Jerad Bitner

Hot damn, it finally happened! 🚀 Bitcoin just smashed through the psychological barrier of $100,000, hitting an astounding $103,000. For those of us who’ve been in the crypto space for years, this isn’t just another price milestone – it’s the culmination of a vision that many thought impossible when Bitcoin was dismissed as just “magic internet money.”

I’ve been having way too much fun lately! 🚀 I’ve been diving deep into the world of WebSim.ai, creating interactive web simulations that blend mathematics, physics, and visual art. Today, I’m excited to share a new section of my blog dedicated to these experiments.

What’s WebSim.ai?

WebSim.ai is this pretty rad platform that lets you create real-time web simulations using Three.js, WebGL shaders, and other web technologies. Think of it as a playground where code meets creativity, allowing you to build everything from particle systems to reaction-diffusion simulations.

The Experiments

I’ve kicked things off with a couple of fascinating experiments:

Reaction-Diffusion Simulation

You know those patterns you see on seashells and animal coats? That’s what reaction-diffusion systems model. My simulation uses Three.js and custom shaders to create an interactive version of this natural phenomenon. You can literally poke and prod at the simulation, watching as the chemicals (represented by colors) react and diffuse across the screen.

The real magic happens in the shader code, where I’m implementing the Gray-Scott model:

float Da = 1.0;
float Db = 0.5;
float f = 0.04;
float k = 0.06;
float t = old.x * old.y * old.y;

These parameters control how the patterns form and evolve. Tweak them slightly, and you get wildly different results - from fingerprint-like swirls to spotted patterns reminiscent of leopard prints.

Dynamic Fractal Exploration

The second experiment dives into the mesmerizing world of fractals. Using WebGL shaders, I created an interactive fractal viewer that lets you pan through infinite mathematical landscapes. What makes this particularly interesting is the extreme zoom capabilities - you can dive deeper and deeper into the patterns, discovering new details at every level.

Technical Insights

Building these experiments has taught me some valuable lessons about real-time graphics programming:

1. Ping-Pong Rendering: For simulations like reaction-diffusion, you need to constantly swap between two render targets - one for reading the current state and one for writing the next state.

2. Shader Performance: When you’re running complex calculations in real-time, every optimization counts. I learned to balance visual quality with performance by carefully managing shader complexity.

3. User Interaction: Adding interactive elements makes these mathematical concepts more engaging and intuitive. A simple mouse interaction can bring an abstract concept to life.

The Future of Web Simulations

This is just the beginning. I’ve got several more experiments in the pipeline, including:

• Particle systems with physics
• Fluid dynamics simulations
• Interactive cellular automata

Try It Yourself

I’ve added a new WebSim Experiments section to my blog where you can play with these simulations directly in your browser. Each experiment is interactive, so don’t be shy - click, drag, and explore!

The beauty of these experiments is that they’re not just visual eye candy - they’re interactive tools for understanding complex systems. Whether you’re a math enthusiast, a creative coder, or just someone who enjoys playing with cool web stuff, I think you’ll find something interesting here.

Have you played with WebSim.ai or similar platforms? I’d love to hear about your experiences with creative coding and web simulations. Drop a comment below or reach out - let’s geek out about the intersection of code and creativity! 💡

It’s funny how perspective changes everything. As I sit here reflecting during Thanksgiving week, I’m struck by just how different things feel compared to a year ago. Sometimes you don’t realize how far you’ve come until you take a moment to look back.

If you haven’t been sleeping under a rock for the past few years, you’ve probably heard the buzz about AI-powered coding tools. GitHub Copilot, Amazon CodeWhisperer, Anthropic Claude - these robo-devs are making waves and promising to revolutionize how we sling code. But are they really the game-changers they claim to be, or just overhyped toys? Let’s cut through the noise and see what’s really crackin’.

The landscape of web development is undergoing a profound transformation, one that reminds me of the early days of responsive design or the shift to mobile-first thinking. But this time, the change is more fundamental - AI isn’t just another tool in our toolkit, it’s reshaping how we approach the entire development process.

Having spent years in web development, from the days of jQuery to modern React applications, I’ve seen many evolutionary steps. But what’s happening now feels revolutionary. AI is becoming less of an external tool and more of a collaborative partner in the development process.

The most fascinating aspect to me is how this impacts the role of web developers. We’re moving from being pure coders to becoming something more akin to systems architects and AI coordinators. It reminds me of the transition from writing vanilla JavaScript to adopting frameworks - at first, it felt like we might be losing something, but we ended up gaining a whole new level of capability.

What really gets me excited is the emergence of what I call “AI-native” web experiences. Imagine websites that don’t just serve content, but actually understand and adapt to user context in real-time. We’re not just talking about A/B testing anymore; we’re looking at interfaces that can dynamically reorganize themselves based on individual user behavior and needs.

The technical implications are profound:

• Edge computing is becoming crucial as more processing needs to happen closer to the user
• We’re seeing the emergence of new web standards specifically designed for AI integration, like Constitutional AI and W3C’s Human-Centric AI Community Group. The standardization landscape is rapidly evolving with several key initiatives:
  • NIST’s AI Risk Management Framework provides crucial guidelines for managing AI-related risks, with specific guidance for generative AI systems
  • ISO/IEC standards are defining AI system lifecycles and management systems
  • The W3C’s AI & Web Impact Report outlines how AI systems are reshaping the web’s architecture
  • Emerging Spatial Web Standards are addressing interoperability and governance of intelligent software agents
• Privacy and security considerations are evolving rapidly as we handle more complex, AI-driven interactions

The most intellectually stimulating challenges right now revolve around bridging traditional web development and AI capabilities. How do we maintain performance when we’re running increasingly complex AI operations? How do we ensure consistency across different AI systems? These are the kinds of problems that energize our field and drive innovation forward.

One thing I’ve learned from working with various technologies is that the key to successful adoption is finding the right balance. Just as we had to find the sweet spot between client-side and server-side rendering, we now need to find the right mix of human-designed and AI-generated components.

The tooling ecosystem is already adapting. We’re seeing the emergence of AI-first frameworks like Vercel’s AI SDK that treat AI capabilities as first-class citizens. Testing is becoming more autonomous, with AI systems able to predict and prevent potential issues before they arise. It reminds me of the shift from manual testing to automated testing suites, but with an intelligence that can actually understand context and user intentions.

For those looking to stay ahead in this evolving landscape, here’s what I think matters most:

1. Focus on understanding AI capabilities and limitations - knowing what AI can and can’t do is becoming as important as knowing your programming languages
2. Develop expertise in human-AI interaction design - this is becoming a crucial skill for creating effective web experiences
3. Maintain a strong ethical framework - as AI becomes more integrated into our web applications, understanding the ethical implications of our design decisions becomes increasingly important

The web as we know it is evolving into something more intelligent and responsive, while still maintaining its core purpose of connecting people and information. It’s an exciting time to be in web development, and I’m looking forward to seeing how we collectively shape this new frontier.

P.S. If you’re working on interesting AI-integrated web projects, I’d love to hear about your experiences in the comments below. The future of web development is being written right now, and we’re all part of that story.