Quantum computer that learns from its own errors

Google Research demonstrated a reinforcement learning (RL) framework that allows a quantum computer to continuously adapt to drift during computation without halting. The RL agent learns from quantum error correction detection events to dynamically steer control parameters, improving logical stability by 3.5x and reducing logical error rates to record lows.

Google/DeepMind

Mac Mini M4 Pro and OpenClaw: Testing Local LLM Inference

The article tests local LLM inference on a Mac mini M4 Pro with 48 GB RAM using OpenClaw and LM Studio. Three models are compared: google/gemma-4-26b-a4b-qat, qwen/qwen3.6-35b-a3b, and google/gemma-4-31b. Results show that MoE models like gemma-4-26b and qwen3.6-35b offer better speed and energy efficiency compared to the dense model gemma-4-31b.

Apple OpenAI Google/DeepMind