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.
315 episodios disponibles

Latest episodes of the podcast AI: post transformers

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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
Self-Search Reinforcement Learning for LLMs 18/08/2025
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
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