AI Research Teardowns

Paper Breakdowns

Technical breakdowns of seminal AI research papers — analyzing mathematical formulations, algorithmic methods, engineering trade-offs, and production serving implications.

arXiv:2412.19437
26 Jul 2026
DeepSeek-V3 & R1 Paper Breakdown: Multi-Head Latent Attention, Auxiliary-Loss-Free MoE, and DualPipe

Definitive technical paper breakdown of DeepSeek-V3 and R1 detailing Multi-Head Latent Attention (MLA) low-rank KV compression, auxiliary-loss-free MoE load balancing, and DualPipe pipeline parallelism.

Core Methods:
Multi-Head Latent Attention (MLA) Low-Rank KV CompressionAuxiliary-Loss-Free MoE Load BalancingMulti-Token Prediction (MTP) Loss ObjectiveDualPipe Overlapped Computation-Communication Pipeline
16 min readRead Paper Teardown
arXiv:2407.08608
26 Jul 2026
FlashAttention-3 Paper Breakdown: Fast and Memory-Efficient Attention with FP8 Warp-Specialization

Definitive paper teardown of FlashAttention-3 detailing producer-consumer warp specialization, asynchronous TMA memory loads, FP8 GEMM MMA execution, and inter-warp communication on Hopper GPUs.

Core Methods:
Producer-Consumer Warp SpecializationAsynchronous TMA (Tensor Memory Accelerator) LoadsFP8 Low-Precision GEMM Tensor Core ExecutionIn-SRAM Softmax Scaling and Online Rescaling
15 min readRead Paper Teardown
arXiv:2309.06180
26 Jul 2026
PagedAttention Paper Breakdown: Virtual Memory Allocation for LLM KV Cache Serving

Definitive paper teardown of vLLM's PagedAttention architecture detailing virtual memory block translation, dynamic copy-on-write sequence forks, and prefix caching.

Core Methods:
Paged KV Cache Virtual Memory ManagerBlock Table Logical-to-Physical Address TranslationCopy-on-Write Sequence BranchingRadixTree Shared Prefix Caching
14 min readRead Paper Teardown
doi:10.1098/rstb.2008.0300
16 Jul 2026
What Predictive Processing Can and Cannot Teach AI Engineers

Predictive processing offers a useful account of hierarchical inference and error correction, but it is not a shortcut from brain metaphor to system architecture.

Core Methods:
theoretical synthesishierarchical generative modelingpredictive-coding formulation
18 min readRead Paper Teardown