AI: post transformers

Por: mcgrof
The transformer architecture revolutionized the world of Neural Networks. It was a springboard for what we know today as modern artificial intelligence. This podcast focuses on modern state of the art research paper reviews starting from the transformer and on.
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Latest episodes of the podcast AI: post transformers

Mostrando página 13 de 18

Pimba: Processing-in-Memory for LLM Serving 27/08/2025
Oaken: Fast, Efficient LLM Serving with Hybrid KV Cache Quantization 27/08/2025
AdamW: Decoupled Weight Decay Regularization for Adaptive Gradient Algorithms 27/08/2025
Training Recurrent Neural Networks: Vanishing and Exploding Gradients 27/08/2025
Adafactor: Memory-Efficient Adaptive Learning Rates 27/08/2025
SPAM: Stabilizing LLM Training with Spike-Aware Optimization 27/08/2025
Google: Measuring AI's Environmental Impact at Scale 26/08/2025
ComoRAG: Cognitively Inspired Narrative Reasoning 26/08/2025
Quantizing Diffusion LLMs: A Systematic Study 26/08/2025
ODYSSEY: Unified Mobile Manipulation for Agile Quadruped Robots 26/08/2025
GPT-5 Spatial Intelligence: An Empirical Study 24/08/2025
DeepSeek-V3.1: A Hybrid AI Model with Enhanced Reasoning 23/08/2025
Compressed Experts: Efficient MoE Model Editing 23/08/2025
Genie 3: A New Frontier for World Models 22/08/2025
Los Alamos: overcoming the memory wall fighting sparse memory access 21/08/2025
Switch Transformers: Trillion Parameter Models with Sparsity 20/08/2025
Linear Transformers: Faster Than RNNs 20/08/2025
Speed Always Wins: Efficient Large Language Model Architectures 20/08/2025
Atom: Low-Bit Quantization for LLM Serving 18/08/2025
Continuous Batching for LLM Inference: Throughput and Latency Gains 18/08/2025
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