UFC fighter Tim Means was arrested in Albuquerque on a child abuse charge, according to online court records. He is accused of strangling and striking a teenager.

Brock Rechsteiner, son of WWE Hall of Famer Scott Steiner, signed with the Tennessee Titans as an undrafted free agent after going undrafted out of Jacksonville State.

Former NFL quarterback Steve Beuerlein said he is using AI-powered technology from Heartflow to help predict potential heart issues at age 61.

The tech titans are slated to duke it out in court. The tech titans are slated to duke it out in court. Musk and Altman's bitter feud over OpenAI to be laid bare in court Tesla chief believes Altman broke company's founding agreement - and legal battle promises to be explosive T he bitter rivalry between two of the tech world's most powerful men arrives in court this week, as Elon Musk's lawsuit against Sam Altman and OpenAI heads to trial in Oakland, California. The case is set to feature some of the biggest names in Silicon Valley, and its outcome could affect the course of the AI boom. Musk's suit, filed in 2024, focuses on the formative years of OpenAI when he, Altman and others co-founded the artificial intelligence company as a nonprofit with a grand purpose.

A still from animated film La Sélection Mécanique, directed by Jules Blachier. A still from animated film La Sélection Mécanique, directed by Jules Blachier. While emerging technology is banned from the Palme d'Or, an upstart movement is gaining investment and attention I n Cannes' darkened screening rooms, the supposed future of cinema flickered into life this week and it was strange. The first edition of the World AI film festival (WAIFF) showcased visions of men with fish scales erupting from their necks and seaweed from their mouths, a heroine with a heart beating outside her body and so many massed armies of AI-generated tanned men sweeping across battlefields that David Lean would have blushed. Last week the Cannes film festival, entering its 76th year, banned the emerging technology from its Palme d'Or competition, insisting "AI imitates very well but it will never feel deep emotions".

This work presents a data-driven approach for the indoor localization of an observer on a 2D topological map of the environment. State-of-the-art techniques may yield accurate estimates only when they are tailor-made for a specific data modality like camera-based system that prevents their applicability to broader domains. Here, we establish a modality-agnostic framework (called OT-Isomap) and formulate the localization problem in the context of parametric manifold learning while leveraging optimal transportation. This framework allows jointly learning a lowdimensional embedding as well as correspondences with a topological map. We examine the generalizability of the proposed algorithm by applying it to data from diverse modalities such as image sequences and radio frequency signals. The experimental results demonstrate decimeter-level accuracy for localization using different sensory inputs.

In this section, we demonstrate the effectiveness of low-rank matrix factorization in recovering the label relationship matrix. We first present four important facts: f1: the rank of the matrix is equivalent to the number of classes. Specifically, this also means that if ˆZi,k = 1, then ˆZj,k = 1. We consider a toy example (without self-loops), ˆZ = 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 A = 0 1 1 1 0 0 1 0 0 0 0 0 0 0 0 0 (14) In a standard LRMF problem, it is not possible to recover ˆZ from A since no entries are observed for the third and fourth rows. However, we can demonstrate how LRMF effectively performs in this situation. Recovery: We begin by assuming v1 is in class 1, resulting in U1,: = [1, 1, 1] and V1,: = [1,0,0]. By observing A1,4, we know that v4 is also in class 1, resulting in U4,: = [1, 1, 1]and V4,: = [1,0,0](f2). By analyzing A1,2 and A1,3, we determine that v2 and v3 do not belong to class 1.

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