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RWKV-7: Advancing Recurrent Neural Networks for Efficient Sequence Modeling
Autoregressive Transformers have become the leading approach for sequence modeling due to their strong in-context learning and parallelizable training enabled by softmax attention. However, softmax…
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Attractors in Neural Network Circuits: Beauty and Chaos
The state space of the first two neuron activations over time follows…
Our newest Gemini model with thinking
Today we’re introducing Gemini 2.5, our most intelligent AI model. Our first…
Multilayer Perceptron Explained with a Real-Life Example and Python Code: Sentiment Analysis
This is the first article in a series dedicated to Deep Learning,…
Exploring Empty Spaces: Human-in-the-Loop Data Augmentation
Data augmentation is crucial to make machine learning models more robust and…
TokenSet: A Dynamic Set-Based Framework for Semantic-Aware Visual Representation
Visual generation frameworks follow a two-stage approach: first compressing visual signals into…
A Coding Implementation of Extracting Structured Data Using LangSmith, Pydantic, LangChain, and Claude 3.7 Sonnet
Unlock the power of structured data extraction with LangChain and Claude 3.7…
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