Upcoming (serious) Web performance boostBy: Adam Scott5 June 2025Progress ReportSometimes, just adding a compiler flag can yield significant performance boosts. And that just happened.For about two years now, all major browsers have supported WASM (WebAssembly) SIMD. SIMD stands for “Single instruction, multiple data” and is a technology that permits CPUs to do some parallel computation, often speeding up the whole program. And that’s exactly why we tried it out recently.We got positive results.The need for performance on the WebThe Web platform is often overlooked as a viable target, because of its less-than-ideal environment and its perceived poor performance. And the perception is somewhat right: the Web environment has a lot of security-related quirks to take into account—the user needs to interact with a game frame before the browser allows it to play any sound1. Also, due to bandwidth and compatibility reasons, you rarely see high-fidelity games being played on a browser. Performance is better achieved when running software natively on the operating system.But don’t underestimate the potential of the Web platform. As I explained in broad terms at the talk I gave at the last GodotCon Boston 2025, the Web has caught up a lot since the days of Flash games. Not only are there more people playing Web games every year, but standards and browsers improve every year in functionality and in performance.And that’s why we are interested in using WASM SIMD.WASM SIMD BenchmarksOur resident benchmark expert Hugo Locurcio (better known as Calinou) ran the numbers for us on a stress test I made. We wanted to compare standard builds to builds with WASM SIMD enabled.Note: You may try to replicate his results, but be aware that he has a beast of a machine. Here are his PC’s specifications:CPU: Intel Core i9-13900KGPU: NVIDIA GeForce RTX 4090RAM: 64 GB (2×32 GB DDR5-5800 CL30)SSD: Solidigm P44 Pro 2 TBOS: Linux (Fedora 42)I built a Jolt physics stress test from a scene initially made by passivestar. By spawning more and more barrels into the contraption, we can easily test the performance difference between the WASM SIMD build and the other.Without WASM SIMDWith WASM SIMDImprovement (approx.)Test linksLinkLink-Firefox 138(“+100 barrels” 3 times)2×Firefox 138(“+100 barrels” 6 times)10.17×*Chromium 134(“+100 barrels” 3 times)1.37×Chromium 134(“+100 barrels” 6 times)14.17×**Please note that once the physics engine enters a “spiral of death”, it is common for the framerate to drop to single digits, SIMD or not. These tests don’t prove 10× to 15× CPU computing speed improvements, but rather that games will be more resilient to framerate drops on the same machine in the same circumstances. The 1.5× to 2× numbers are more representative here of the performance gains by WASM SIMD.What it means for your gamesStarting with 4.5 dev 5, you can expect your Web games to run a little bit more smoothly, without having to do anything. Especially when things get chaotic (for your CPU). It isn’t a silver bullet for poorly optimized games, but it will help nonetheless. Also, note that it cannot do anything for GPU rendering bottlenecks.Be aware that the stress tests are meant by nature to only test the worst case scenarios, so you may not see such large improvements in normal circumstances. But it’s nice to see such stark improvements when the worst happens.AvailabilityFrom here on out, the 4.5 release official templates will only support WebAssembly SIMD-compatible browsers in order to keep the template sizes small. We generally aim to maintain compatibility with the oldest devices we can. But in this case, the performance gains are too large to ignore and the chances of users having browsers that are that far out of date is too small relative to the potential benefits.If you need to use non-SIMD templates, don’t fret. You can always build the Godot Editor and the engine templates without WebAssembly SIMD support by using the wasm_simd=no build option.What’s next?As I wrote in my last blog post, we’re currently working very hard to make C#/.NET exports a reality. We do have a promising prototype, we just need to make sure that it’s production-ready.I also mentioned in that article that I wanted to concentrate on improving our asset loading game. Preloading an entire game before even starting it hinders the ability to use Godot for commercial Web games. Once something is implemented to improve that issue, count on me to share the news with you.It’s either that, or we return to the old days of spam-webpages using the “Congratulations, you won!” sound effect when you least expect it. ↩

One of the key use cases for generative AI involves answering questions over private datasets, with retrieval-augmented generation (RAG) as the go-to framework. As new RAG techniques emerge, there’s a growing need to benchmark their performance across diverse datasets and metrics.  To meet this need, we’re introducing BenchmarkQED, a new suite of tools that automates RAG benchmarking at scale, available on GitHub (opens in new tab). It includes components for query generation, evaluation, and dataset preparation, each designed to support rigorous, reproducible testing.   BenchmarkQED complements the RAG methods in our open-source GraphRAG library, enabling users to run a GraphRAG-style evaluation across models, metrics, and datasets. GraphRAG uses a large language model (LLM) to generate and summarize entity-based knowledge graphs, producing more comprehensive and diverse answers than standard RAG for large-scale tasks.  In this post, we walk through the core components of BenchmarkQED that contribute to the overall benchmarking process. We also share some of the latest benchmark results comparing our LazyGraphRAG system to competing methods, including a vector-based RAG with a 1M-token context window, where the leading LazyGraphRAG configuration showed significant win rates across all combinations of quality metrics and query classes. In the paper, we distinguish between local queries, where answers are found in a small number of text regions, and sometimes even a single region, and global queries, which require reasoning over large portions of or even the entire dataset.  Conventional vector-based RAG excels at local queries because the regions containing the answer to the query resemble the query itself and can be retrieved as the nearest neighbor in the vector space of text embeddings. However, it struggles with global questions, such as, “What are the main themes of the dataset?” which require understanding dataset qualities not explicitly stated in the text.   AutoQ: Automated query synthesis This limitation motivated the development of GraphRAG a system designed to answer global queries. GraphRAG’s evaluation requirements subsequently led to the creation of AutoQ, a method for synthesizing these global queries for any dataset. AutoQ extends this approach by generating synthetic queries across the spectrum of queries, from local to global. It defines four distinct classes based on the source and scope of the query (Figure 1, top) forming a logical progression along the spectrum (Figure 1, bottom). Figure 1. Construction of a 2×2 design space for synthetic query generation with AutoQ, showing how the four resulting query classes map onto the local-global query spectrum.  AutoQ can be configured to generate any number and distribution of synthetic queries along these classes, enabling consistent benchmarking across datasets without requiring user customization. Figure 2 shows the synthesis process and sample queries from each class, using an AP News dataset. Figure 2. Synthesis process and example query for each of the four AutoQ query classes.  About Microsoft Research Advancing science and technology to benefit humanity View our story Opens in a new tab AutoE: Automated evaluation framework  Our evaluation of GraphRAG focused on analyzing key qualities of answers to global questions. The following qualities were used for the current evaluation: Comprehensiveness: Does the answer address all relevant aspects of the question?  Diversity: Does it present varied perspectives or insights?  Empowerment: Does it help the reader understand and make informed judgments?  Relevance: Does it address what the question is specifically asking?   The AutoE component scales evaluation of these qualities using the LLM-as-a-Judge method. It presents pairs of answers to an LLM, along with the query and target metric, in counterbalanced order. The model determines whether the first answer wins, loses, or ties with the second. Over a set of queries, whether from AutoQ or elsewhere, this produces win rates between competing methods. When ground truth is available, AutoE can also score answers on correctness, completeness, and related metrics. An illustrative evaluation is shown in Figure 3. Using a dataset of 1,397 AP News articles on health and healthcare, AutoQ generated 50 queries per class (200 total). AutoE then compared LazyGraphRAG to a competing RAG method, running six trials per query across four metrics, using GPT-4.1 as a judge. These trial-level results were aggregated using metric-based win rates, where each trial is scored 1 for a win, 0.5 for a tie, and 0 for a loss, and then averaged to calculate the overall win rate for each RAG method. Figure 3. Win rates of four LazyGraphRAG (LGR) configurations across methods, broken down by the AutoQ query class and averaged across AutoE’s four metrics: comprehensiveness, diversity, empowerment, and relevance. LazyGraphRAG outperforms comparison conditions where the bar is above 50%. The four LazyGraphRAG conditions (LGR_b200_c200, LGR_b50_c200, LGR_b50_c600, LGR_b200_c200_mini) differ by query budget (b50, b200) and chunk size (c200, c600). All used GPT-4o mini for relevance tests and GPT-4o for query expansion (to five subqueries) and answer generation, except for LGR_b200_c200_mini, which used GPT-4o mini throughout. Comparison systems were GraphRAG (Local, Global, and Drift Search), Vector RAG with 8k- and 120k-token windows, and three published methods: LightRAG (opens in new tab), RAPTOR (opens in new tab), and TREX (opens in new tab). All methods were limited to the same 8k tokens for answer generation. GraphRAG Global Search used level 2 of the community hierarchy. LazyGraphRAG outperformed every comparison condition using the same generative model (GPT-4o), winning all 96 comparisons, with all but one reaching statistical significance. The best overall performance came from the larger budget, smaller chunk size configuration (LGR_b200_c200). For DataLocal queries, the smaller budget (LGR_b50_c200) performed slightly better, likely because fewer chunks were relevant. For ActivityLocal queries, the larger chunk size (LGR_b50_c600) had a slight edge, likely because longer chunks provide a more coherent context. Competing methods performed relatively better on the query classes for which they were designed: GraphRAG Global for global queries, Vector RAG for local queries, and GraphRAG Drift Search, which combines both strategies, posed the strongest challenge overall. Increasing Vector RAG’s context window from 8k to 120k tokens did not improve its performance compared to LazyGraphRAG. This raised the question of how LazyGraphRAG would perform against Vector RAG with 1-million token context window containing most of the dataset. Figure 4 shows the follow-up experiment comparing LazyGraphRAG to Vector RAG using GPT-4.1 that enabled this comparison. Even against the 1M-token window, LazyGraphRAG achieved higher win rates across all comparisons, failing to reach significance only for the relevance of answers to DataLocal queries. These queries tend to benefit most from Vector RAG’s ranking of directly relevant chunks, making it hard for LazyGraphRAG to generate answers that have greater relevance to the query, even though these answers may be dramatically more comprehensive, diverse, and empowering overall. Figure 4. Win rates of LazyGraphRAG (LGR) over Vector RAG across different context window sizes, broken down by the four AutoQ query classes and four AutoE metrics: comprehensiveness, diversity, empowerment, and relevance. Bars above 50% indicate that LazyGraphRAG outperformed the comparison condition.  AutoD: Automated data sampling and summarization Text datasets have an underlying topical structure, but the depth, breadth, and connectivity of that structure can vary widely. This variability makes it difficult to evaluate RAG systems consistently, as results may reflect the idiosyncrasies of the dataset rather than the system’s general capabilities. The AutoD component addresses this by sampling datasets to meet a target specification, defined by the number of topic clusters (breadth) and the number of samples per cluster (depth). This creates consistency across datasets, enabling more meaningful comparisons, as structurally aligned datasets lead to comparable AutoQ queries, which in turn support consistent AutoE evaluations. AutoD also includes tools for summarizing input or output datasets in a way that reflects their topical coverage. These summaries play an important role in the AutoQ query synthesis process, but they can also be used more broadly, such as in prompts where context space is limited. Since the release of the GraphRAG paper, we’ve received many requests to share the dataset of the Behind the Tech (opens in new tab) podcast transcripts we used in our evaluation. An updated version of this dataset is now available in the BenchmarkQED repository (opens in new tab), alongside the AP News dataset containing 1,397 health-related articles, licensed for open release.   We hope these datasets, together with the BenchmarkQED tools (opens in new tab), help accelerate benchmark-driven development of RAG systems and AI question-answering. We invite the community to try them on GitHub (opens in new tab).  Opens in a new tab

Courtesy of IKEAFurnishing the first place you call your own is a big deal. It needs to be more elevated than your dorm room, but the pieces also need to be affordable. You want quality furniture that will last well beyond your first lease, but it also needs to be adaptable to suit your ever-evolving style. The foolproof solution to all of these needs? IKEA. The retailer has long mastered Scandinavian simplicity, with functional, budget-friendly furniture that works with a range of styles. Here are seven selects to make your first apartment feel like home. The best part? These are proven favorites, with ratings of 4+ stars out of 5 from hundreds, if not thousands of reviews—so you can trust that each and every one will deliver both quality and style.1KALLAX Shelf Unit$80 at IKEAYour dream of built-in bookshelves may be a few years (or decades) away, but that doesn’t mean you can’t fake it. Use the adaptable KALLAX series to build a shelving display that suits your space by combining different-size units.2MALM Bed Frame$219 at IKEAFeaturing clean lines and an unfussy design, the MALM is an IKEA classic, available in three sizes (full, queen, and king) and four finishes (white, blue, and dark brown or oak veneer). The high headboard offers ample back support for those work-from-bed days, and the sides can be adjusted to fit varying mattress heights. If you need extra storage, just add the rolling MALM underbed storage boxes.Advertisement - Continue Reading Below3ÄLVDALEN Sleeper Sofa$449 at IKEAIt’s guaranteed that your friends will want to come for an overnight visit in your first apartment, and you’ll want to do them one better than a blow-up air mattress to sleep on. Enter the attractive and comfortable ÄLVDALEN sleeper sofa. It easily folds out to a full-size bed, and even features storage under the seat to hold the bedding. Plus, it comes with a 10-year limited warranty, so you can trust its durability for years to come.4MICKE Desk$90 at IKEAA full-blown home office may not be in the cards for a first pad, but a sleek workspace that won’t detract from the vibe of your living room certainly is. The streamlined MICKE desk features a long tabletop (at nearly 56 inches, it can fit two chairs) and a cable compartment to keep cords hidden away.Advertisement - Continue Reading Below5LACK Wall Shelf Unit$100 at IKEA“Highly aesthetic,” “modern and so practical,” “sturdy and well-designed”—these are just a few of the comments from 1,300+ reviewers about why they love this shelf unit so much. Use it to turn unused vertical wall space into an artful display of ceramics, photos, and books. Hung vertically, each shelf can hold up to six pounds.6STORKLINTA 3-Drawer Chest$120 at IKEASimple, modern, and highly functional, the STORKLINTA dresser features integrated handles on the upper edge of the drawers for a hardware-free design. The anchor-and-unlock feature reduces tip-over risk by requiring the chest be anchored to the wall for more than one drawer to be opened at once.Advertisement - Continue Reading Below7NISSAFORS Utility Cart$30 at IKEAWhether you need more storage in your tiny kitchen or you’re simply looking for a minimalist bar cart, the NISSAFORS is the answer. It’s made of powder-coated steel, it’s available in four finishes—sophisticated black is our favorite—and it’s been tested to IKEA’s strictest standards for stability and durability, so you know it’s built to last.

Text embedding and reranking are foundational to modern information retrieval systems, powering applications such as semantic search, recommendation systems, and retrieval-augmented generation (RAG). However, current approaches often face key challenges—particularly in achieving both high multilingual fidelity and task adaptability without relying on proprietary APIs. Existing models frequently fall short in scenarios requiring nuanced semantic understanding across multiple languages or domain-specific tasks like code retrieval and instruction following. Moreover, most open-source models either lack scale or flexibility, while commercial APIs remain costly and closed. Qwen3-Embedding and Qwen3-Reranker: A New Standard for Open-Source Embedding Alibaba’s Qwen Team has unveiled the Qwen3-Embedding and Qwen3-Reranker Series—models that set a new benchmark in multilingual text embedding and relevance ranking. Built on the Qwen3 foundation models, the series includes variants in 0.6B, 4B, and 8B parameter sizes and supports a wide range of languages (119 in total), making it one of the most versatile and performant open-source offerings to date. These models are now open-sourced under the Apache 2.0 license on Hugging Face, GitHub, and ModelScope, and are also accessible via Alibaba Cloud APIs. These models are optimized for use cases such as semantic retrieval, classification, RAG, sentiment analysis, and code search—providing a strong alternative to existing solutions like Gemini Embedding and OpenAI’s embedding APIs. Technical Architecture Qwen3-Embedding models adopt a dense transformer-based architecture with causal attention, producing embeddings by extracting the hidden state corresponding to the [EOS] token. Instruction-awareness is a key feature: input queries are formatted as {instruction} {query}<|endoftext|>, enabling task-conditioned embeddings. The reranker models are trained with a binary classification format, judging document-query relevance in an instruction-guided manner using a token likelihood-based scoring function. The models are trained using a robust multi-stage training pipeline: Large-scale weak supervision: 150M synthetic training pairs generated using Qwen3-32B, covering retrieval, classification, STS, and bitext mining across languages and tasks. Supervised fine-tuning: 12M high-quality data pairs are selected using cosine similarity (>0.7), fine-tuning performance in downstream applications. Model merging: Spherical linear interpolation (SLERP) of multiple fine-tuned checkpoints ensures robustness and generalization. This synthetic data generation pipeline enables control over data quality, language diversity, task difficulty, and more—resulting in a high degree of coverage and relevance in low-resource settings. Performance Benchmarks and Insights The Qwen3-Embedding and Qwen3-Reranker series demonstrate strong empirical performance across several multilingual benchmarks. On MMTEB (216 tasks across 250+ languages), Qwen3-Embedding-8B achieves a mean task score of 70.58, surpassing Gemini and GTE-Qwen2 series. On MTEB (English v2): Qwen3-Embedding-8B reaches 75.22, outperforming other open models including NV-Embed-v2 and GritLM-7B. On MTEB-Code: Qwen3-Embedding-8B leads with 80.68, excelling in applications like code retrieval and Stack Overflow QA. For reranking: Qwen3-Reranker-0.6B already outperforms Jina and BGE rerankers. Qwen3-Reranker-8B achieves 81.22 on MTEB-Code and 72.94 on MMTEB-R, marking state-of-the-art performance. Ablation studies confirm the necessity of each training stage. Removing synthetic pretraining or model merging led to significant performance drops (up to 6 points on MMTEB), emphasizing their contributions. Conclusion Alibaba’s Qwen3-Embedding and Qwen3-Reranker Series present a robust, open, and scalable solution to multilingual and instruction-aware semantic representation. With strong empirical results across MTEB, MMTEB, and MTEB-Code, these models bridge the gap between proprietary APIs and open-source accessibility. Their thoughtful training design—leveraging high-quality synthetic data, instruction-tuning, and model merging—positions them as ideal candidates for enterprise applications in search, retrieval, and RAG pipelines. By open-sourcing these models, the Qwen team not only pushes the boundaries of language understanding but also empowers the broader community to innovate on top of a solid foundation. Check out the Paper, Technical details, Qwen3-Embedding and Qwen3-Reranker. All credit for this research goes to the researchers of this project. Also, feel free to follow us on Twitter and don’t forget to join our 95k+ ML SubReddit and Subscribe to our Newsletter. Asif RazzaqWebsite |  + postsBioAsif Razzaq is the CEO of Marktechpost Media Inc.. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of Artificial Intelligence for social good. His most recent endeavor is the launch of an Artificial Intelligence Media Platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news that is both technically sound and easily understandable by a wide audience. The platform boasts of over 2 million monthly views, illustrating its popularity among audiences.Asif Razzaqhttps://www.marktechpost.com/author/6flvq/A Step-by-Step Coding Guide to Building an Iterative AI Workflow Agent Using LangGraph and GeminiAsif Razzaqhttps://www.marktechpost.com/author/6flvq/From Clicking to Reasoning: WebChoreArena Benchmark Challenges Agents with Memory-Heavy and Multi-Page TasksAsif Razzaqhttps://www.marktechpost.com/author/6flvq/Mistral AI Introduces Mistral Code: A Customizable AI Coding Assistant for Enterprise WorkflowsAsif Razzaqhttps://www.marktechpost.com/author/6flvq/NVIDIA AI Releases Llama Nemotron Nano VL: A Compact Vision-Language Model Optimized for Document Understanding

The wait is almost over – Nintendo’s Switch 2 officially ships starting today, and the gaming community is electrified with anticipation. With its announcement sending shockwaves through the industry, the Switch 2 promises upgraded hardware, enhanced graphics, and a fresh wave of exclusive titles that have fans and newcomers alike counting down the hours. Social media and gaming forums are buzzing with unboxing plans, early impressions from pre-release units, and speculation about which features will define this next generation of hybrid gameplay. As any veteran Switch owner knows, the right accessories can dramatically enhance the gaming experience, and the Switch 2 is no exception. Whether it’s for extended play sessions at home, on-the-go protection, or boosting multiplayer fun, accessories are the unsung heroes that maximize the console’s potential. From ergonomic thumb grips and bumper cases to game-cartridge-holders, a well-equipped setup can make all the difference – and JSAUX seems to have everything sorted. Designer: JSAUX 1. JSAUX Carrying Case for Nintendo Switch 2 No one wants to risk their brand-new Switch 2 rattling around in a flimsy pouch. JSAUX’s Carrying Case ditches the generic for a custom-molded fit, wrapping your console in thick, dual-layer EVA hard-shell that shrugs off drops and shields against everyday scuffs. The plush microfiber lining is a small luxury, keeping your screen pristine even after you inevitably toss the case into a crowded backpack. There’s room for everything you actually need: 15 game card slots, a mesh pocket for cables and earbuds, and enough space for your Switch 2 with its own protective case attached. JSAUX nails the details with a smooth dual zipper, a Velcro strap to keep your console locked in place, and an adjustable stand that turns any table into a mobile gaming station. Whether you’re heading out for a weekend or just want to keep your gear tidy at home, the comfortable handle and detachable shoulder strap make carrying a breeze. It’s protection, organization, and a flex of practicality, without the bulk. Why We Recommend It This is the Switch 2 case for real-world gamers – the ones who actually take their console outside, swap cartridges in weird places, and need gear that isn’t just stylish, but built for chaos. The customizable storage and soft-but-tough protection mean your Switch 2 and accessories survive every bump, drop, or accidental coffee spill. It’s the kind of case that lets you focus on the game, not what’s happening to your hardware. Click Here to Buy Now: $14.39 $21.99 (34% off, use coupon code “JSSWITCH2”). This code can be stacked with existing product deals or discounts. Hurry, deal ends in 48-hours! 2. JSAUX 3-Pack Tempered Glass Screen Protector for Nintendo Switch 2 You know the moment you peel the plastic off a brand-new console? That pristine look deserves to last. JSAUX’s Tempered Glass Screen Protector for Switch 2 nails that first-day shine with edge-to-edge coverage, engineered specifically for Nintendo’s 2025 flagship. The guide frame makes installation foolproof – seriously, it’s almost impossible to misalign or trap bubbles, even if you’re all thumbs and shaky from launch-day excitement. Once on, the 99% transparency keeps every pixel crisp and colors vibrant, so Breath of the Wild 2 or Mario Kart pop just like on day one. Built from dual-tempered 9H glass, it shrugs off scratches, rogue keys, and the random chaos of backpack travel. The 0.3mm thickness is as subtle as it gets – no loss of touch accuracy, no weird drag. And thanks to a nano-oleophobic coating, smudges wipe away quickly, so you’re never gaming through a fingerprint haze. Whether you’re marathon grinding or passing the Switch to a pizza-fingered friend, this protector is ready for real-world gaming. Why We Recommend It Forget triple-checking your bag for sharp objects – this JSAUX screen protector means your Switch 2 just isn’t precious anymore, it’s practical. Installation is stress-free, the display stays flawless, and your frantic touchscreen mashing never feels laggy. For anyone tired of treating their console like fine china, this is the protection that lets you just play. Click Here to Buy Now: $5.59 $9.99 (44% off, use coupon code “JSSWITCH2”). This code can be stacked with existing product deals or discounts. Hurry, deal ends in 48 hours! 3. JSAUX Protective Case Compatible with Nintendo Switch 2 Skip the bulky bricks—this JSAUX Protective Carry Case is precision-engineered for the Switch 2 and the Switch 2 only. You get a snug, movement-free fit that feels purpose-built because it is, and it won’t work with any extra shells or cases. The hard PC exterior shrugs off scratches, dust, and splashes, holding up under café tables and cross-country flights alike. Inside, soft silicone strips keep your Switch 2 floating safely, while the clever raised sections mean your joysticks never take the brunt of an accidental bump. Traveling light? The detachable wrist strap is a small convenience that makes a big difference, and the slim profile means this case slides into any backpack or shoulder bag without hogging space. Built-in game card slots are a thoughtful touch – no more loose cartridges rattling around or getting lost in the depths of your bag. It’s the kind of accessory that makes daily Switch 2 use seamless, keeping your console clean, protected, and always ready to play. Why We Recommend It No-nonsense protection, zero wasted space. This case is for people who toss their Switch 2 into a bag and actually live life. The fit is tight, the shell is tough, and the joystick protection is smarter than most cases twice the price. Game card slots mean your library travels with you, not in a Ziploc. It’s the everyday armor you don’t have to think about, but you’ll notice the moment you need it. Click Here to Buy Now: $13.59 $25.99 (47% off, use coupon code “JSSWITCH2”). This code can be stacked with existing product deals or discounts. Hurry, deal ends in 48-hours! 4. JSAUX Thumb Grips for Nintendo Switch 2 If you’ve ever wished for a thumbstick upgrade on the Switch 2, these JSAUX Thumb Grips are as close as it gets to pro-level control, without needing a soldering iron or a warranty-voiding moment. Designed specifically for the Nintendo Switch 2, they snap on with a reassuring snugness and stay put through frantic boss fights or marathon Splatoon sessions. Three sizes (1, 2, and 3) are included in the kit, so you can fine-tune each stick for your hand size and play style – no more settling for “one size fits all” discomfort. Function isn’t sacrificed for comfort, either. The soft-touch finish and sculpted ergonomic shape actually take the edge off finger fatigue, so you can grind through RPGs or rack up wins in fighters without your thumb locking up. Each cap height serves a purpose: short for fast, twitchy moves in action games, tall for accuracy and steady aim in shooters, original size to simply boost grip. Mix and match to build your own hybrid layout. Why We Recommend It Who knew a 10-second upgrade could totally shift your game? These JSAUX Thumb Grips for Switch 2 let you dial in comfort and precision, whether you’re craving snap reflexes in Smash or pixel-perfect aim in Splatoon. No slipping, no awkward fit, no thumb fatigue after hours – just that satisfying soft grip and a custom feel that actually matches your play style. For anyone tired of stock sticks, this is the tweak you’ll wish you’d made sooner. Click Here to Buy Now: $6.39 $12.99 (50% off, use coupon code “JSSWITCH2”). This code can be stacked with existing product deals or discounts. Hurry, deal ends in 48-hours! 5. JSAUX Dockable Case for Nintendo Switch 2 The JSAUX Protective Case for Nintendo Switch 2 is engineered for gamers who want real protection without sacrificing style or convenience. Its split design means you can effortlessly detach the JoyCons without wrestling with stubborn plastic, and the ultra-thin 1mm PC back shell slides right into the official dock – no need to remove the case every time you charge or play on the big screen. The U-shaped cutout perfectly frames the Switch 2’s built-in kickstand, so you can go from handheld to tabletop mode in seconds, without ever fumbling or forcing a fit. Hybrid construction is the secret sauce here. The JoyCon covers fuse a transparent, scratch-resistant PC front with a soft-touch TPU back, letting the Switch 2’s design shine while adding grip and comfort for marathon sessions. Every port and button stays fully accessible thanks to precise cutouts, and popping the covers on or off is a breeze. No more risking cracked clips or flaky plastic – just smooth, reliable protection dialed in for everyday use. Why We Recommend It Forget clunky cases that ruin the Switch’s sleek vibe or force you to undock every time you want to play on your TV. JSAUX nails the essentials: dock-friendly fit, proper grip, zero interference with the kickstand, and a clear finish that doesn’t hide your console’s good looks. It’s protection that respects the Switch 2’s design – no bulk, no hassle, just smart, seamless defense you barely notice until you need it. Click Here to Buy Now: $12.99 $19.99 (35% off, use coupon code “JSSWITCH2”). This code can be stacked with existing product deals or discounts. Hurry, deal ends in 48-hours!The post Don’t Unbox Your Nintendo Switch 2 Without These Gaming Accessories first appeared on Yanko Design.

Wellness is no longer something we seek out. It’s something we’re building into our homes. From infrared panels and cold plunges to entire rooms designed for rest and recovery, the wellness-at-home movement is reshaping how we live and reset. Thermasol, a pioneer in steam and sauna innovation since 1958, embraces this shift with a new collection of Scandinavian-inspired saunas that bring spa-level luxury to both indoor and outdoor spaces in your home. With natural materials, European craftsmanship, and smart features like WiFi-enabled controls and ambient lighting, each sauna is designed to transform daily rituals into immersive moments of restoration. Aalto Indoor Sauna The new indoor models – Aalto, Astra, and Lumaria – each take a distinct approach to serenity. Aalto, named after the Finnish word for “wave,” features sculptural lines and a seamless blend of wood and glass, creating an organic sense of flow. Astra Indoor Sauna Astra, derived from the Latin word for “stars,” offers a luminous experience with a sleek, corner-friendly layout that maximizes space without compromising elegance. Lumaria Indoor Sauna Lumaria, a combination of the words “lumina” (which means light) and “aria” (or melody), lives up to its name by blending gentle illumination and refined design in two flexible sizes. The Medium fits two to three people while the Large fits up to five – perfect for home wellness areas of all shapes and scales. Ombra Outdoor Sauna Designed by award-winning designer Bojan Črešnar, Thermasol’s five new outdoor saunas feel like you’re stepping away for a short vacation away from home. Each model is a study in contrast – bold yet serene, architectural yet inviting. The Ombra uses tinted, reflective glass that offers privacy while maximizing the views. Wavy wood accents add an organic warmth to the otherwise streamlined facade. Ombra Outdoor Sauna Ombra Outdoor Sauna Ombra Outdoor Sauna Vue Outdoor Sauna Vue Outdoor Sauna Vue Outdoor Sauna The Vue opens up to nature with a striking full-glass front, while the Fortis leans into warmth and durability with thermally modified wood and layered insulation. Fortis Outdoor Sauna Fortis Outdoor Sauna Spectra Outdoor Sauna For those with smaller footprints, the Spectra delivers big on style in a compact form, and the Vera is tailored for balconies, rooftops, and garden corners, bringing wellness to even the coziest of spaces. Spectra Outdoor Sauna With this new collection, Thermasol continues to evolve what wellness can look and feel like at home. These saunas merge design, technology, and tradition in ways that feel both elevated and deeply personal. Whether you’re carving out a moment of stillness indoors or soaking in the quiet of your backyard, these saunas invite you to pause, reset, and reconnect – no spa membership required. Vera Outdoor Sauna To learn more about Thermasol’s newest saunas and bring tranquility into your own home, visit thermasol.com. Imagery courtesy of Thermosol.

Discord co-founder and CTO Stanislav Vishnevskiy wants you to know he thinks a lot about enshittification. With reports of an upcoming IPO and the news of his co-founder, Jason Citron, recently stepping down to hand leadership of the company over to

The science-backed method supports strength, mobility and muscle health.

London School Of Emerging Technology (LSET): Bridging Tech Talent With Industry Needs In A Fast-Changing Era  Oneindia

Ryan King Art writes: In this Blender tutorial we will create this Futuristic Stylized Ringed Planet. Source