PCWorld reports on a quirky new Skyrim mod created by Ikea, adding furniture-themed content to the popular RPG. The mod, called Kallax Storageborn, features actor Matt Berry voicing a sentient Kallax shelving unit, alongside meatball helmets and Allen key weapons. Players can explore Ikea-inspired cave environments, with the mod available now through the Skyrim Creations website, marking an unusual but creative gaming expansion for the furniture brand. The Swedish furniture giant Ikea continues to venture into the world of gaming. A few weeks ago, they unveiled the new Yxstaby collection in collaboration with Microsoft's gaming division, Xbox, but the company has now brought its furniture into the gaming world in the form of an officially licensed mod for the hit game The Elder Scrolls V: Skyrim. The'Kallax Storageborn' mod introduces Ikea's classic Kallax shelving unit as a companion in the game, designed to help you carry around all the junk you collect in Skyrim. Actor Matt Berry, known for his role in the TV series, among other things, provides the voice of the Kallax shelving unit in the game. The developers at Kinggath Creations have also added "meatball helmets," an Allen key as a weapon, and an adventure that takes the player into two Ikea-inspired caves. The "Kallax Storageborn" mod can be downloaded from the Skyrim Creations website .

When you purchase through links in our articles, we may earn a small commission. It took entirely too long to get the taskbar back on top without mods. But at least I found a cool new program with community-supplied tweaks. This morning I woke up to a freshly rebooted desktop. A bit annoying, but that's just something that happens with Windows 11 -- it reboots to install an update after a while, sometimes even when you don't ask it to.

A.1 Construction of a D-EquiStatic graph A practical method to construct a D-EquiStatic weight matrix W is provided in Alg. 3. We should mention that the "while" loop in the algorithm is adopted to guarantee kΠWk2 ρ. Construct W by (3); end Output: The D-EquiStatic weight matrix W and its associated basis indices {ut}Mt=1 A.2 Proof of Theorem 1 Before showing properties of W defined by (3), we provide two lemmas as follows. Referring to Theorem 1.6 of [32], we have the following result for a sequence of random matrices. Lemma 1 (Matrix Bernstein) Consider a sequence of K independent random n n matrices {Mi}Ki=1. Assume that each random matrix satisfies E[Mi] = 0, and kMik2 R almost surely. Theorem 1 (Formal restatement of Theorem 1) Let A(u) be defined by (2) for any u [n 1]and the D-EquiStatic weight matrix W be constructed by (3) with {ui}Mi=1 following an independent and identical uniform distribution from [n 1].

Aligning language models (LMs) to human preferences has emerged as a critical pursuit, enabling these models to better serve diverse user needs. Existing methods primarily focus on optimizing LMs for a single reward function, limiting their adaptability to varied objectives. Here, we propose $\textbf{multi-objective decoding~(MOD)}$, a decoding-time algorithm that outputs the next token from a linear combination of predictions of all base models, for any given weighting over different objectives.We exploit a common form among a family of $f$-divergence regularized alignment approaches (such as PPO, DPO, and their variants) to identify a closed-form solution by Legendre transform, and derive an efficient decoding strategy.Theoretically, we show why existing approaches can be sub-optimal even in natural settings and obtain optimality guarantees for our method.Empirical results demonstrate the effectiveness of the algorithm. For example, compared to a parameter-merging baseline, MOD achieves 12.8\% overall reward improvement when equally optimizing towards $3$ objectives. Moreover, we experiment with MOD on combining three fully-finetuned LMs of different model sizes, each aimed at different objectives such as safety, coding, and general user preference. Unlike traditional methods that require careful curation of a mixture of datasets to achieve comprehensive improvement, we can quickly experiment with preference weightings using MOD to find the best combination of models.

Britain is to develop new air defence weapons alongside the EU's four biggest military powers, deepening ties with the European defence sector. The project will invite manufacturers in the UK, Germany, France, Italy and Poland to submit plans to build low-cost missiles and autonomous drones. The allies are pledging a speedy process to build the weapons together, inspired by Ukraine's development of cheap drones to counter attacks from Russia. The UK's Ministry of Defence (MoD) says the programme will prioritise a lightweight, affordable surface-to-air weapon, with the first project to be delivered by next year. The plan, announced at a meeting of the five countries' defence ministers in the Polish city of Krakow, marks a boost to UK-Europe ties after the failure of talks last year over UK participation in the EU's new €150bn (£130bn) defence fund.

SB-FBSDE isanewclass ofgenerativemodels that, inspiring bytherecent advance of understanding deep learning through the optimal control perspective [61-63], adopts Lemma 5 to generalize the score-based diffusion models.

Federated learning (FL) faces challenges in ensuring both privacy and communication efficiency, particularly in resource-constrained environments such as Internet of Things (IoT) and edge networks. While sign-based methods, such as sign stochastic gradient descent with majority voting (SIGNSGD-MV), offer substantial bandwidth savings, they remain vulnerable to inference attacks due to exposure of gradient signs. Existing secure aggregation techniques are either incompatible with sign-based methods or incur prohibitive overhead. To address these limitations, we propose Hi-SAFE, a lightweight and cryptographically secure aggregation framework for sign-based FL. Our core contribution is the construction of efficient majority vote polynomials for SIGNSGD-MV, derived from Fermat's Little Theorem. This formulation represents the majority vote as a low-degree polynomial over a finite field, enabling secure evaluation that hides intermediate values and reveals only the final result. We further introduce a hierarchical subgrouping strategy that ensures constant multiplicative depth and bounded per-user complexity, independent of the number of users n.

The UK lacks a plan to defend itself from military attack, a committee of MPs has warned. In a highly critical report, the defence committee says the UK is over-reliant on US resources and that preparations to defend itself and overseas territories in the event of attack are nowhere near where they need to be. The committee's chair, Labour MP Tan Dhesi, said: Putin's brutal invasion of Ukraine, unrelenting disinformation campaigns, and repeated incursions into European airspace mean that we cannot afford to bury our heads in the sand. It comes as the Ministry of Defence (MoD) identified parts of the country where six or more new munitions factories could be built. In June, Defence Secretary John Healey announced plans to move the UK to war-fighting readiness, including £1.5bn to support the construction of new munitions factories, which will be built by private contractors.