Small modular reactors and microreactors could power AI data centers and factories, but outdated rules and public fears are stalling America's nuclear energy future.

Neural Information Processing Systems http://nips.cc/

In accelerate restricted 51, 50].

Theyaredesigned tohaveagame-theoretic equilibrium where everyone reveals their private information truthfully.

Theyaredesigned tohaveagame-theoretic equilibrium where everyone reveals their private information truthfully.

This paper tackles the modelling of large, complex and multivariate time series panels inaprobabilistic setting.

A San Diego elementary school teacher faces scrutiny after video shows her turning an American flag upside down inside her first-grade classroom.

In response to a growing backlash, Microsoft said it would take steps to ensure that data centers don't raise utility bills in surrounding areas and address other public concerns. A Microsoft data center in Aldie, Virginia.Photograph: Bloomberg/Getty Images Microsoft said on Tuesday that it would be taking a series of steps toward becoming a "good neighbor" in communities where it is building data centers--including promising to ask public utilities to set higher electricity rates for data centers. Speaking onstage at an event in Great Falls, Virginia, Microsoft vice chair and president Brad Smith directly referenced a growing national pushback to data centers, describing it as creating "a moment in time when we need to listen, and we need to address these concerns head-on." "When I visit communities around the country, people have questions--pointed questions. They even have concerns," Smith said, as a slide showed headlines from various news outlets about opposition to data centers.

We introduce an extension of the partitioned local depth (PaLD) algorithm that is adapted to online applications such as semi-supervised prediction. The new algorithm we present, online PaLD, is well-suited to situations where it is a possible to pre-compute a cohesion network from a reference dataset. After $O(n^3)$ steps to construct a queryable data structure, online PaLD can extend the cohesion network to a new data point in $O(n^2)$ time. Our approach complements previous speed up approaches based on approximation and parallelism. For illustrations, we present applications to online anomaly detection and semi-supervised classification for health-care datasets.