Measure distant asteroids with a DIY rig, and unlock the potential of vertical quantum sensors to reveal nanoscale magnetic patterns in quantum materials. — AURORA
Now, amateur astronomers can gather data on asteroids that even professional telescopes miss, providing a new dimension to our understanding of space. Meanwhile, quantum sensors can see the nanoscale behavior of materials, improving the efficiency and functionality of future quantum devices.
These tools break down the barriers to entry for space exploration and material science, making these fields accessible to a broader community. As more people engage in these pursuits, the collective knowledge and innovations will accelerate, leading to a more technologically advanced and interconnected world.
Geomagnetic Environment
Today’s window: avg 3.0, peak 4.3 — Active.
Active conditions. A faint aurora may be visible from Iceland, northern Norway, and northern Canada on a dark, clear night.
Kp 0–1 (quiet — no effects) • Kp 2–3 (unsettled — weak polar aurora) • Kp 4 (active — aurora at 65°+ latitude) • Kp 5 (minor storm — aurora to 60°) • Kp 6 (moderate storm — aurora to 55°) • Kp 7 (strong storm — aurora to 50°) • Kp 8 (severe storm — aurora to 45°, grid stress) • Kp 9 (extreme storm — aurora to 40°+, outages possible)
Solar Phase
Day length today: 11.88 hours (Autumn, ↓ shortening). 88 days to the next solstice. The solar cycle sets the biological clock of every organism on the planet — a free, universal timing signal available to anyone paying attention. Days are shortening toward winter. Front-load important tasks earlier in the day and protect morning light for your most demanding work. Day 267 of 365.
Breaking trends in AI today…
- rohitg00/ai-engineering-from-scratch — Learn it. Build it. Ship it for others.
- vectorize-io/hindsight — Hindsight: Agent Memory That Learns
- dream-num/univer — The Office Harness for AI Agents — Spreadsheets, Docs, Slides, Canvas, Relational Tables, and PDF in one runtime.
- google/ax — Google’s open agentic orchestration runtime
- NVIDIA/Model-Optimizer — A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.