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 14 de 18

Diffusion Language Models: Principles, Techniques, and Applications 18/08/2025
The Mapped Memory Mistake: Why DBMSs Should Avoid MMAP 13/08/2025
NVIDIA GDS, BAM Vs RocM solutions 13/08/2025
pNFS Flex Files 13/08/2025
ELMo-Tune-V2: LLM-Assisted Auto-Tuning for Key-Value Stores 13/08/2025
fMoE: Fine-Grained Expert Offloading for MoE Serving 13/08/2025
AiSAQ: DRAM-free ANNS with Product Quantization 13/08/2025
Scaling PostgreSQL at OpenAI: Read-Heavy Workloads and Optimizations - PGConf.dev 2025 13/08/2025
NVMe Offload on Colossal AI: Breaking the GPU Memory Wall 13/08/2025
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
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