Backpropagation
The fundamental algorithm for training neural networks, which calculates how much each weight contributed to the overall error and adjusts them to improve predictions.
Backpropagation, short for backward propagation of errors, was popularized in 1986 by Rumelhart, Hinton, and Williams. It works by computing the gradient of the loss function with respect to each weight using the chain rule of calculus, then updating weights in the direction that reduces error. The algorithm is the backbone of deep learning — without it, training networks with millions or billions of parameters would be computationally infeasible. Modern frameworks like PyTorch and TensorFlow implement automatic differentiation to handle backpropagation efficiently.
Explore the Data
Related Terms
Artificial General Intelligence (AGI)
A hypothetical form of AI that can understand, learn, and apply knowledge across any intellectual task at or above human level, rather than being specialized for specific tasks.
AI Alignment
The research field focused on ensuring AI systems behave in accordance with human values and intentions, particularly as systems become more capable.
ChatGPT
OpenAI's conversational AI assistant, launched in November 2022, which catalyzed the current generative AI boom by demonstrating the capabilities of large language models to a mainstream audience.
Fine-Tuning
The process of further training a pre-trained AI model on a specific, smaller dataset to specialize it for a particular task or domain, requiring far less compute than training from scratch.
Foundation Model
A large AI model trained on broad data that can be adapted to a wide range of downstream tasks — examples include GPT-4, Claude, Gemini, and Llama.
Frontier Model
The most capable and advanced AI models at any given time, typically trained with the largest compute budgets and achieving state-of-the-art performance on benchmarks.
AI Economy Pulse
Every Friday: the 3 AI data points that actually matter this week. Free, forever.
Latest: “AI Investment Hits $42B in Q1 2026 — Here's Where It Went”
No spam, ever. Unsubscribe anytime.