As part of a collaboration with Open Targets on the development of a Side Effect Resource to guide target selection, we have two positions a...

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In gene set analysis, a researcher is typically confronted with many uncertainties in choosing the “right” method, corresponding parameter setting, and data preprocessing approach. We aim to offer gu....

By: Alireza Minagar, MD, MBA, MS (Bionformatics) Software Engineer **👁️ A Developer’s Look Into the Most Advanced Visual System We Know: The Human Brain** When we build computer vision systems, we start with what we know — layers, convolution, pooling, attention. But long before we had GPUs and PyTorch, evolution had already coded the ultimate visual model: the human visual cortex. This article unpacks what developers, AI engineers, and machine learning enthusiasts can actually learn from the visual brain — not as metaphor, but as software architecture. 🔬** Neuroscience as Architecture: Lessons from Nature** 1. Retina = Real-Time Signal Preprocessing Before data ever reaches the brain, your retina compresses, enhances contrast, and selectively transmits. Like a CNN's early layers, it removes noise and boosts signal. 2. V1 Cortex = Orientation Filters Visual cortex area V1 is a matrix of filters — each neuron tuned to detect a specific angle or motion. It’s sparse coding at the hardware level. Sound familiar? 3. Feedback Loops = Adaptive Context Human perception is bidirectional: higher cognitive areas send predictions back to early visual zones. Modern transformers use similar contextual encoding. The brain did it naturally. 4. Saccades = Intelligent Sampling We don’t scan every pixel. Our eyes jump (saccades) based on salience and interest — biologically optimized attention. Great UX. Better compute economy. 5. Plasticity = Lifelong Learning Unlike static models, the brain rewires — without catastrophic forgetting. Future AI must embrace online learning and dynamic architectures to keep pace. 💡** So, What Can Coders Learn?** We’re not just chasing performance benchmarks — we’re imitating intelligence itself. And the brain, especially its visual engine, is proof that elegance and efficiency can coexist. Let’s build models that are adaptive, context-aware, and designed for lifelong learning — just like the brain. 📖 **Want the Deep Dive?** 🔗 Full Medium Article https://medium.com/@aminagar_38889/the-visual-cortex-algorithm-what-coding-can-learn-from-the-brains-vision-engine-ddd6fdbbdc69

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