47 summarised stories about Model Architecture, each linking back to the original source. Browse all topics →
Ars Technica 1 month ago 39
Researchers built Spi-Fly, an algorithm inspired by fruit fly smell processing, to better remember scents over time. It was described in a paper published in Neuromorphic Computing and Engineering. The result is an odor-recognition system aimed to reduce the “quick to forget” limitation seen in many commercial electronic noses as it adds longer-lasting scent memory.
The daily briefing
TLDRocket reads all relevant sources, removes duplicate coverage, and summarises the day in two minutes. Follow companies and topics for alerts, or get the briefing in Slack. Free, no spam, unsubscribe anytime.
TLDRocket
16 October 2026
AI’s center of gravity this week moved toward something less glamorous than headlines about “smarter” models: scaling the stuff models actually learn from. AI4Bharat and NVIDIA released Nemotron-pretraining-Indic-v1, backed by an open, GPU-accelerated synthetic data generation pipeline for 22 Indian languages. The corpus is massive—about 2.8 trillion tokens—split across 2,601.0 billion native-script tokens and 224.6 billion romanized tokens. The practical pitch is even sharper: builders can reuse not just the data, but the full prompt/quality/repair recipe, then continue-pretraining to push results on Nemotron 3.5 Super VL, with the promise that an Indic continued-pretraining stage helps benchmarks.
Read the full briefing →