Sapients paper on the concept of Hierarchical Reasoning Model
The Hierarchical Reasoning Model (HRM) introduces a novel recurrent architecture that enables efficient sequential reasoning with only 27 million parameters, achieving high performance on complex tasks without extensive data or pre-training. Link to article
Three high-performance RISC-V processors to watch in H2 2025
Three high-performance RISC-V processors—UltraRISC UR-DP1000, Zhihe A210, and SpacemIT K3—are set to launch in H2 2025, showcasing advancements in octa-core architecture and AI capabilities.
Sub-millisecond GPU Task Queue: Optimized CUDA Kernels for Small-Batch ML Inference on GTX 1650.
Achieved 93,563 ops/sec and 0.011 ms median latency on a GTX 1650 by optimizing CUDA kernels for small-batch ML inference, demonstrating significant performance gains over traditional frameworks like PyTorch and cuBLAS.
I tried implementing the CRISP paper from Google Deepmind in Python
The CRISP paper from Google DeepMind proposes integrating clustering during training, enhancing the model's ability to learn clusterable representations rather than relying on post-hoc methods, which are less effective.
Do you think that Muon Optimizer can be viewed through the lens of explore-exploit?
The Muon optimizer demonstrates the ability to achieve comparable loss with significantly less data, indicating a potential shift in optimization strategies after years dominated by Adam.
LLM Economist: Large Population Models and Mechanism Design via Multi‑Agent Language Simulacra
The LLM Economist preprint introduces a novel approach where LLM-based agents optimize economic policy through multi-agent simulation, allowing a planner to propose tax schedules while a population of 100 worker agents responds based on their personas.
How to improve pretraining pipeline
Enhancements to the pretraining pipeline include Flash Attention, RMSNorm, SwiGLU, and RoPE, which optimize model performance on an 11b token dataset of web text and code.
The AI-Failsafe-Overlay introduces a logic-gated failsafe protocol aimed at addressing misalignment in recursive AI systems, featuring structural admission filters, audit-triggered lockdowns, and persistence-boundary constraints.