Paige Spiranac hits bombs at Truist pro-am after years of being shunned, fighter jets interrupt golf & MEAT! Disney's big mistake with Star Wars was turning Luke Skywalker into Mark Hamill: miserable, pathetic and sad WWE US Champion Tiffany Stratton takes her new belt for a celebratory ride on a jet ski, moose delay & MEAT! Nick Bosa's model girlfriend starts summer in a pink bikini on a tennis court, crazy Mark Hamill & plandemic! Best friend booted from wedding for bride's bachelorette cheating, sugar daddy has money troubles & Reno Ruth Taylor Sheridan's hit CIA/military series gets major update ahead of new season premiere Smokin' Charley Hull is back to promoting nicotine after giving up the cigs, Mets booth mess & steak tacos! Hayden Panettiere has a very important message to share with everyone, she's into women too Cameron Brink explores the jungle in a bikini before WNBA tip, Italian PM posts some thirst & woke Star Wars! Perez Hilton heaps praise on Ivanka Trump, takes swipe at Kardashians during appearance on Tomi Lahren's show I don't buy that Iran has a'divided government,' US Navy captain says Democratic congressman blames Trump for disruption of world's oil supply Putin is'really worried' about Ukrainian drone strikes: National security expert OH, DEER!: Nursing home receives unexpected visitor Does the U.S. Still Need NATO?

Marco Rubio warns China of'repercussions' as he reveals what really happened during closed-door Trump and Xi meeting Ex-Yankees star Carl Pavano'peed in shampoo bottles and soiled the bed,' ex-wife claims as bitter prenup feud takes disgusting twist Fury as Kash Patel SNORKELS at sacred war tomb where 900 sailors still lie... then jets off to Las Vegas Glamorous Texas Democrat's secret KINK exposed: Congressional candidate's past life returns to haunt her After theater groping shame, Lauren Boebert is being bankrolled by America's cringiest ex-congressman... and it exposes a MASSIVE hypocrisy Horrifying final days of killer dad Chris Watts' pregnant wife before she was slaughtered alongside their daughters. Read all the chilling texts and receipts in full for first time: 'My eyes burn from crying' RHOBH star Diana Jenkins denies claims she put Hayden Panettiere in bed with'undressed man' when she was 18 Trump reveals Xi's offer to break Iran's Hormuz chokehold... as China's price for the rescue looms Mystery blonde Trump aide with unfettered access to President's phone sparks White House friction: Real reason his posts contain random capital letters... and shadowy team behind them unmasked Florida's $130k housing miracle comes with a brutal catch as families priced out of paradise flock to first trailer park in decades Despicable crimes paid for couple's lavish lifestyle that they flaunted online while gold chain-wearing husband fleeced $1BILLION from taxpayers New DNA analysis of Christopher Columbus reveals truth about explorer's origins that rewrites history Bitter cat fight erupts over DHS'sugar baby' scandal: Veteran female intelligence officer launches explosive new accusations that go right to top of counterterror HQ I lost 9lb in two weeks by making one simple tweak to my lifestyle. I didn't use Mounjaro, diet or change how I exercise and I couldn't believe the results... anyone can do it too I'm godfather to Candace Owens' daughter and Charlie Kirk was my friend... so I know the real reason she's attacking Erika - and I'll never publicly condemn her Britney Spears seen'barking and carrying knife' during chaotic restaurant visit I've had acid reflux all my life. Target customers threaten to boycott store after controversial'upgrade' to shopping cart These UFO files were just the start. Government insiders reveal'holy crap' moment coming next... and their bombshell extraterrestrial'conclusive proof' The truth has always been out there.

Plus: Meta officially kills encrypted Instagram DMs, the Trump administration targets "violent left wing extremists," leaked documents reveal Russia's school for elite hackers, and more. Cramming for finals is bad enough without the platform you use to do your schoolwork suddenly shutting down. Unfortunately for countless students across the US, that's exactly what they faced on Thursday after Canvas went into "maintenance mode" following a ransomware attack on education tech firm Instructure. Hackers using the name ShinyHunters claimed responsibility for the breach, and experts say the chaos they caused shows how far these actors will go to extort their victims. Did you know that Google Chrome includes an automatic download of the Gemini Nano AI model?

The cars that debuted at the Beijing Auto Show demonstrate that the Chinese market is now at the forefront of electrification and intelligence. These are the 19 most intriguing models we saw. The newest concept car from Lynk & Co was revealed at the 2026 Beijing Auto Show. While major motor shows in Europe and the United States are being forced to downsize or change their format, those in China continue to expand. With 1,451 vehicles on display, including 181 world premieres, the 2026 Beijing International Automotive Exhibition 2026 (also known as Auto China 2026) has become the largest auto show in history--and that's in terms of both exhibition space and the number of vehicles on display. This fact itself reflects a shift in the center of gravity of the automotive industry, but that's not all. A much larger structural transformation is actually taking place in China today. Previously, the focus was on low-priced electric vehicle models, but now price is no longer the primary point of competition.

TikTok has rowed back on an AI feature which incorrectly summarised some videos on the platform, including claiming a celebrity was fruit. The company's'AI overviews' recently began appearing beneath content on the platform to describe what a video was showing, or provide more context. While only rolled out to some users in the US and the Philippines, the feature's incorrect and bizarre AI-generated summaries of TikTok content - seen beneath videos of celebrities like platform star Charli D'Amelio - have been shared widely. According to TikTok, its experimental summaries have been tweaked to only suggest products similar to those shown in videos. The changes were first reported by news outlet Business Insider .

Megan Rapinoe, in a shock to no one, backs Angel Reese skipping interviews as'taking power back' White House calls out Newsom as California girls' track and field controversy reignites Here's why the coaches association's 24-team College Football Playoff could ruin the sport Boston Celtics star Jaylen Brown tells ESPN's Stephen A Smith to'be quiet and retire' President Trump on $1,000 World Cup ticket prices: 'I wouldn't pay it either, to be honest' Pirates vs. Diamondbacks betting preview targets the under as both offenses go cold in series Former LSU coach Brian Kelly uses AI to prepare for job interviews, proving he's just like the rest of us Mark Hamill is a'miserable human being': Sage Steele AOC is in'favor' of'robbing' the American people: Tiffany Smiley Iran's playbook is to talk and then fight, Lt Gen Keith Kellogg says Watters: If Iran doesn't sign this fast, the US will be a lot more violent US waits for Iran's response on peace proposal Authorities try to'connect the dots' on hantavirus infections Jesse Watters: Spencer Pratt is a'charismatic, common-sense populist' Greg Gutfeld: Dana White laughs off the'toxic masculinity thing' OutKick Another LIV golfer remains committed to staying put: 'I have full faith in the future of LIV' Thomas Detry says players'really love it' and calls on the entire roster to show cohesion and support Greg Palkot breaks down the announcement that Saudi Arabia's Public Investment Fund will cease funding for the LIV Golf tour, putting its future in jeopardy. LIV Golf now seeks new investors while players attempt to rejoin the PGA Tour. Out of seemingly nowhere, the future of the LIV Golf Tour has been put in serious jeopardy. The breakaway golf tour previously relied on funding from the Saudi Arabia-backed Public Investment Fund to back extremely high purses and bring in top players with massive signing bonuses. But that funding is coming to an end after the 2026 season, throwing all of that progress into jeopardy.

LLMs excel at predictive tasks and complex reasoning tasks, but many high-value deployments rely on decisions under uncertainty, for example, which tool to call, which expert to consult, or how many resources to invest. While the usefulness and feasibility of Bayesian approaches remain unclear for LLM inference, this position paper argues that the control layer of an agentic AI system (that orchestrates LLMs and tools) is a clear case where Bayesian principles should shine. Bayesian decision theory provides a framework for agentic systems that can help to maintain beliefs over task-relevant latent quantities, to update these beliefs from observed agentic and human-AI interactions, and to choose actions. Making LLMs themselves explicitly Bayesian belief-updating engines remains computationally intensive and conceptually nontrivial as a general modeling target. In contrast, this paper argues that coherent decision-making requires Bayesian principles at the orchestration level of the agentic system, not necessarily the LLM agent parameters. This paper articulates practical properties for Bayesian control that fit modern agentic AI systems and human-AI collaboration, and provides concrete examples and design patterns to illustrate how calibrated beliefs and utility-aware policies can improve agentic AI orchestration.

External priors of unknown reliability create a brittle trade-off in causal discovery: blind trust amplifies errors, blind rejection wastes signal. Real priors are also heterogeneously reliable -- physical laws are trustworthy, LLM-suggested edges are speculative -- yet existing methods either ignore priors or impose them through globally uniform trust. We propose PRCD-MAP, a soft prior-consumption layer that assigns per-edge trust to an imperfect prior and uses it to modulate a prior-aware $\ell_1$ and prior-weighted $\ell_2$ regularizer in a MAP objective. Trust is calibrated by empirical Bayes on a Laplace-approximated marginal likelihood and propagated along the prior graph by an MLP, so data-confirmed neighborhoods boost trust and contradictions suppress it. PRCD-MAP enjoys a population-level safety guarantee: it is $\varepsilon$-safe in expectation over the prior-generation distribution, with $\varepsilon\leq C\cdot\mathrm{acc}(1{-}\mathrm{acc})\cdot d^2/T$ at the parametric $T^{-1}$ rate and vanishing at the prior-quality endpoints. When the prior is uninformative, learned trust provably collapses to its floor and the method recovers a no-prior baseline. Empirically, on real CausalTime data PRCD-MAP exploits informative LLM priors (LLM-prior gain $+0.067/+0.089$ AUROC on AQI/Medical over a no-prior PRCD-MAP backbone; combined backbone+prior lead $+0.123/+0.043$ over PCMCI+), auto-attenuates on the anonymous-variable Traffic stress test, and retains a lead at $d{=}300$; against BayesDAG, the closest soft-Bayesian baseline, PRCD-MAP wins on every CausalTime dataset under a matched $W_0$-only protocol. A four-way ablation isolates each component: EB calibration and MLP trust propagation jointly carry the plurality of the gain, with positive sign on every dataset. Extensions to nonlinear (NAM) and cross-sectional settings show the calibrated-trust principle is setting-agnostic.

Commercial Microwave Links (CMLs) offer dense spatial coverage for rainfall sensing but produce path-integrated measurements that make accurate ground-level reconstruction challenging. Existing methods typically oversimplify CMLs as point sensors and neglect line integration relating rainfall to signal attenuation, resulting in degraded performance under heterogeneous precipitation. In this work, we view rain field reconstruction as a Bayesian inverse problem with Diffusion Models (DMs) as high-fidelity spatial priors. We show that diffusion models better preserve key rainfall statistics compared to censored Gaussian processes. Framing rainfall estimation as a Bayesian inverse problem with a DM prior enables training-free posterior sampling using a broad family of methods, including Plug-and-Play, Sequential Monte Carlo, and Replica Exchange methods. Experiments on synthetic and real-world datasets demonstrate consistent improvements over established CML-based reconstruction baselines.

Kernel quadrature (KQ) is a kernel-based approach to numerical integration, closely related to Bayesian quadrature (BQ) and probabilistic integration [38, 39, 10]. For sufficiently regular integrands, KQ can exploit spectral structure in a reproducing kernel Hilbert space (RKHS) that is invisible to plain Monte Carlo and thereby converge faster than the usual O(N 1/2) rate in the number of points [3, 28]. Unconstrained kernel-based rules, however, may produce numerically unstable weights, motivating longstanding interest in positively weighted rules [13, 21, 29, 46]. In this paper, positive weights mean nonnegative weights that sum to one, i.e., simplex or convex-combination weights. Whether positive-weight KQ can systematically improve over Monte Carlo is a subtle question. Kernel herding and related constructions suggested fast rates under favorable assumptions [13], but the conditional-gradient viewpoint of Bach et al. [4] clarified that the strongest such assumptions are not generally available in infinite-dimensional RKHSs. Subsequent herding-type analyses in broad RKHS settings have therefore mostly remained at the Monte-Carlo scale, except under additional structure or modified algorithms such as sparse herding variants [31, 44, 43]. Beyond herding, subsampling-based positive KQ methods such as thinning [16, 15] and recombination [21, 24] have obtained rates beyond Monte Carlo, but a general mechanism for such improvement in the simple i.i.d.