UHQBot

Former Thief: The Dark Project designer, Ion Storm game director, and sometime Spielberg collaborator Randy Smith Evergreen has shared his probably-incendiary view that photorealistic videogame graphics need not have advanced any further than Remedy's original Alan Wake. For context, Alan Wake released back in 2010, when some of you people were screaming babies. Every touted breakthrough in visual fidelity since that golden year? A pointless indulgence and a reckless travesty. A middle finger jammed up the nose of god. Smith Evergreen is entirely wrong, of course: videogame graphics actually topped out with PS1's MediEvil, still definitively the most faithful and convincing portrayal of an incompetent walking skeleton known to science. That said, this is an OG Thief designer we're talking about. Let's hear the poor soul out. Read more View the full article

Back in October 2025, GTA 6 developers Rockstar fired a group of 34, mostly UK-based employees on a charge of "gross misconduct", alleging that they had risked the leaking of confidential information while posting on a Discord server set up by union organisers. The ousted UK workers and their representatives have since taken Rockstar to court, accusing the company of getting rid of them to stop their union gaining enough members to win official recognition under UK law. This week, both parties filed opening submissions at an employment tribunal in Glasgow, which Rockstar parent company Take-Two Interactive have emailed to RPS and Game Developer, among others. Taken together, the filings amount to over 100 pages of claims and counterclaims, with thousands of pages of evidence to be discussed in the coming weeks. Amongst other things, the docs give us more sense of events leading up to the dismissals, including the revelation that Rockstar had a mole or "whistleblower" passing them information on the people using the Discord server. Read more View the full article

Earlier this week, Hideo Kojima-helmed action espionage game Physint switched publishers from PlayStation to Xbox, a leap across the console divide which might make it more likely to get a PC port. At the time, Kojima claimed PlayStation had tried to can the game, while the console makers tried to paint the divorce as an amicable split. Now, a report's shed more light on why Sony decided to ditch Physint. Read more View the full article

Up until now, Rockstar Games have kept mum about what plans they have for the future of Grand Theft Auto multiplayer once GTA 6 releases on consoles in November. Thanks to filings submitted by the studio as part of the final hearing in a legal battle over the firings of 34 developers last year, that silence appears to have been broken. Read more View the full article

Just over a month on from a consortium led by the Saudi Arabian government's Public Investment Fund taking over EA, in a buyout worth $55 billion, said new owners are reportedly considering merging the publishers with their existing gaming firm Savvy Games Group. The result would be an ubermegacorp to serve as a vehicle for all of the Saudi wealth fund's future video game-related biz. Read more View the full article

The beautiful thing about people that like dungeon crawlers is that they're all sickos. Every single one of them! This is not a genre that's for the faint of heart. It is often plodding and methodical and conniving, so focused on stats and character classes that you could drown in the amount of numbers you have to pay attention to. So, how about a dungeon crawler where the battling happens automatically, and all you have to do is a little bit of programming? It's called Dungeon Automata, and trust me, the programming isn't as bad as it sounds. Read more View the full article

There are probably many jokes one could make about mushrooms being edible, and mushrooms being like, edible, man in relation to Shroom and Gloom, a positively mycelial roguelike deckbuilder where you roam spore-filled dungeons with two decks of cards in tow. I won't do that though because that would mean having to think of them, and like Edwin before me, I just don't have it in me. What I do have is the ability to tell you about Shroom and Gloom, which is out in early access today. Read more View the full article

Today marks yet another day in reporting on layoffs that have occurred in the games industry over the past several years, with this occasion unfortunately being GNOG and Goodbye Volcano High developer KO_OP. The studio shared word that 13 staffers were being laid off less than two weeks after the launch of the studio's latest game, Young Suns, explaining the process by which this took place in a statement that provides an example of what should really be just the bare minimum in these situations. Read more View the full article

In this IP-obsessed world, it is quite easy to wonder if anything will ever actually come to an end. Theoretically, the Final Fantasy 7 trilogy of remakes will be coming to an end next year with Final Fantasy 7 Revelation. Except that might not even be true because a couple of pieces of DLC, about Sephiroth and Vincent Valentine respectively, are also in the works, so who knows when the actual end date is. Whether this is actually the end of Final Fantasy 7 or not, however, doesn't matter, as its director is treating it that way. Read more View the full article

Manufacturing floors, warehouses and production lines rarely stay fixed — tasks change, layouts shift and new products arrive, and most robots can’t keep up without significant reprogramming. Skild AI’s new S1 robot foundation model helps address this, designed to learn previously unseen, long-horizon tasks from a single video demonstration. The model, launched last week, uses video as input to understand and execute the task without updating its weights or undergoing task-specific post-training — a technique called in-context learning. Skild built S1 and conducted the research on NVIDIA AI infrastructure, part of a broader collaboration spanning synthetic data generation, model training, simulation and real-world physical AI deployment. The companies are working together to move adaptable robot intelligence from the lab into factories and other dynamic operating environments. “Learning by experience, and not preprogramming, is the step change that has happened in robotics,” said Deepak Pathak, cofounder and CEO of Skild AI. “NVIDIA Isaac Lab and NVIDIA Cosmos technologies help Skild create the scalable, diverse experience its robots need to learn across many scenarios and embodiments.” The launch comes as the company reached a $100 million annual revenue run rate 10 months after its first commercial deployment. In that time, Skild has built more than 60 deployment partnerships with work spanning manufacturing, logistics, inspection, security, food preparation and other applications. Learning New Work From One Video Most industrial robots are built for fixed jobs, so each new product, process or layout requires more data, retraining and validation. S1 takes a different approach: An operator records a video of the desired task and provides it to the model as a prompt. It interprets the demonstrated intent, objects and sequence, then maps them into actions for the robot in front of it — with no retraining — and often for a task not covered by its pretraining dataset. S1 can perform unfamiliar tasks lasting up to 10 minutes, including plant potting, pancake making, pour-over coffee brewing and kit assembly. These tasks can span dozens of manipulation steps and require the robot to compose skills in sequences it hasn’t previously performed. https://blogs.nvidia.com/wp-content/uploads/2026/09/robotics-promo-skildai-corp-blog-1600x900-one.mp4 In one plant-potting test, the Skild AI team moved from recording the demonstration to autonomous execution on hardware in just 11 minutes. The model can also adjust when objects move, recover from errors and combine skills in sequences that weren’t explicitly programmed. In Skild’s tests on new, multistep tasks, its S1 robot succeeded about 66% of the time at each step, compared with 9% for a similar AI system — a more than sevenfold improvement. Skild also estimates that showing the robot one short video example can be as useful as giving it roughly 380 hands-on training examples. A person collecting those examples manually could take 50-100 hours. From Research to Factory Work S1 breaks the cycle of needing to constantly retrain robots for new factors by letting operators demonstrate new tasks directly without requiring a new dataset or training run for every change. Where customer agreements permit, experience from Skild’s commercial deployments can inform the broader model and help accelerate future deployments. That work is already in action on the factory floor. Skild, NVIDIA and Foxconn are deploying the Skild Brain on dual-arm manipulators for high-precision assembly of NVIDIA Blackwell systems. In one demonstrated workflow, a robot installs a busbar and limit block, fastens 16 screws and adapts to disturbances across a multistep task. The work requires precise motion, contact-aware control, sequence tracking and recovery when the scene differs from the plan. https://blogs.nvidia.com/wp-content/uploads/2026/09/skildai-video-2.mp4 NVIDIA Technology Across the Development Cycle NVIDIA accelerated computing gives Skild the scale to train its shared robot brain using simulation, human video, teleoperation and, where permitted, deployment data. NVIDIA Cosmos open world foundation models help diversify training data and turn video into structured descriptions, while Cosmos Curator helps annotate, filter and organize data at scale. Skild is extensively using NVIDIA’s open simulation frameworks to train and validate its robot brain before real-world deployment. NVIDIA Omniverse libraries and the NVIDIA Isaac Sim framework provide physically based virtual environments for generating data, testing edge cases and validating behaviors. Skild further strengthens the skills of its brain through reinforcement learning in Isaac Lab, an open modular robot learning framework. Powered by the Newton physics engine, Isaac Lab helps Skild’s engineers accurately model various physical parameters, such as forces, contact, collision and pressure, and reduce the simulation-to-reality gap. Skild and NVIDIA are also jointly developing new GPU-accelerated simulation solvers that quickly and accurately model how robots physically touch, grip and manipulate solid objects. They’ll soon be made available to all developers as part of Newton. As models move toward production, NVIDIA Nsight tools help engineers find performance bottlenecks during training, and the NVIDIA TensorRT software development kit optimizes inference so robots can respond quickly in the physical world. Together, these technologies connect the data, simulation, training and deployment stages instead of treating them as separate systems. Read Skild AI’s S1 research and explore the NVIDIA Isaac robotics platform. View the full article

Ubisoft are planning to start testing a new tool that'll allow Prince of Persia The Lost Crown Steam players to access features only usually available via the publishers' Connect launcher without actually having to have said launcher installed. That's according to a Steam announcement post which only appears to be visible to folks who already own a copy of The Lost Crown on Valve's storefront. Read more View the full article

I remember once when I was a child, my uncle was visiting and completely unprompted (and kindly) he gave me a copy of one of the Total War games, I think the Rome one, you'll have to forgive my memory. I'd literally never played a strategy game in my life, but I gave it a go anyway, and quickly found myself thinking, "hey, where are the collectibles? Why's there no triple jump?" The onboarding process did not help me much, and after a failure of a battle where I lost everything, I soon gave up after. So it's because of not particularly strategic people like me that makes me understand why developer Creative Assembly want Total War: Warhammer 40,000 "approachable and accessible". Read more View the full article

The global robotaxi market — physical AI’s first commercial breakthrough — is projected to reach $400 billion by 2035, with over 6 million commercial vehicles in operation as driverless fleets are already moving people through some of the world’s busiest and most complex streets. Deploying a driverless vehicle is one challenge. Scaling a fleet is a next-level computing challenge; it means delivering the same safe, reliable performance across thousands of vehicles. Meeting those demands requires enormous amounts of compute across the robotaxi development lifecycle, from preparing and training AI models to simulating and validating driving behavior, as well as real-time processing in the vehicle. NVIDIA provides an open platform for AI training, simulation and safety validation, with libraries, software development kits, workflows and models that developers can use alongside their own technology stacks. Every major robotaxi program operating at commercial scale today is running on NVIDIA’s modular stack, spanning AI training, simulation, in-vehicle computing — or a combination of the three — to develop and deploy fleets at scale. What Is a Robotaxi Technology Stack? A robotaxi technology stack is the end-to-end set of technologies used to develop, validate and deploy autonomous vehicles (AVs) — from data and AI model training to simulation, safety validation and real-time in-vehicle computing. NVIDIA’s robotaxi and AV platform brings these capabilities together in a three-computer solution: the model training computer, simulation and validation computer, and in-vehicle computer. 1. Training Computer: NVIDIA DGX Robotaxi intelligence advances as programs turn growing volumes of fleet data into increasingly capable models. Driving models can be trained on NVIDIA DGX systems. The NVIDIA Alpamayo portfolio of open reasoning vision language action (VLA) models, simulation frameworks and physical AI datasets gives developers building blocks they can adapt to their own data, requirements and technology stacks. Its reasoning models help address long-tail AV challenges by breaking complex driving situations into smaller steps, reasoning through each one and selecting the safest trajectory. NVIDIA also provides physical AI datasets, reinforcement learning blueprints and recipes for post-training and distillation, helping developers optimize models for their target vehicles. 2. Simulation and Validation Computer: NVIDIA Omniverse and Cosmos on NVIDIA RTX PRO Robotaxi programs can’t rely on physical miles alone to capture rare, long-tail driving scenarios. NVIDIA Omniverse NuRec models reconstruct real-world driving scenarios from sensor data, while NVIDIA Cosmos world foundation models generate physically based variations of them, enabling developers to turn thousands of real-world corner cases into millions of combinations of driving behavior, traffic, weather, lighting and sensor conditions. Running on NVIDIA RTX PRO Servers, NVIDIA Omniverse and Cosmos support closed-loop simulation and validation. The NVIDIA AlpaSim simulation framework extends the workflow for training and evaluating reasoning-based autonomous-driving models, helping developers identify weaknesses before deployment. 3. In-Vehicle Computer and Sensor Architecture: NVIDIA DRIVE Hyperion With DRIVE AGX NVIDIA DRIVE Hyperion is NVIDIA’s modular in-vehicle compute and sensor reference architecture for level-4-ready robotaxis. DRIVE Hyperion 10 pairs dual NVIDIA DRIVE AGX Thor systems-on-a-chip, built on the NVIDIA Blackwell platform, with 14 high-definition cameras, nine radars, three lidars and 12 ultrasonics for real-time, 360-degree sensor fusion. Its redundant compute and sensing design supports fail-operational driving if a sensor or compute component fails. The dual DRIVE AGX Thor is designed to run modern AI workloads — including VLA models — for perception, reasoning, path planning and driving actions. NVIDIA Halos provides a production-ready safety foundation through Halos OS, and a broader validation and certification framework spanning independent inspection, system validation, large-scale simulation and continuous testing from cloud to car. Robotaxi Leaders Adopting NVIDIA’s Robotaxi Technology Stack NVIDIA’s robotaxi ecosystem spans every region where commercial robotaxi services are emerging today: Asia, Europe, the Middle East and North America. Across these markets, mobility providers, AV developers and automakers are adopting NVIDIA’s three-computer architecture to train AI models, simulate and validate driving behavior, and deploy autonomous vehicles at scale. Scaling Robotaxi Services Globally Uber is scaling its fleet of NVIDIA DRIVE Hyperion, with plans to reach 28 cities by 2028. Uber and NVIDIA are also building a robotaxi AI data factory on NVIDIA Cosmos to curate fleet driving data for rare scenarios. Together, Uber and NVIDIA are collaborating with Autobrains, Avride, Lucid, May Mobility, Mercedes-Benz, Momenta, Nissan, Nuro, Pony.ai, Stellantis, Waabi, Wayve, WeRide and Zoox to bring NVIDIA-powered robotaxi services to the Uber platform. May Mobility is planning to operate autonomous ride-hailing services through Uber’s network, while developing its software stack on the NVIDIA DRIVE platform. Bolt uses NVIDIA technologies to develop and scale AVs across Europe. Lyft plans to use NVIDIA DRIVE Hyperion as a reference architecture for future autonomous fleets. May Mobility vehicles are also currently operating on Lyft’s network in Atlanta, powered by NVIDIA DRIVE. Through its partnership with Grab, WeRide plans to bring its DRIVE Hyperion- and DRIVE AGX Thor-based GXR to key markets across Southeast Asia. Waymo partners with NVIDIA to help build its autonomous computing system. Building Robotaxi Intelligence Behind these services, AV developers are using NVIDIA accelerated computing, simulation and in-vehicle platforms to build the intelligence that operators and automakers deploy. Wayve, Nissan and Uber are developing a global robotaxi program using a prototype vehicle that combines Nissan’s vehicle engineering, Wayve’s embodied AI and the NVIDIA DRIVE Hyperion platform. Autobrains is developing robotaxi programs with Uber in Munich and VinFast in Southeast Asia, built on NVIDIA DRIVE Hyperion and enabled by Autobrains’ Agentic AI technology. Zoox uses NVIDIA DRIVE for in-vehicle computing and cloud-based training and simulation. Momenta is developing its software stack based on NVIDIA DRIVE AGX running on DriveOS. Pony.ai developed its new-generation autonomous-driving domain controller with NVIDIA DRIVE Hyperion and DRIVE AGX Thor. Tensor is developing its level 4 Robocar with eight NVIDIA DRIVE AGX Thor systems-on-a-chip in its in-vehicle supercomputer. Waabi expands into the robotaxi market through a deployment collaboration with Uber; its Waabi Driver platform is built on NVIDIA DRIVE AGX Thor. TIER IV and Isuzu are deploying level 4 autonomous buses built on NVIDIA DRIVE Hyperion and DRIVE AGX Thor. Lenovo is supplying its NVIDIA DRIVE AGX Thor-based AD1 level 4 domain controller for a next-generation robotaxi program with SWM. DeepRoute.ai is developing a new generation of robotaxis built on the NVIDIA DRIVE Hyperion platform with DRIVE AGX Thor. Bringing Robotaxis Into Production As these systems move from development into production, automakers are integrating NVIDIA technology into autonomous and robotaxi-ready vehicle programs. Tesla trains its autonomous-driving neural networks on NVIDIA supercomputers. Mercedes-Benz and NVIDIA are collaborating with Uber to develop a robotaxi ecosystem based on the new S-Class, built on the NVIDIA DRIVE Hyperion architecture, full-stack NVIDIA DRIVE AV L4 software, and NVIDIA Alpamayo open AI models, simulation tools and datasets to support reasoning-based, safety-first autonomy. Stellantis, Wayve and Uber are collaborating to develop and deploy L4 driverless mobility services, leveraging NVIDIA DRIVE Hyperion and AI computing technologies. Lucid, Nuro and Uber are developing a global robotaxi service using NVIDIA DRIVE AGX Thor, part of the DRIVE Hyperion platform. Hyundai Motor and Kia are expanding their collaboration with NVIDIA to develop data-driven autonomous-driving systems built on NVIDIA DRIVE Hyperion. NVIDIA will also explore expanded collaboration with Hyundai Motor Group’s joint venture, Motional, to advance level 4 robotaxi services. Geely, alongside its ecosystem partners, plans to develop and commercialize robotaxis using DRIVE Hyperion. Zeekr, a Geely Auto Group brand, has adopted DRIVE AGX Thor for a centralized domain controller. From cloud to car, nearly every layer of the robotaxi platform is being developed on NVIDIA accelerated computing. Explore NVIDIA’s complete platform for robotaxi development. View the full article

AI inference chipmaker d-Matrix today announced it will use NVIDIA NVLink Fusion to connect its next-generation Raptor XPUs to NVIDIA’s AI infrastructure platform — joining a growing roster of ecosystem partners. By connecting Raptor to NVIDIA NVLink scale-up and Spectrum-X scale-out networking, the NVIDIA MGX rack architecture and the broader NVIDIA AI platform, NVLink Fusion gives d-Matrix an accelerated, lower-risk path from custom silicon to large-scale deployment. “Demand for inference is soaring, but capital, time and energy remain finite,” said Sid Sheth, cofounder and CEO of d-Matrix during a press briefing yesterday. “With NVLink Fusion and MGX, we can integrate our Raptor XPUs into a broadly deployed, liquid-cooled architecture, giving customers a faster, lower-risk path to deploy and scale ultralow-latency inference.” The NVIDIA AI platform is vertically integrated and horizontally open. NVLink Fusion extends this openness to XPUs and CPUs, allowing silicon companies to focus on their processor innovations while using NVIDIA infrastructure to deploy them at AI factory scale. From Custom Silicon to Rack-Scale Deployment NVLink Fusion — Quick Reference What is NVIDIA NVLink Fusion? NVIDIA’s platform for integrating third-party custom XPUs and CPUs with NVLink scale-up networking, MGX rack architecture, and the full AI factory platform — spanning compute, networking, storage, security, power, cooling and software. What problem does it solve? Building a custom XPU is hard. Deploying one at scale is harder. NVLink Fusion lets XPU makers skip building rack-scale infrastructure from scratch and plug directly into NVIDIA’s proven, globally deployed AI factory platform. How fast is it? 3x lower XPU-to-XPU latency than off-the-shelf Ethernet, 10x higher packet rates, and 3 TB/s per XPU of all-to-all bandwidth via sixth-generation NVLink. Who are the partners? d-Matrix, AWS, Arm, Intel, Fujitsu, SiFive, Alchip, Astera Labs, GUC, Marvell, MediaTek, Samsung, Cadence, Synopsys, Ayar Labs and Lightmatter. What CPU architectures does it support? All major CPU architectures — Arm, x86 and RISC-V — alongside NVIDIA GPUs. What is a semi-custom AI factory? A semi-custom AI factory pairs NVIDIA’s proven infrastructure with a partner’s custom XPU. NVLink Fusion provides the interconnect, rack architecture, software and supply chain; the partner focuses on differentiated silicon. Building an XPU is only the first step. Deploying it at AI factory scale requires a complete platform spanning networking, rack architecture, power, cooling, software and a proven supply chain. Each of the steps — sourcing chips, integrating high-speed interfaces, validating a scale-up networking solution, designing and certifying rack architecture — adds time, costs and risks. NVLink Fusion lets silicon innovators connect directly into NVIDIA’s proven platform. It’s the high-bandwidth, low-latency technology that connects custom XPUs and CPUs to the NVIDIA stack. By adopting NVLink Fusion, d-Matrix can tap into the NVIDIA MGX ecosystem’s mature, validated rack designs, supply chain, power and cooling infrastructure. By standardizing on a common rack, data centers can be built once and support GPUs, CPUs and XPUs — without requiring a separate rack architecture for each processor type. NVLink Fusion Integrates d-Matrix XPUs Into AI Factories Using NVIDIA NVLink, d-Matrix plans to connect its XPUs in a single high-bandwidth, low-latency scale-up domain. Its racks can also work alongside NVIDIA GPU-based systems like NVIDIA Vera Rubin NVL72 for disaggregated inference. d-Matrix also plans to integrate NVIDIA Vera CPUs, NVIDIA ConnectX-9 SuperNICs, NVIDIA BlueField-4 DPUs and NVIDIA Spectrum-X Ethernet networking. Together with NVLink and MGX, these technologies give d-Matrix a proven foundation to deploy specialized inference alongside NVIDIA systems within flexible, unified AI factories. NVLink Fusion Opens NVIDIA AI Factories to Specialized XPU Architectures The NVIDIA full-stack AI factory platform includes NVIDIA Vera Rubin NVL72, Groq 3 LPX, the Vera CPU rack, Vera BlueField-4 STX storage and Spectrum-6 SPX Ethernet networking. It’s designed to be completely fungible — running every AI workload, model and model architecture — with the best performance per watt and lowest cost per token. NVLink Fusion gives customers the flexibility to match the right compute to each workload within a common AI factory platform, opening access to NVIDIA networking, systems, software and global supply chain. Silicon innovators like d-Matrix can use NVLink Fusion to increase performance, accelerate time to market and reduce the risk of deploying semi-custom AI factories. View the full article

Gear up: The latest PC games and major updates are ready to play on GeForce NOW this week. WARDOGS drops onto the cloud at early-access launch, alongside the Valheim 1.0 Deep North update and Bus Simulator 27 — part of nine new titles joining the cloud. The newest PC releases can demand serious hardware, storage space and upgrade budgets. GeForce NOW puts GeForce RTX-powered performance in the cloud, so members can jump into the newest titles across supported devices without needing expensive PC upgrades to keep up. From a 100-player tactical firefight to a frozen Viking frontier and a growing bus empire, every adventure is ready when members are — no downloads or storage management required. Who Let the ‘WARDOGS’ Out? Take on the Control Zone: WARDOGS launches on GeForce NOW today, bringing BULKHEAD’s large-scale tactical first-person shooter to the cloud at early-access launch. Up to 100 players across three teams battle to control randomized zones in a large-scale military sandbox, where tactical gunplay, combined-arms combat, building and destruction can change the course of a match. There’s no single route to victory. Outfit a loadout, coordinate a squad, fortify a strategic position or take the fight to the enemy in vehicles. Every team play action earns cash, giving players more ways to invest in gear and vehicles that can turn the tide. Ultimate members can stream the fight with GeForce RTX 5080-class performance in the cloud for a tactical advantage. Pick up the battle across supported devices without waiting on a huge game install or clearing local storage first. Ice, Ice in the Deep North, Baby Sharpen the axes and raise the shields – Valheim has left early access with its 1.0 update, letting members stream the final biome in Iron Gate’s Viking survival saga through Steam and Xbox Store. Set sail for the Deep North, a frozen frontier filled with new enemies to face, weapons to craft and strongholds to build before the cold closes in. The 1.0 launch also arrives alongside new platform versions with full crossplay support, making it easier to rally the clan. Whether returning to a long-running world on a PC or Mac or beginning a fresh voyage on a Steam Deck or Amazon Fire TV Stick, members can head to the Deep North across supported devices without waiting for downloads. The Wheels on the Bus Go ‘Round in the Cloud Hop into the driver’s seat. Bus Simulator 27 is now streaming from GeForce NOW. Drive a fleet of more than 45 officially licensed buses from 13 manufacturers through Felicia Bay, a sunny region with two cities, 20 districts and a full day-and-night cycle. Build routes, manage timetables and grow a successful bus company in Story, Career or Sandbox mode. And there’s even more to stream from the GeForce NOW library this week: Bus Simulator 27 (New release on Steam, Sept. 8) Halloween: The Game (New release on Steam, Sept. 8) Honeycomb: The World Beyond (New release on Steam, Sept. 8) Wanderburg (New release on Steam, Sept. 8) Shroom and Gloom (New release on Steam, Sept. 10) Train Sim World 7 – Advanced Access (New release on Steam, Sept. 10) WARDOGS (New release on Steam, Sept. 10) Welcome to Elderfield (New release on Steam, Sept. 10) Death Stranding Director’s Cut (Epic Games Store) Dates listed above reflect when games are released on their respective stores. GeForce NOW availability may vary, as games are onboarded after release and added throughout the week. Keep an eye on GeForce NOW channels and GFN Thursdays for availability updates on announced titles. One GFN community member recently returned after six years, saying NVIDIA DLSS 5 technology renewed their interest in GeForce NOW cloud gaming. Ready to try it out, too? Start with a day pass to test premium cloud gaming before committing to a membership. For those who decide to keep playing, the cost can be applied toward their first monthly membership. What are you planning to play this weekend? Let us know on X or in the comments below. View the full article