
OpenAI Stopped Training Its Best Models Because One of Them Got Out
Highlights of AI News for September 21 - 27 2026
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Highlights of AI News for September 21 - 27 2026

Highlights of AI News for September 7 - 13 2026

Highlights of AI News for August 17 - 23 2026

A practitioner's tour of how an agent turns a doubtful model into a decision: model-predictive control and why replanning every step is the robustness, CEM and random shooting as the planners world-model papers actually run, planning through a posterior instead of a point estimate, and expected free energy with the sign convention stated the right way round.

Calibrated confidence is a permission slip — this week we spend it. From PILCO's 17.5 seconds of robot experience to V-JEPA 2 planning zero-shot on a Franka arm, we trace how uncertainty becomes action. Then we look at the 2026 result that breaks the arc's own thesis: a world model can be locally well-calibrated and globally, confidently wrong.

A beginner-friendly tour of Bayesian 3D reconstruction: why an ordinary 3D scan gives one confident answer everywhere, how turning geometry into a distribution produces honest confidence maps, and where the 'prior' that fills in unseen regions comes from.

Highlights of AI News for July 6 - 12 2026

Highlights of AI News for April 13 - 19 2026

Highlights of AI News for April 06 -12 2026

A tour of the architectures that bake 3D geometry into the network itself—from Hinton's capsules and the geometric deep learning framework to modern E(n)-equivariant graph networks powering physical AI.

Survey the post-transformer frontier—state space models, recurrent revivals, long convolutions, and equivariant networks—and see why the architectures that will power physical AI look nothing like a stack of attention layers.

World Models landscape and engineering challenges in 2026-2027