This week
Suggest a nameObligation Marketing for AI Builders
The 7-Rung LadderThe 8-Type TaxonomyWrapper or WinnerThe Sample ColumnThe Signal
Updated through the day. Every headline links straight to the source. The two lines underneath are ours.
This is the kind of question that generates engagement but rarely produces actionable insight. Timelines depend entirely on which domain, which experts, and how you measure, and the answer changes weekly. Skip unless you're looking for a casual take on capability trends rather than signal on what's actually changed.
The framing of genuine RSI is directionally important and the scenarios map to real problems, but the paper reads more like taxonomy than breakthrough. No evidence that current models can actually execute the autonomous improvement steps described. Useful for long-term thinking, not actionable this quarter.
This isolates a specific, reproducible failure mode in video understanding models that broad benchmarks tend to hide, useful for anyone evaluating video LLMs for surveillance, sports analytics, or safety monitoring tasks that depend on counting discrete events. The gap between counting slow state changes and fast transient events is the kind of thing that will bite production systems quietly. Worth checking your own video model's behavior on high-frequency events before trusting it.