AI: My very own personal GPT

I'm thrilled to introduce a groundbreaking addition to my professional profile: my very own personal GPT!


This advanced AI can interactively provide insights about my skills, projects, and experiences, making it easier than ever to get to know my professional background and what I bring to the table. It's like having a dynamic, real-time CV that you can engage with directly.

Whether you're a recruiter, a potential collaborator, or just curious, you can explore my personal GPT.

 
I'm excited about the potential of AI to transform the way we present ourselves and connect with opportunities. This is just one example of how technology can be leveraged to make our professional lives more efficient and engaging.

Let's embrace innovation together! And have fun chatting with my virtual self (I hope I trained it well!), and if you decide to use the conversational mode, remember this is not my real voice!

Cyrille (the real one)

 

Campus BioTech: Life Sciences Café+Croissant before the summer

I had an absolute blast talking about the future of AI-powered scientific visualization. Can't wait to fully immerse ourselves in this thrilling new era of scientific communication!

 

More information here.

BATbern53 - Storage vs Compute

I had an incredible time presenting the challenges of rendering highly detailed large models using the techniques I've developed over the past decade at Blue Brain.

A big thanks to all the attendees and for the fantastic discussions!

Abstract:

Scientific exploration has increasingly shifted from traditional storage-centric approaches to compute-centric methods, leveraging advanced software for data integration, analysis, and interactive visualization of vast scientific datasets.

 

To address this need, Blue Brain developed and open-sourced Blue Brain Brayns, a technical platform for the visualization of in-silico datasets, which later gave birth to the Blue Brain BioExplorer.

Initially created to tackle key scientific questions related to the Coronavirus and to deliver a powerful visualization tool, the BioExplorer now excels in reconstructing, visualizing, exploring, and detailing the structure and function of biological systems, from molecular systems up to the full brain.

In this highly visual presentation, I will demonstrate how I architected and built the application that EPFL's Blue Brain Project utilizes to generate high-quality, high-fidelity images and movies, along with interactive and immersive experiences of the digital reconstruction of the rodent brain. By prioritizing computational efficiency over traditional storage, we enable real-time manipulation and exploration of large datasets.

 

 

 

 

Additionally, I will present a few examples of how AI is a game changer, solving problems that were almost impossible to solve with classic techniques. These examples will highlight the transformative impact of AI in enhancing image quality, speeding up data processing, and uncovering new scientific insights that were previously beyond our reach 

 

 

More information about BATbern53 : https://www.berner-architekten-treffen.ch

AI: Unleashing Generative AI for Stunning Scientific Visualizations! Part 3

I'm super excited to share that I've created a new tool to make your experience with the Blue Brain #BioExplorer a whole lot easier: the GPT Python Code Assistant. This nifty assistant uses OpenAI's GPT-4 to give you a smooth, intuitive way to interact with the BioExplorer platform, so you won't need to dive into the documentation anymore.

With this assistant, you can just chat with the GPT in plain language to get the help you need. Whether you're a seasoned researcher or a newcomer, this tool is here to make your workflow more efficient and enjoyable.

https://chatgpt.com/g/g-EwAj4evNu-bioexplorer-code-assistant

The GPT Python Code Assistant comes packed with awesome features. You can interact with it in natural language, so instead of sifting through documentation, you just ask your questions and get clear, concise answers and code snippets tailored to what you need. If you run into coding issues, the assistant can help you debug, optimize, and write Python code specific to the Blue Brain BioExplorer. Plus, it's continuously updated with new features, fixes, and improvements, so you always have the latest info and capabilities at your fingertips. It's designed to be user-friendly, offering an intuitive interface that lets you get help without disrupting your workflow.

Creating the GPT Python Code Assistant is a big step forward in making complex data exploration and analysis more accessible. I'm excited to share this with you and can't wait to see how it enhances your experience with the Blue Brain BioExplorer.

Stay tuned for more updates as we keep improving and expanding the GPT assistant. Happy exploring!

AI: Unleashing generative AI for stunning scientific visualizations! Part 2

I have been struggling forever to map textures onto neurons. It's a challenge that has plagued me throughout my journey at Blue Brain, particularly with the intricate details of ray-tracing. The traditional approach to texture mapping involved meticulous UV mapping, which demanded time, patience, and a deep understanding of 3D modeling techniques. This complex and often frustrating process has been a significant roadblock in my work, as rendering realistic textures onto such intricate models like neurons was both time-consuming and demanding.

But recently, generative AI has introduced a game-changing alternative. By learning from vast datasets of visual information, including natural textures, AI can produce mappings directly onto 3D models without the need for traditional UV mapping. This new approach mirrors the methods of traditional artists who create works based on their interpretation of the world around them, offering a more intuitive, streamlined workflow.

For me, this transition requires rewiring my brain, shifting from manual, technique-driven methods to a more intuitive, AI-assisted process. Yet, I see potential in combining the best of both worlds: the craftsmanship of traditional 3D design and the innovative capabilities of AI-generated art.

This hybrid approach offers an exciting future for 3D design, where human intuition and AI's learning capabilities can work together, creating lifelike textures and realistic models that push the boundaries of digital art. By merging these disciplines, designers can overcome challenges and unlock new creative possibilities, allowing for more dynamic and lifelike renderings than ever before.

AI: Unleashing generative AI for stunning scientific visualizations! Part 1

In the world of scientific research, visualizing complex data is crucial. With generative AI and tools like the open-source Blue Brain BioExplorer that I developed at EPFL, and Adobe's Firefly, it's now easier to create captivating scientific visualizations while using the real data as a source to the final composition.

Generative AI automates the process, saving time and enabling experimentation with different visual styles. This empowers artistic creativity, communication and outreach efforts.

As generative AI continues to evolve, the possibilities for visualizing complex scientific concepts are limitless.

Reach out if you wish to explore this exciting frontier of creativity and discovery.

https://github.com/favreau/BioExplorer

https://firefly.adobe.com

HUG: When Epilepsy Leads to Mystical Ecstasy

I'm absolutely thrilled to share that I've had the privilege of producing an image for PICARD Fabienne from HUG - Hopitaux Universitaires de Genève that highlights her fascinating research on ecstatic epilepsy.

The presentation titled "Quand l’épilepsie amène à l’extase mystique" (When Epilepsy Leads to Mystical Ecstasy) offers a captivating journey that delves into the intricate workings of the brain, specifically within the framework of the predictive coding theory. This theory suggests that the brain generates predictions about incoming sensory information and constantly updates these predictions based on new data. Through the lens of this theory, the presentation explores how epilepsy can lead to mystical experiences, altering the brain's predictive processes.

I encourage you to take a moment to watch the accompanying video and delve into the mesmerizing discoveries awaiting within. 

Neuron morphologies: https://neuromorpho.org

Wishing you an extraordinary 2024!

Throughout the last decade, I embarked on impactful collaborations, ranging from Harvard Brain Magazine to the realms of molecules and subatomic worlds, computational neuroscience, and virology, with a specific focus on unraveling the complexities of COVID-19. This marked the initiation of a distinctive scientific visual exploration in these intricate domains, involving collaboration with exceptional minds, intensive coding for CPU and GPU architectures, and the application of cutting-edge ray tracing techniques for sophisticated visualizations. Our findings were concurrently disseminated through scientific publications, contributing significantly to the field and making the journey of conveying our scientific discoveries through advanced visuals truly exhilarating.

This body of work not only made substantial contributions to scientific publications but also afforded opportunities to showcase our achievements at prestigious venues such as the Centre Pompidou in Paris, as well as the CCCB in Barcelona and Madrid. These exhibitions underscored the global relevance and significance of our research.

As the Blue Brain Project approaches its conclusion in 2024, I eagerly anticipate new ventures. Beyond my daily 4km swim, my commitment to accuracy and visual excellence remains pivotal in the development of software for distributed and high-performance computation, data visualization, exploration, and communication.

EPFL: Unveiling the Potential of the GPU-accelerated Signed Distance Field Technique in computational neuroscience

The intricacies of the brain, a marvel of complexity, encompass billions of neurons, astrocytes, and a network of elaborate blood vessels. Unraveling the structure and interactions within this intricate organ is paramount in the realm of neuroscience.

A powerful technique that has emerged in recent years is the application of signed distance fields (SDFs) to construct realistic shapes directly from raw data, eliminating the need for meshes. These shapes are dynamically generated at rendering time from simple primitives such as spheres, cylinders, cones, etc.

The signed distance field technique excels in generating high-fidelity graphics that faithfully represent the complexities of biological structures. By encoding distance information for each point in space, this technique facilitates the creation of intricate and realistic 3D reconstructions directly from raw data (.h5 or .swc).

A notable advantage of employing signed distance fields is their capacity to enable interactive exploration. Researchers can seamlessly navigate through reconstructed 3D models of neurons, astrocytes, and blood vessels, gaining a dynamic and immersive understanding of their spatial relationships. This interactive feature enhances the exploration process, fostering a more intuitive and insightful analysis of the data.

The utilization of the signed distance field technique to visualize and explore neurons, astrocytes, and blood vessels signifies a substantial advancement in the field of neuroscience. This potent approach, originally developed with insights from Inigo Quilez's blog, provides high-quality graphics that empower researchers to study the intricacies of the brain's architecture.

The implementation of the signed distance field technique, initially available in the Blue Brain BioExplorer CPU back-end, underwent a transformative upgrade. Over the last two days, I successfully ported the technique to GPU using the CUDA programming language and the NVIDIA OptiX ray-tracing framework. This enhancement not only accelerates the visualization process but also opens new horizons for real-time, high-performance exploration of intricate neural structures. This collaborative fusion of cutting-edge technologies ensures that the exploration of neural intricacies remains at the forefront of scientific discovery, propelling our understanding of the brain into new dimensions.

• Blue Brain BioExplorer: https://github.com/BlueBrain/BioExplorer

• Inigo Quilez - articles- distance functions: https://iquilezles.org/articles/distfunctions/

• SDF Tracing visualization: https://www.shadertoy.com/view/lslXD8

 

EPFL: Interactive visualization of the Fusion Reactor Tokamak plasma

In my dedicated efforts to advance nuclear fusion, I embarked on a journey to translate conceptual ideas into tangible actions. This mission commenced with the creation of a test dataset, meticulously crafted with insights derived from engaging discussions within our team. To expedite the visualization and exploration of this data, I turned to the remarkable open-source application known as BioExplorer.

BioExplorer, originally developed for biological datasets, proved to be an invaluable asset in our venture. While its roots lay in the realm of biology, its adaptability and versatility allowed it to seamlessly integrate with our nuclear fusion research. This application, once primarily designed for biological data, had evolved to accommodate and process a wide range of scientific datasets, transcending its initial domain.

In the context of nuclear fusion, the core challenge lies in modeling the behavior of superheated plasma, the fuel for this revolutionary energy source. To visually represent this complex phenomenon, I envisioned the plasma as an array of particles, with each particle intricately characterized by its position and direction. The direction vector of each particle not only represented its position but also served as a direct indicator of the particle's charge, a crucial factor in the fusion reaction.

Efficiency was paramount in this ambitious undertaking, and BioExplorer played a pivotal role. This open-source application, known for its adaptability, provided a user-friendly platform to visually explore and analyze the scientific datasets, irrespective of their origin. It allowed us to gain valuable insights and a deeper understanding of the plasma's behavior, further propelling our research forward.

To ensure real-time visualization of the plasma's behavior, I harnessed the formidable processing power of Graphics Processing Units (GPUs). These GPUs were thoughtfully optimized with a tree-based acceleration structure, making them an ideal choice for handling the intricate calculations required for real-time visual representation of the plasma's behavior.

Perhaps the most astonishing aspect of this project was its efficiency. What might seem like a Herculean task was accomplished in no more than two days of relentless work. This achievement not only underscores the power of modern computational tools but also highlights the immense potential of nuclear fusion as a clean and virtually limitless energy source, hinting at a future where our energy needs may be met sustainably and efficiently, with the invaluable assistance of open-source applications like the versatile and adaptable BioExplorer.

Check out the BioExplorer source code and the Python Jupyter Notebook used to create the image above.

CERN: Particles Composition and Interactions Using the Nuon Model

Drawing inspiration from René Brun's remarkable publication titled "Particles Composition and Interactions Using the Nuon Model" I embarked on a venture to visualize the magnetic fields engendered by sub-particles within the realm of collisions.

 

Although the data I employed differs from that presented in the paper, I found the concept of moving away from the conventional depiction of particles as simple spheres and instead illustrating their genuine magnetic fields to be captivating.

 

 

With the computational capabilities readily accessible on ordinary consumer PCs today, it is now possible to calculate these fields in real-time, opening up novel avenues for visualizing and exploring the intricacies of the sub-atomic world.

 

Try it for yourself!! https://particle-physics.netlify.app

Full source code: https://github.com/favreau/NuonModelVisualizer

HARVARD: The Harvard Brain

So proud to appear in the Harvard Brain Spring 2023 issue.

Studies In Silico: An Interview With Cyrille Favreau On EPFL’s Blue Brain Project, by Lara Ota, Buse Toksöz, and Kei Hayashi

http://www.theharvardbrain.com/spring-2023-8203lara-ota-buse-toksoumlz-and-kei-hayashi.html

EPFL: Blue Brain BioExplorer goes RTX!

Exciting news! I just released the version 1.6.0 of the Blue Brain BioExplorer. It now goes #NVDIARTX with OptiX backend compatibility, #AI denoiser, and new stereo camera! High-quality rendering of scientific datasets and #VR use-cases with pure ray-tracing.

Open source code: https://github.com/BlueBrain/BioExplorer