History

Perforated and the Shift Toward Efficient Intelligence

• AI systems increasingly constrained by compute, latency, and deployment cost
• Modern ML workflows prioritize efficiency alongside accuracy
• Perforated introduces neuroscience-inspired infrastructure compatible with existing PyTorch workflows
• Focus shifts from larger models to smarter, more efficient systems

Transformers and Large-Scale Deep Learning

• Transformer architectures accelerate modern AI capabilities
• Rapid growth in model size and compute requirements
• Foundation models emerge across language, vision, and multimodal AI
• Infrastructure cost and deployment complexity begin scaling dramatically

AlexNet Ignites the Modern Deep Learning Era

• AlexNet wins ImageNet competition by a decisive margin, reducing error rates dramatically
• Demonstrates that deep convolutional neural networks trained on GPUs can outperform traditional methods
• Proves scalability of deep learning across computer vision and beyond
• Marks the beginning of rapid AI progress driven by deeper networks and larger datasets

Backpropagation Enables Modern Neural Networks

• Backpropagation becomes the dominant training method for neural networks
• Multi-layer learning becomes computationally practical
• Deep learning foundations begin taking shape
• Training efficiency and scalability become central challenges

The McCulloch-Pitts Artificial Neuron

• One of the earliest mathematical models of an artificial neuron
• Simplified neuron abstraction becomes foundational to machine learning
• Core neuron structure remains largely unchanged for decades
• Modern neuroscience understanding remains limited in AI systems

Sherrington Defines the Synapse

• Sherrington introduces "synapse" for the junction between neurons
• Neural communication is understood as contact-based, not continuous wiring
• Signal transfer, inhibition, and integration become central neuroscience ideas
• Biological intelligence is framed as networked, directional, and adaptive

Cajal Reveals the Neuron's Structure

• Ramón y Cajal shows neurons are distinct cells, not one continuous network
• Dendrites emerge as tree-like structures central to neural signaling
• Directional information flow begins to reshape neuroscience
• Rich biological neuron structure becomes visible