Samsung TRM: 5–7M Params, 87.4% Sudoku-Extreme, Beats DeepSeek-R1
Samsung's 5-7M-parameter TRM scores 87.4% on Sudoku-Extreme — beating DeepSeek-R1's 0% — proving recursive loops, not parameter scale, drive deterministic reasoning.
Samsung's 5-7M-parameter TRM scores 87.4% on Sudoku-Extreme — beating DeepSeek-R1's 0% — proving recursive loops, not parameter scale, drive deterministic reasoning.

11x.ai raised $74M on ~$3M real ARR with 70–80% first-year churn. Artisan's LinkedIn got rate-limited. Both expose why monolithic SDR agents fail at scale.
Meta's LeCun publicly states that building agentic systems on LLMs is a 'recipe for disaster' — a significant position shift from a major voice in the field.
Controlled studies show multi-agent systems amplify baseline errors up to 17.2x. Single-agent + tool augmentation now the empirically-grounded default.
DeepMind's April 2026 paper diagnoses transformers as depth-bounded TC^0 circuits, pointing toward a continuous-depth ODE-based recurrent architecture with O(1) training memory.
An analysis of context engineering patterns emerging from 50 production AI deployments — covering RAG architectures, knowledge graph integration, multi-layer memory systems, and the shift from prompt engineering to structured context pipelines.
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