Full Archive · Page 60

Research archive, page 60

Browse entries 1417–1440 of 1470. Return to the first page to search and filter the complete collection.

Preferences Over Benchmarks: Model Routing — Archana Kamath & Tyler Gillam, DigitalOcean video thumbnail Play video
AI Engineer August 22, 2026 video

Preferences Over Benchmarks: Model Routing — Archana Kamath & Tyler Gillam, DigitalOcean

Two terminals run the same prompt, build me a spinning wheel app. On the left every request goes to a single premium model. On the right they go through a router that picks a model per task. Both finish at about the same time with comparable output, and by then the router's session has cost 8 cents against 25.

The Next Medium: Why Real-Time Interactive Video Changes Everything — Ahmed Ahres, Reactor video thumbnail Play video
AI Engineer August 18, 2026 video

The Next Medium: Why Real-Time Interactive Video Changes Everything — Ahmed Ahres, Reactor

Uber could not exist without GPS. Ahmed Ahres uses that to argue real time is a change of medium rather than a speedup: before GPS you consulted a map somebody else had already made, and afterwards your own position became something you could act on continuously. He runs the same argument through film.

Training Krea 2: What matters in generative model training — Sangwu Lee, Krea.ai video thumbnail Play video
AI Engineer August 15, 2026 video

Training Krea 2: What matters in generative model training — Sangwu Lee, Krea.ai

The most reliable way to render a person is to render the most boring average person and put them in the center of the frame. Sangwu Lee offers that as the price the big image models pay for consistency: ask a production model for a burning skull and every output comes back clean, competent, and nearly identical.

Intelligence + Continual Learning = Expertise — Yu Su, NeoCognition video thumbnail Play video
AI Engineer August 12, 2026 video

Intelligence + Continual Learning = Expertise — Yu Su, NeoCognition

Scheduling a meeting is not finding a shared slot on everyone's calendar. It is a constraint optimization over authority, priority, and urgency, and an expert sees that immediately where a very capable model does not. Yu Su uses examples like that one to separate two things the field keeps collapsing together.