SMRTR summary
Masked IRL uses two LLMs to help robots interpret vague instructions—one clarifies prompts, the other filters relevant environmental details. Tested on robotic arms, it improved preference understanding by 15% using 5x less training data.
SMRTR provides this summary for quick context. The original article belongs to Daily.dev.
Read the original articleThis archive is built from SMRTR newsletter stories. Subscribe for hand-picked stories without the extra noise.
Amazon is shutting down Mechanical Turk on September 30, 2026, ending a 21-year platform where workers earned small amounts per task. Thousands across 190 countries will lose...
Solo AI filmmakers risk burnout by absorbing every crew role simultaneously. Combat this by locking references early, batching similar tasks, and maintaining a steady production...
Hypernetworks were used to generate interpretable neural networks, discovering three novel algorithms for computing L1 norms without prior knowledge. The resulting networks also...
RAG performance varies by use case—OpenAI tested query expansion, re-ranking, smart routing, and chunk-size tuning on a real project, confirming that evaluation and testing are...
Andrew Ng's top AI skills list, drawn from 10,000+ job postings, focuses too narrowly on building. Real enterprise AI also demands business acumen, risk awareness, orchestration,...
Most AI agents fail real-world tasks despite bold marketing claims. Only three agents—all from Amazon or OpenAI—passed testing by documenting both checkout capability and a...