Jul 26, 2026

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• Running a 28.9M parameter LLM on an $8 microcontroller

• A 28.9 million parameter language model runs on the ESP32-S3 microcontroller, leveraging Per-Layer Embeddings to store most parameters in flash memory, allowing it to operate efficiently despite limited SRAM.

• The new rules of context engineering for Claude 5 generation models

• Claude 5 models have undergone significant changes in context engineering, notably reducing the system prompt by over 80% without sacrificing performance, allowing for more flexible and intuitive interactions.

• Bringing PyTorch Monarch to AMD GPUs

• PyTorch Monarch has been successfully ported to AMD GPUs with ROCm, enabling fault-tolerant distributed training that minimizes wasted computation and maximizes GPU utilization, crucial for training large language models.

• Need Arxiv endorsement for CS.LG to publish a preprint about Learning Stable Latent Manifolds from noisy sensor data /Observation space [P]

• The study explores learning stable latent manifolds from noisy sensor data, demonstrating that such data can effectively support auto-regression tasks under specific conditions, with empirical validation on NASA's CMAPSS dataset.