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 16

Mem0: Scalable Long-Term Memory for AI Agents 12/08/2025
Qwen-Image: Generation and Editing with Precision 12/08/2025
Chain-of-Thought Reasoning: A Brittle Mirage? 11/08/2025
DroidSpeak: Cross-LLM KV Cache Sharing 08/08/2025
Dynamic Tanh: Transformers Without Normalization 08/08/2025
Movement Pruning: Adaptive Sparsity by Fine-Tuning 08/08/2025
Kaiming Initialization and PReLU 08/08/2025
Xavier Initialization: Deep Feedforward Networks: Training Difficulties and Solutions 08/08/2025
MEGABYTE: Multiscale Transformers for Million-byte Sequences 08/08/2025
Gemma: Google DeepMind's Open Language Models 08/08/2025
The Elements of Differentiable Programming 08/08/2025
DiMSUM: Image Generation with Diffusion Mamba 08/08/2025
LMCache: Supercharging LLM Performance with KV Cache Management 08/08/2025
AI and the Memory Wall: Overcoming Bottlenecks 08/08/2025
DyNN-Offload: Efficient Memory for Dynamic Neural Networks 08/08/2025
TierTrain: Proactive Memory Tiering for DNN Training 08/08/2025
MoE Offloaded 08/08/2025
CODEGEN: Open Language Model for Code Synthesis 08/08/2025
DeepSeekMoE: Scalable Mixture-of-Experts Language Models 08/08/2025
DeepSeek-R1 Dynamic 1.58-bit Quantization: A Performance Analysis 08/08/2025
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