Stay ahead of the curve. Access the most influential breakthrough papers, detailed YouTube lectures, expert analyses, and codebases driving modern Artificial Intelligence.
The absolute gold standard lecture on building a Generative Pre-trained Transformer from absolute scratch in PyTorch. Covers multi-head attention, self-attention, and scaling laws.
An incredible, non-technical to semi-technical orientation of what LLMs are, how they are trained (pretraining, SFT, RLHF), and their future security landscapes (jailbreaks, prompt injections).
A breathtaking geometric visualization of how tokens map to high-dimensional space, and how key/query/value vectors route contextual importance mathematically.
A highly detailed paper walkthrough highlighting the absolute genius of removing Recurrent layers (RNNs) and relying entirely on multi-head attention blocks.
An outstandingly clear visual breakdown of AI inference execution. Demystifies KV Cache, speculative decoding, model quantization, and the hardware bottlenecks of high-throughput LLM hosting.
The paper that changed the world. It introduced the self-attention mechanism, the Encoder-Decoder transformer layout, and sinusoidal positional encoding.
Introduced the low-rank update matrices technique, freezing pretrained model weights and drastically lowering the GPU memory required for instruction finetuning.
A breakthrough replacement for RLHF. It bypasses training a separate reward model entirely, optimizing the policy directly using simple binary preference data.
Details the state-of-the-art architecture of DeepSeek-V3. Covers Multi-head Latent Attention (MLA), DualPipe pipelines, and load-balanced Mixture of Experts (MoE).
The absolute best reference write-up outlining Agent planning loops, memory profiles (sensory, short-term, long-term), and detailed tool calling APIs.
One of the most famous visual deep-dives of the Transformer architecture, explaining the flow of tensors from encoders to decoders with incredible visual clarity.
Evaluates a model across 57 subjects spanning humanities, social sciences, STEM, and professional domains. Still used as a key benchmark for foundational intelligence.
A highly challenging PhD-level science and logic dataset designed such that even human experts struggle unless they have access to search tools.
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A detailed 2-hour lecture explaining BPE, vocab training, and special token handling.