critical aspects. Dynamics refer to the realistic simulation of movement and interactions of objects that behave according to the laws of physics. Aspiring artists can gain expertise in this area by enrolling in the best animation institute in Pune, which offers comprehensive training in dynamics. Among these, cloth, hair, and fluid simulations stand out due to their complexity and relevance in creating lifelike animations. Whether it’s the fluttering of a character’s cape, the natural bounce of hair, or the mesmerizing flow of water, these simulations are pivotal in delivering immersive experiences in movies, games, and commercials.  

Cloth Simulation

Cloth simulation focuses on recreating the behavior of fabrics in various scenarios, such as movement, stretching, and interaction with other objects. This involves complex mathematical models and algorithms to ensure realism.  

1. Core Principles  

Cloth behaves based on its material properties like weight, elasticity, and friction. Simulating it accurately involves solving equations related to physics and geometry. Systems like mass-spring models and finite element methods (FEM) are commonly used to calculate cloth dynamics.  

2. Applications in Media

In animated movies and games, cloth simulation is critical for creating realistic costumes. For example, in Disney's *Frozen*, Elsa’s dress moves naturally as she walks, thanks to detailed cloth simulations.  

3. Challenges

One of the biggest hurdles in cloth simulation is balancing realism with computational efficiency. Realistic fabric behavior requires heavy calculations, especially in complex scenes with multiple garments interacting with wind, water, or other forces.  

4. Software for Cloth Simulation

Tools like Marvelous Designer, Houdini, and Maya’s nCloth are widely used for cloth simulation. These programs offer parameters to control fabric types, gravity, and collisions.  

Hair Simulation

Hair simulation is another intricate aspect of dynamics, involving thousands of individual strands that must move cohesively while responding to environmental forces like wind and gravity.  

1. Understanding Hair Dynamics

Hair simulations are governed by principles such as strand stiffness, weight, and drag. To achieve realism, animators simulate each strand or clump as a physical object that interacts with forces around it.  

2. Techniques Used

Simulating hair often relies on particle-based systems or curve dynamics. Particle systems simulate hair as individual particles connected by constraints, while curve dynamics model hair as curves with defined physics properties.  

3. Iconic Examples  

Disney’s *Tangled* revolutionized hair simulation with Rapunzel’s 70 feet of flowing, interactive hair. The studio used a unique software called Medusa to simulate hair that could interact with the environment and character movements seamlessly.  

4. Challenges in Hair Simulation

Hair simulations can be computationally expensive due to the sheer number of strands and their complex interactions. Animators must also ensure that simulated hair blends seamlessly with the character’s movements and emotions.  

5. Tools for Hair Simulation

Programs like Blender, Houdini, and Maya’s XGen are popular for hair simulations. These tools allow artists to design, groom, and animate hair with customizable properties.  

Fluid Simulation  

Fluid simulation is one of the most visually stunning aspects of dynamics, focusing on recreating the behavior of liquids, gases, and fire.  

1. Key Properties of Fluids

Fluids are defined by properties like viscosity, density, and surface tension. Simulations must account for these variables to replicate natural behaviors such as water ripples, splashes, or fire flickering.  

2. Methods of Simulation

Fluid simulations often use grid-based methods like Eulerian grids or particle-based approaches such as Smoothed Particle Hydrodynamics (SPH). These techniques allow animators to calculate fluid behavior in three-dimensional space.  

3. Applications in Media

From raging ocean waves in *Moana* to the fiery explosions in action movies, fluid simulations bring realism to scenes that would otherwise be impossible to film practically.  

4. Challenges in Fluid Simulation

Simulating fluids requires high computational power, especially for large-scale effects like oceans or floods. The interaction of fluids with other objects, such as characters or terrain, adds another layer of complexity.  

5. Popular Tools

Houdini, RealFlow, and Blender’s Mantaflow are leading software for fluid simulations. These tools enable artists to design everything from realistic water splashes to intricate smoke patterns.  

Integrating Dynamics in Production

1. Collaboration with Other Departments  

Simulations often require close collaboration with animators, riggers, and lighting artists. For instance, cloth simulations must match the character's movements, while hair dynamics need to respond to wind or environmental changes.  

2. Optimization Techniques

To balance realism and efficiency, studios use techniques like level of detail (LOD), where simulations are more detailed in close-up shots and simplified for distant ones.  

3. The Role of AI in Dynamics  

Recent advancements in AI and machine learning are transforming dynamics simulations. AI-powered tools can predict fabric or hair behavior faster, reducing computational load and enhancing accuracy.  

Future Trends in Dynamics Simulations

1. Real-Time Simulations

With the rise of virtual production and gaming, real-time dynamics are becoming essential. Technologies like Unreal Engine enable real-time cloth and fluid simulations, revolutionizing interactive media.  

2. Integration with AR/VR

In augmented and virtual reality, dynamics simulations enhance user immersion by providing lifelike interactions with virtual environments.  

3. Sustainability in Rendering

As simulations become more advanced, optimizing computational resources is critical to reduce the environmental impact of rendering processes.  

Conclusion

Cloth, hair, and fluid simulations are at the heart of modern visual storytelling, pushing the boundaries of what is possible in animation and VFX. Aspiring artists looking to master these skills can benefit greatly from training at an animation institute in Pune, where they can learn the latest techniques and tools. As technology advances, these dynamics will continue to evolve, enabling artists to create even more breathtaking and realistic worlds. By mastering these simulations, creators not only enhance visual appeal but also bring authenticity to their stories, bridging the gap between reality and imagination.

[vfxexpress]

The Walking Dead – Daryl Dixon: VFX Breakdown by Mathematic Film

The first season of The Walking Dead: Daryl Dixon showcases stunning visual effects crafted by Mathematic Film. Witness the chaos as the undead meet their doom, and dive into the intricate process behind these spectacular scenes.

[raisedbyelectronics]

"Just pick up a pencil."

I honestly disagree with this sentiment.

Let's start with the collateral damage.

There is generative art out there that isn't made through GANs or other similar methods. Reddit's r/generative is home to this kind, made without either lifted training data or a prompt-based workflow. Just math, computer wizardry, and human ingenuity. You can make beautiful fractals, flowing shapes, etc., and you can take as many liberties as you want. Yet this unrelated art form happens to share the name "generative."

Then there's procedural effects in 3D digital art, animation, VFX, and CAD. I see that form of randomness as no worse than the natural imperfections that result from a pencil or paintbrush.

Even stabilization tools on apps like ProCreate have come under fire.

People hear about "Photoshop's plagiarism algorithms" and think the whole app uses them, or that Gaussian blur algorithms use content from Google Images.

I think a lot of the "pick up a pencil" crowd are missing the point and vilifying all computer-aided art forms as soulless, or making points tangential to the overall AI debate.

I can follow the logic behind a lot of arguments over the collection of training data for "true" AI art made with GAN and stable diffusion-based models, or the skill level of prompt engineering. (But I don't agree with banning or shaming it at all, or even with the idea that it's wrong, as enforcing the copyright of images from a Google Search would inadvertently ban many memes, and stable diffusion is way more complicated than a simple collage)

But mathematical or random models, liberties left to the computer, and digital art in general, are unfairly vilified in the process.

It's okay to pick up a pencil. But you can pick up a stylus, pick up your finger and put it on whatever control is in reach, etc., or pick up your technical intuition in one way or another.

And I also would love to see more ML-based AI that gives an artist even more liberties, and that discloses, for example, what it was trained on (perhaps consensual algorithms or mass libraries of stock photography).

Hypothetically, not all "true" AI has to be based on prompt engineering, or use it as the sole means of calling up images – and prompt engineering can also be used for finer details, etc. Perhaps as a way of generating the textures of 3D polygon animation.

But the goalposts keep moving.

This AI was trained on images in the public domain/that the company has permission to use!

Well, did the artists know at the time?

Well, this AI was trained on images expressly submitted to us!

But still, you're enabling non-artists to make fake art!

How?

Well, all you're doing is typing in a paragraph!

But this system has more areas to type in what you want, not just a single box!

But still, writing isn't making art!

Okay, this system more closely resembles a drawing program that turns your basic sketches or lasso fills into whatever you want them to be – the composition is yours!

But that's too easy!

Okay, this system just uses a really good ML algo to imitate brush strokes of a paintbrush!

Well....

"Why can't we use computers to simplify the boring stuff instead of simplifying the fun stuff?"

I've heard this so many times... implying that making art with a computer isn't fun, or that using a computer to automate or randomize anything is an insult to those who "took the time."

A few people speaking about AI music seem to also criticize things like random LFOs, random note generators, etc., that influence the sound design or composition of a production in a random way, though still ultimately on the terms of the producer. It's still a craft of love, and a great way to make cool R2D2 sounds or glitchy percussion.

Or speak of live musicians as the victims of AI music – something that as an electronic musician, I've heard about my hobby in general. That quantizing and pitch correction, or any kind of post-modification of any performance, is dishonest or disrespectful to those who "took the time" to learn to "properly" play. As if music were a sport, not an artform with many ways of practice. That gridding things in or arranging stock samples (a term that has two meanings: either arranging single notes or adding stock loops, or even bits of other songs) is dishonest. A lot of people don't even know that you can program in original melodies in electronic music, or skip samples entirely and use geometric or electronically-generated waveforms.

As if we don't take the time to develop our sounds and mix and match a variety of nonstandard, yet technical, areas, even if we leave some stuff to the computer and/or a stock loop library (or not... I tend not to use the latter).

As if people making any kind of procedural medium on a computer are only doing it because they're inartistic.

As if someone's personal opinion that 3D art with procedural FX, generative mathematical art, the music of Trovarsi, or anything with some randomization is soulless... makes it so.

As if they could do better just sitting down at the tools of the "talentless hacks'" trade.

As if anyone can sit down and make anything on r/generative, or even use Photoshop's Generative Fill, effectively on the first go.

One friend of mine thought electronic music was talentless and unoriginal, and that it was all "soulless and sterile and made from stolen loops"... I offered her 10 minutes of time with my laptop and a pair of headphones... she didn't want to try it out...

Speaking of that, when GarageBand was first announced to the general public, Steve Jobs mostly focused on the stock loops, even though you could make your own loops, record performances all the way through, or just grid things in... or use third party plugins.

I can see a similar trend happening with ML-based AI.

People will take the time to make it, and people will find it worth their time to consume it.

The opposite of "electronic" isn't "real". This is the force of thunder, thought, magnetism, chemistry, and emotion itself.

The opposite of "computer" (adj.) isn't "human." Humans designed computers.

And a lot of more "computery" art and music is very appealing to me. Am I a robot? No, but I'm of the species that designed them, and can tell you first-hand that creativity is very... complicated. Not that I don't think we should have it, but that it's ultimately in the eye of the beholder.

You didn't plan out each imperfection of your pencil line.

Nor each variation in harmonic overtone content or waveform each time you slap your bass.

Nor were you the first to draw a person, photograph the LA River, or tap out a clave rhythm.

Nor do comic book artists generally spend the same time on a single frame as a realist painter does on a whole painting... but that just lets them make more and create a whole new art form. And some comic book artists do slave away on each detail – or draw stick figures and still make effective comics. Or just take pictures for a photo comic. Or use stabilization. Or generative (mathematical) backgrounds.

Not too long ago, calculators were controversial in STEM classrooms. Now, many classes outright require them.

Not too long ago, spell check was lamented by English teachers. Now, many will outright encourage its use in typed essays, or have students do assignments on Canvas with it turned on.

The general attitude for using Wikipedia for research has evolved from "never use" to "use with skepticism and don't cite directly for school, but it's a great 'springboard' to find more info".

And typing has pretty much replaced cursive's role in high schools.

It's all how you look at it.

I will not be convinced that my computer is evil or unhealthy.

[chipped-chimera]

Ok sorry but hold on a sec while I get real neuroscience/social psychology-ey about this.

So I have been a good 'drawer' since I was very young, but I also have a keen interest in psychology for mental health (and honestly autism) reasons. I think one of the most formative things I've ever done in my young life with regards to my perspectives with art, was read Drawing on the Right Side of the Brain by Betty Edwards. At like, 13 (see what I mean about the autism? lol).

Did I need this book considering I'd gotten into my high-school with a literal art scholarship with my demonstrated skill? No. But I was interested in the neuroscience perspective of art + if there was anything I could draw from it that would help my own art improve.

I don't remember the specifics, but my main takeaways were this:

Absolutely no one pops out of the womb with innate art skill. Like language and reading, it is a developed skill, not born out of biological necessity. Natural talent doesn't exist.

Because skill in art tends to be devalued in western society across the board ('starving artist' mentality, how shittily VFX artists have been treated for years, OpenAI already knowing how to ask for permission to make an AI ethical because they were scared of the music industry but threw that out the window crawling for training data for stable-diffusion, how art is constantly stolen and reposted with 'credit to the artist!' without actually linking or crediting said artist - LITERALLY TAKE YOUR PICK) being artistic is not encouraged. As children we all draw (to make art is human, I sincerely believe this), but there will be a point where it goes from being an encouraged part of child development to 'this is a childish waste of time' and actively discouraged as a poor career choice. If you wondered why most people's artistic skill level is 'frozen' and can only draw like an 8 year old - this is why.

The reason people remain stuck in this frozen state is lack of education, because our societal structure doesn't emphasize the use of art. It's considered 'optional' or a 'hobby'. It's not a critical part of the curriculum like math or english. Reading and mathematics are not innate skills either, they have to be trained. The difference here is you straight up just did not get any education to make progress.

As an adult, we tend to get discouraged when we can't draw well at all for all the aforementioned reasons and give up (or if you're extra scummy, make AI art and claim artists are 'gatekeeping' as your excuse) but the only difference between you and someone who can draw, like me, is I grew up in an environment where drawing was encouraged, not torn down as a 'childish activity'. So I've literally spent most of my childhood practicing, that's the only reason I draw better. I just have more years of practice under my belt.

There's no such thing as talent in art. You might be able to pick colours well instinctively, heck you might be a tetrachromat (like I suspect I am) giving you an advantage that is innate and biological. But beyond that I honestly believe the only talent you can have is being stubborn and doggedly aiming for and perusing your goals, even when you feel discouraged. You will always see what is wrong in your own art, no matter if you started drawing seriously yesterday or 30 years ago. It's what I call 'the curse of the artist's eye' - but it is a good thing, because it means you still have room for improvement! You still have things to learn! If you think something about your art is shit, use that as motivation. Learn from the experience. Go find drawing books about the thing you're weak at drawing. Come at it from a different angle, utilize references. Keenly observe what you're looking at.

Also lastly, the most important one: the biggest barrier to improvement for most people is having to wind back years of ingrained symbology and actually start seeing. What do I mean by this? When you draw a portrait of yourself, ears, eyes, nose, etc. you aren't drawing your face at all - you're drawing a collection of learned symbols, the representation of an eye, a nose, a mouth, that you may have learned at 8 years old - then never progressed further. To break out of this you have to stop seeing 'eyes' and 'noses' you have to start seeing shapes and lines. One of the activities to demonstrate this in the book was to take a picture of a still life scene or something and do your best to draw it. Then take that picture, flip it upside-down and draw it again but upside-down. Generally comparing the two pictures, the upside-down version always had a drastic improvement - because you basically forced your brain out of using recognized, ingrained symbols and had to rely on shapes and structure instead.

Also as a side note: Having ingrained symbols isn't a bad thing - it's the backbone of artist style. But this is why most professional artists, even with highly stylized style recommend learning anatomy and doing life drawing first - because they have spent time learning to understand how things actually look and improving their skill, before basically developing a symbolic shorthand. I can usually tell my symbolic associations are getting too strong or I've 'forgotten' how to draw things when I start getting a lot of 'same face syndrome' in my art. That's usually a sign I need to go hit the books, practice drawing from life again so I can remember that. I don't just practice drawing eyes once and never do it again - I probably do a refresher, at minimum, once a year. And each year it gets a bit better.

So that's it. Talent doesn't exist, everyone can draw - all you gotta do is be stubborn enough to keep learning. Go forth and draw shit!

No really, this is literally it - in my lifetime I've infected at least three people with the drawing bug telling people this, girl in my italian class went from going 'I wish I could draw' to sitting next to me in fine arts in my final year of school. Just practice dude - and be stubborn about it.

truly the best thing to say to someone who self-deprecatingly tells you they "can't draw" is "why?"

[inspirationinbadthings]

ADIDAS "REMEMBER THE WHY" from Norm Li, csc on Vimeo.

Client: Adidas @adidas @adidasbasketball Prod Co: Love Song @lovesongfilms Agency: Johannes Leonardo @wearejl Dir: Illimitéworld @illimiteworldtv EP: Kelly Bayett @kellybayett EP: Daniel Wolfe @Judedanielwolfe EP: Deannie O’Nell @deannieo Head of Prod: Paige Kauffman @thatgirlpk Producer: Elise Tyler @snackelise Talent: Mekhi Kimble @mekhi_kimble Music: Flying Lotus @flyinglotus DP: Norm Li, csc @norm_li PD: Andrew Clarke 1st AC: Nico Martin @cleofilms Gaffer: Drew Valenti @drewvalenti Key Grip: Nick Kirsten @babytuna_can Drone: Lightcraft @lightcraft.tv Scripty: Edye Rice Editor: Matt Carter @matt_carter Editorial: Final Cut @finalcutedit Colorist: Joseph Bicknell @josephbicknell VFX: Mathematic LA @mathematic_us VFX EP: Hadi Dahrouge @hadiwd VFX Producers: Spencer Patzman & Matthew Allen @spencerpatzman @matthewallenfilm Post Supervisor & On Set Supervisor: Vincent Blin @blincestagram Sound & Mix: Barking Owl @barkingowlsound Sound Designer: Gus Koven @guskoven Rental House: Camtec @camtec_official Film: Kodak @kodak_shootfilm

[hridaymehta]

Editing Workshop

Research and Planning - Post 20

Before beginning on working on our project, we took part in the Editing Workshop at our school, where we learnt about how editing happens, the software we were going to use for editing, etc.

We began with discussing what a pixel is. It is the tiniest square in an image holding a particular shade of colour. Multiple pixels of various shades (or even of the same shade) come together to form an image.

There are 2 types of software, ones that use pixels and ones that use vectors. A vector software enables the user to design and manipulate computer images using geometric and mathematical commands.

There are 2 other types of software, layer based and node based. Layer based software uses multiple layers of certain text, photos, videos or audio which are 'layered' one on top of the other to produce the final output, in video the topmost layer showing the most amount of significance, however in audio layers the significance is equal. A node based software links images, texts, audio and video to produce the final output, appearing to be like a tree diagram, or a flowchart.

An example of a layer based software is Final Cut Pro X, which layers different forms of media to create a product, whereas an example of a node based software is Nuke, a great software used for VFX.

Moving on, we began with learning about the Final Cut Pro X video editing software's user interface, analyzing what each panel, tool, function and button is used for whilst editing. We explored different interfaces as well, for editing, adding any VFX or SFX from their respective libraries, titling libraries, transitions and colour grading.

At first looking at the software without having an understanding, I was a little bit overwhelmed by the appearance, looking at all the tasks it could carry out. After seeing it in action with some footage our sir edited to show how it performs, I had a clearer idea of how to edit. These skills immensely get enhanced and polished during the post-production phase of the project.

I have never used MacOS or Final Cut Pro X in my life, so getting used to their interfaces and keyboard functions was a task at first, but eventually I got used to it, and its safe to say that Windows is far superior. Before learning to use Final Cut Pro X, I learned using the MacOS and getting used to it, eventually learning Final Cut Pro X.

Our sir explained to us how the keyboard is more reliable than using a mouse while editing, since you can use all 10 fingers on the keyboard, rather than 2 on the mouse. It is not just easier to master or faster to use, but most importantly the most accurate way of editing. Zooming in on the timeline to see if audio and video have synced all the way to inputting decibel values for each audio clip, even cutting or copy-pasting, I agreed with him on that, as during the workshop I may have found it hard to believe, however after actually using the editing software I was able to make a judgement, that keyboard is better.

Below are some of the evidences of us editing in Final Cut Pro X.

[ubejamjar]

I have this head canon that the majority of Imperial medici are arcanists instead of conjurers. Garleans are fearful/wary of magick, but arcanima might be more acceptable than other practices. It's aether manipulation through mathematics and geometry, something less mystical than pulling from the elements or stars. I can definitely see the Empire drilling mathematics into their conscripts' heads.

So, I think of Ajisai's scholar abilities being more geometric/technological/scientific. They would have names like coalescence, equilibrium, proof, hypothesis, sine, cosine, tangent. You know, all that stuff I never understood in high school.

I've been using Papachin's Classic SCH skill remake to get vfx that match the aesthetic.

top [ruin ii] default (left) vs. papachin (right) bottom [sacred soil] default (left) vs. papachin (right)

I just think it's neat :D

I haven't really decided what this would mean for Lily. Since she's Surito Carito's creation and bound to the job stone, she would draw off of his memories. But, since Ajisai is her summoner, it makes sense that Lily might be influenced by the way Ajisai casts.

I'm just rambling ^^;;

8/15/24

Does / would your wol(oc) have unique spells or skills?

[humbertovidalphoto]

AN OPERA OF THE MOUNTAINS - for Moncler from Jonas Lindstroem on Vimeo.

Becoming the mountain. Helicopter rides on volcano peaks, 2 meters of snow per night, chasing the rare sun, fighting the Patagonian winds, waiting, waiting, fearing defeat, suddenly we feel so small against the highest of peaks. It feels good to have brought this film home, it’s feels good to be alive. An opera of the mountains for Moncler shot in July in Patagonia, Chile starring Richard Permin.  Cinematography Matias Boucard.  Ski Operator Alexander Ryden. Drone House of FPV. Production Iconoclast / Jean Pierre Gavini, Guillaume Le Gat Service La Casa Edit Max Paschke Grade Sofie Friis Borup VFX Mathematics

[nofatclips]

Kids Turned Out Fine by A$AP Rocky from the album TESTING (samples Don't Come Home Today by Good Morning) - Director: Dexter Navy

[maacsatara]

Simulation and Dynamics: Fluid Simulation and Particle Systems

Simulation and dynamics are crucial fields in computer graphics and animation that allow artists and developers to create realistic representations of physical phenomena such as fluids, smoke, fire, hair, and cloth. Among these, fluid simulation and particle systems stand out as powerful techniques used to bring lifelike motion and effects to digital environments. These simulations are fundamental to visual effects (VFX), video games, virtual reality (VR), and scientific visualization. For those looking to master these advanced techniques, studying at the best VFX institute in Pune can provide the necessary training and skills. This article delves into fluid simulation and particle systems, exploring their principles, applications, and impact on the digital world.

Fluid Simulation: Bringing Realistic Liquids to Life

Fluid simulation refers to the mathematical modeling of liquids and gases to recreate their behavior in a digital environment. This technique is essential for creating realistic effects like water, smoke, fire, and other fluid dynamics that react naturally to forces such as gravity, wind, and pressure.

**Key Concepts in Fluid Simulation:**

1. **Navier-Stokes Equations:** Fluid simulations are based on the Navier-Stokes equations, which describe the motion of fluid substances. These equations are a set of nonlinear partial differential equations that govern the conservation of mass, momentum, and energy within a fluid. Solving these equations accurately is the key to achieving realistic fluid simulations.

2. **Grid-Based Methods:** One common approach to fluid simulation is the grid-based method, which divides the simulation space into a 3D grid of cells. Each cell stores information about the fluid’s properties, such as velocity, pressure, and density. The simulation calculates the interactions between these cells over time to produce realistic fluid motion. The most popular grid-based method is the "Eulerian" approach, which tracks the fluid’s velocity field at fixed points in space.

3. **Particle-Based Methods:** Another approach is particle-based simulation, such as Smoothed Particle Hydrodynamics (SPH). In this method, fluids are represented as a collection of particles that interact with each other based on physical laws. Each particle carries properties like mass, position, and velocity, and their interactions determine the fluid's behavior. Particle-based methods are particularly effective for simulating free-surface flows, such as splashing water.

4. **Hybrid Methods:** Modern fluid simulations often combine grid-based and particle-based methods to achieve higher accuracy and stability. Hybrid methods can capture the strengths of both approaches, allowing for detailed surface representation and realistic interaction with solid objects.

**Applications of Fluid Simulation:**

Fluid simulation is widely used in various fields, including:

- **Visual Effects (VFX) in Film and Television:** Realistic fluid simulations are used to create stunning water scenes, raging fires, smoke, and explosions in movies and TV shows. For example, the water effects in "Pirates of the Caribbean" and the fire in "Game of Thrones" were achieved using sophisticated fluid simulation techniques.

- **Video Games:** In video games, fluid simulation is used to create dynamic environments that react to player actions, such as splashing water or smoke from explosions. Although real-time fluid simulation is computationally intensive, advancements in graphics hardware and algorithms have made it possible to achieve convincing fluid effects in modern games.

- **Scientific Visualization:** Fluid simulations are also used in scientific research to visualize complex fluid dynamics, such as weather patterns, ocean currents, and aerodynamics. These simulations help researchers understand natural phenomena and make data-driven decisions.

Particle Systems: Creating Complex Effects with Simple Elements

Particle systems are another powerful tool in computer graphics, used to simulate a wide range of natural phenomena like fire, smoke, rain, dust, and magical effects. A particle system consists of a large number of small, simple particles that collectively form complex visual effects.

**Key Concepts in Particle Systems:**

1. **Emitters:** The emitter is the source that generates particles in a particle system. Emitters can have different shapes, such as points, lines, or surfaces, and can control properties like emission rate, direction, and speed. For instance, a point emitter might simulate a spark, while a surface emitter could simulate rain falling on the ground.

2. **Particle Attributes:** Each particle in a system has attributes like position, velocity, color, size, and lifespan. These attributes define the particle’s behavior and appearance. Over time, particles may change color, fade out, or follow specific motion patterns based on predefined rules or dynamics.

3. **Forces and Dynamics:** Forces such as gravity, wind, turbulence, and drag affect the motion of particles in a system. By applying these forces, developers can create realistic effects that mimic real-world phenomena. For example, particles in a smoke simulation might rise and disperse as they interact with turbulence and wind forces.

4. **Shading and Rendering:** The appearance of particles is controlled by shaders and rendering techniques. Shaders define how particles interact with light, color, and transparency, enabling the creation of different effects like glowing embers, misty fog, or glittering stars.

**Applications of Particle Systems:**

Particle systems are widely used across various industries:

- **Visual Effects (VFX):** In movies and TV shows, particle systems are used to create dynamic effects such as explosions, fire, smoke, and magical spells. For instance, the dust and debris in battle scenes or the shimmering particles in a magic spell are often created using particle systems.

- **Video Games:** Particle systems are used to create interactive and immersive environments in video games. Effects like fire, rain, snow, and smoke are simulated in real-time using optimized particle systems, enhancing the gameplay experience.

- **Virtual Reality (VR) and Augmented Reality (AR):** Particle systems are also used to create realistic and interactive effects in VR and AR applications, such as fireballs in a VR game or confetti in an AR experience.

#### The Future of Simulation and Dynamics

As technology continues to evolve, the future of simulation and dynamics looks promising. Advances in hardware, such as GPUs, and the development of more efficient algorithms are pushing the boundaries of what is possible in real-time simulation. Techniques like deep learning and machine learning are also being explored to predict and simulate complex dynamics more efficiently.

Furthermore, the integration of simulation tools into game engines and 3D software packages like Blender, Houdini, and Unreal Engine is making these technologies more accessible to artists, designers, and developers. This democratization of technology is opening new doors for creativity, allowing for more realistic and interactive experiences in digital media.

Conclusion

Simulation and dynamics, particularly fluid simulation and particle systems, play a crucial role in creating realistic and compelling visual effects in digital media. These techniques allow artists and developers to simulate complex natural phenomena and bring digital worlds to life. Learning these techniques at a reputable VFX institute in Pune can help aspiring artists master the skills required to create such effects. As technology advances, the potential for more accurate and efficient simulations continues to grow, paving the way for more immersive and visually stunning experiences in movies, games, and beyond.

[vfxexpress]

VESPER VFX BREAKDOWN - MATHEMATIC FILM

VESPER VFX BREAKDOWN – MATHEMATIC FILM

Over all Supervisor Yann Blondel CEO/VFX Producer Guillaume MarienVFX Producer Nadège MoreauVFX Supervisors Thomas Van Maele and Clément Germain Mathematic Film is the longform and episodic branch for Mathematic Studio. Vesper (released in France as Vesper Chronicles) is a 2022 science fiction film directed by Kristina Buožytė and Bruno Samper, starring Raffiella Chapman, Eddie Marsan, Rosie…

[nofatclips-home]

A la folie by Juliette Armanet extrait de l'album Petite Amie - Réalisation I ADRIEN ARMANET

[rycofx]

Shooting rays into a phyllotaxis spiral! 😵 . . . #Looping #Animation #Render #3D #Houdini #Mantra #Math #Mathematics #Art #VFX #Houdini #SideFX #Design #Digital #Abstract #Digitalart #Lighting #Ray #Raytrace #Cube #Dark #Light #Laser #laserbeam #mdcommunity #XUXOE #plsur #lucidscreen