Project G-Assist — available through the NVIDIA App — is an experimental AI assistant that helps tune, control and optimize NVIDIA GeForce RTX systems. NVIDIA’s Plug and Play: Project G-Assist Plug-In Hackathon — running virtually through Wednesday, July 16 — invites the community to explore AI and build custom G-Assist plug-ins for a chance to win prizes and be featured on NVIDIA social media channels. G-Assist allows users to control their RTX GPU and other system settings using natural language, thanks to a small language model that runs on device. It can be used from the NVIDIA Overlay in the NVIDIA App without needing to tab out or switch programs. Users can expand its capabilities via plug-ins and even connect it to agentic frameworks such as Langflow. Below, find popular G-Assist plug-ins, hackathon details and tips to get started. Plug-In and Win Join the hackathon by registering and checking out the curated technical resources. G-Assist plug-ins can be built in several ways, including with Python for rapid development, with C++ for performance-critical apps and with custom system interactions for hardware and operating system automation. For those that prefer vibe coding, the G-Assist Plug-In Builder — a ChatGPT-based app that allows no-code or low-code development with natural language commands — makes it easy for enthusiasts to start creating plug-ins. To submit an entry, participants must provide a GitHub repository, including source code file (plugin.py), requirements.txt, manifest.json, config.json (if applicable), a plug-in executable file and READme code. Then, submit a video — between 30 seconds and two minutes — showcasing the plug-in in action. Finally, hackathoners must promote their plug-in using #AIonRTXHackathon on a social media channel: Instagram, TikTok or X. Submit projects via this form by Wednesday, July 16. Judges will assess plug-ins based on three main criteria: 1) innovation and creativity, 2) technical execution and integration, reviewing technical depth, G-Assist integration and scalability, and 3) usability and community impact, aka how easy it is to use the plug-in. Winners will be selected on Wednesday, Aug. 20. First place will receive a GeForce RTX 5090 laptop, second place a GeForce RTX 5080 GPU and third a GeForce RTX 5070 GPU. These top three will also be featured on NVIDIA’s social media channels, get the opportunity to meet the NVIDIA G-Assist team and earn an NVIDIA Deep Learning Institute self-paced course credit. Project G-Assist requires a GeForce RTX 50, 40 or 30 Series Desktop GPU with at least 12GB of VRAM, Windows 11 or 10 operating system, a compatible CPU (Intel Pentium G Series, Core i3, i5, i7 or higher; AMD FX, Ryzen 3, 5, 7, 9, Threadripper or higher), specific disk space requirements and a recent GeForce Game Ready Driver or NVIDIA Studio Driver. Plug-In(spiration) Explore open-source plug-in samples available on GitHub, which showcase the diverse ways on-device AI can enhance PC and gaming workflows. Popular plug-ins include: Google Gemini: Enables search-based queries using Google Search integration and large language model-based queries using Gemini capabilities in real time without needing to switch programs from the convenience of the NVIDIA App Overlay. Discord: Enables users to easily share game highlights or messages directly to Discord servers without disrupting gameplay. IFTTT: Lets users create automations across hundreds of compatible endpoints to trigger IoT routines — such as adjusting room lights and smart shades, or pushing the latest gaming news to a mobile device. Spotify: Lets users control Spotify using simple voice commands or the G-Assist interface to play favorite tracks and manage playlists. Twitch: Checks if any Twitch streamer is currently live and can access detailed stream information such as titles, games, view counts and more. Get G-Assist(ance)  Join the NVIDIA Developer Discord channel to collaborate, share creations and gain support from fellow AI enthusiasts and NVIDIA staff. Save the date for NVIDIA’s How to Build a G-Assist Plug-In webinar on Wednesday, July 9, from 10-11 a.m. PT, to learn more about Project G-Assist capabilities, discover the fundamentals of building, testing and deploying Project G-Assist plug-ins, and participate in a live Q&A session. Explore NVIDIA’s GitHub repository, which provides everything needed to get started developing with G-Assist, including sample plug-ins, step-by-step instructions and documentation for building custom functionalities. Learn more about the ChatGPT Plug-In Builder to transform ideas into functional G-Assist plug-ins with minimal coding. The tool uses OpenAI’s custom GPT builder to generate plug-in code and streamline the development process. NVIDIA’s technical blog walks through the architecture of a G-Assist plug-in, using a Twitch integration as an example. Discover how plug-ins work, how they communicate with G-Assist and how to build them from scratch. Each week, the RTX AI Garage blog series features community-driven AI innovations and content for those looking to learn more about NVIDIA NIM microservices and AI Blueprints, as well as building AI agents, creative workflows, digital humans, productivity apps and more on AI PCs and workstations.  Plug in to NVIDIA AI PC on Facebook, Instagram, TikTok and X — and stay informed by subscribing to the RTX AI PC newsletter. Follow NVIDIA Workstation on LinkedIn and X.  See notice regarding software product information.

Editor’s note: This blog is a part of Into the Omniverse, a series focused on how developers, 3D practitioners and enterprises can transform their workflows using the latest advances in OpenUSD and NVIDIA Omniverse. Simulated driving environments enable engineers to safely and efficiently train, test and validate autonomous vehicles (AVs) across countless real-world and edge-case scenarios without the risks and costs of physical testing. These simulated environments can be created through neural reconstruction of real-world data from AV fleets or generated with world foundation models (WFMs) — neural networks that understand physics and real-world properties. WFMs can be used to generate synthetic datasets for enhanced AV simulation. To help physical AI developers build such simulated environments, NVIDIA unveiled major advances in WFMs at the GTC Paris and CVPR conferences earlier this month. These new capabilities enhance NVIDIA Cosmos — a platform of generative WFMs, advanced tokenizers, guardrails and accelerated data processing tools. Key innovations like Cosmos Predict-2, the Cosmos Transfer-1 NVIDIA preview NIM microservice and Cosmos Reason are improving how AV developers generate synthetic data, build realistic simulated environments and validate safety systems at unprecedented scale. Universal Scene Description (OpenUSD), a unified data framework and standard for physical AI applications, enables seamless integration and interoperability of simulation assets across the development pipeline. OpenUSD standardization plays a critical role in ensuring 3D pipelines are built to scale. NVIDIA Omniverse, a platform of application programming interfaces, software development kits and services for building OpenUSD-based physical AI applications, enables simulations from WFMs and neural reconstruction at world scale. Leading AV organizations — including Foretellix, Mcity, Oxa, Parallel Domain, Plus AI and Uber — are among the first to adopt Cosmos models. Foundations for Scalable, Realistic Simulation Cosmos Predict-2, NVIDIA’s latest WFM, generates high-quality synthetic data by predicting future world states from multimodal inputs like text, images and video. This capability is critical for creating temporally consistent, realistic scenarios that accelerate training and validation of AVs and robots. In addition, Cosmos Transfer, a control model that adds variations in weather, lighting and terrain to existing scenarios, will soon be available to 150,000 developers on CARLA, a leading open-source AV simulator. This greatly expands the broad AV developer community’s access to advanced AI-powered simulation tools. Developers can start integrating synthetic data into their own pipelines using the NVIDIA Physical AI Dataset. The latest release includes 40,000 clips generated using Cosmos. Building on these foundations, the Omniverse Blueprint for AV simulation provides a standardized, API-driven workflow for constructing rich digital twins, replaying real-world sensor data and generating new ground-truth data for closed-loop testing. The blueprint taps into OpenUSD’s layer-stacking and composition arcs, which enable developers to collaborate asynchronously and modify scenes nondestructively. This helps create modular, reusable scenario variants to efficiently generate different weather conditions, traffic patterns and edge cases. Driving the Future of AV Safety To bolster the operational safety of AV systems, NVIDIA earlier this year introduced NVIDIA Halos — a comprehensive safety platform that integrates the company’s full automotive hardware and software stack with AI research focused on AV safety. The new Cosmos models — Cosmos Predict- 2, Cosmos Transfer- 1 NIM and Cosmos Reason — deliver further safety enhancements to the Halos platform, enabling developers to create diverse, controllable and realistic scenarios for training and validating AV systems. These models, trained on massive multimodal datasets including driving data, amplify the breadth and depth of simulation, allowing for robust scenario coverage — including rare and safety-critical events — while supporting post-training customization for specialized AV tasks. At CVPR, NVIDIA was recognized as an Autonomous Grand Challenge winner, highlighting its leadership in advancing end-to-end AV workflows. The challenge used OpenUSD’s robust metadata and interoperability to simulate sensor inputs and vehicle trajectories in semi-reactive environments, achieving state-of-the-art results in safety and compliance. Learn more about how developers are leveraging tools like CARLA, Cosmos, and Omniverse to advance AV simulation in this livestream replay: Hear NVIDIA Director of Autonomous Vehicle Research Marco Pavone on the NVIDIA AI Podcast share how digital twins and high-fidelity simulation are improving vehicle testing, accelerating development and reducing real-world risks. Get Plugged Into the World of OpenUSD Learn more about what’s next for AV simulation with OpenUSD by watching the replay of NVIDIA founder and CEO Jensen Huang’s GTC Paris keynote. Looking for more live opportunities to learn more about OpenUSD? Don’t miss sessions and labs happening at SIGGRAPH 2025, August 10–14. Discover why developers and 3D practitioners are using OpenUSD and learn how to optimize 3D workflows with the self-paced “Learn OpenUSD” curriculum for 3D developers and practitioners, available for free through the NVIDIA Deep Learning Institute. Explore the Alliance for OpenUSD forum and the AOUSD website. Stay up to date by subscribing to NVIDIA Omniverse news, joining the community and following NVIDIA Omniverse on Instagram, LinkedIn, Medium and X.

Mark Theriault founded the startup FITY envisioning a line of clever cooling products: cold drink holders that come with freezable pucks to keep beverages cold for longer without the mess of ice. The entrepreneur started with 3D prints of products in his basement, building one unit at a time, before eventually scaling to mass production. Founding a consumer product company from scratch was a tall order for a single person. Going from preliminary sketches to production-ready designs was a major challenge. To bring his creative vision to life, Theriault relied on AI and his NVIDIA GeForce RTX-equipped system. For him, AI isn’t just a tool — it’s an entire pipeline to help him accomplish his goals. Read more about his workflow below. Plus, GeForce RTX 5050 laptops start arriving today at retailers worldwide, from $999. GeForce RTX 5050 Laptop GPUs feature 2,560 NVIDIA Blackwell CUDA cores, fifth-generation AI Tensor Cores, fourth-generation RT Cores, a ninth-generation NVENC encoder and a sixth-generation NVDEC decoder. In addition, NVIDIA’s Plug and Play: Project G-Assist Plug-In Hackathon — running virtually through Wednesday, July 16 — invites developers to explore AI and build custom G-Assist plug-ins for a chance to win prizes. Save the date for the G-Assist Plug-In webinar on Wednesday, July 9, from 10-11 a.m. PT, to learn more about Project G-Assist capabilities and fundamentals, and to participate in a live Q&A session. From Concept to Completion To create his standout products, Theriault tinkers with potential FITY Flex cooler designs with traditional methods, from sketch to computer-aided design to rapid prototyping, until he finds the right vision. A unique aspect of the FITY Flex design is that it can be customized with fun, popular shoe charms. For packaging design inspiration, Theriault uses his preferred text-to-image generative AI model for prototyping, Stable Diffusion XL — which runs 60% faster with the NVIDIA TensorRT software development kit — using the modular, node-based interface ComfyUI. ComfyUI gives users granular control over every step of the generation process — prompting, sampling, model loading, image conditioning and post-processing. It’s ideal for advanced users like Theriault who want to customize how images are generated. Theriault’s uses of AI result in a complete computer graphics-based ad campaign. Image courtesy of FITY. NVIDIA and GeForce RTX GPUs based on the NVIDIA Blackwell architecture include fifth-generation Tensor Cores designed to accelerate AI and deep learning workloads. These GPUs work with CUDA optimizations in PyTorch to seamlessly accelerate ComfyUI, reducing generation time on FLUX.1-dev, an image generation model from Black Forest Labs, from two minutes per image on the Mac M3 Ultra to about four seconds on the GeForce RTX 5090 desktop GPU. ComfyUI can also add ControlNets — AI models that help control image generation — that Theriault uses for tasks like guiding human poses, setting compositions via depth mapping and converting scribbles to images. Theriault even creates his own fine-tuned models to keep his style consistent. He used low-rank adaptation (LoRA) models — small, efficient adapters into specific layers of the network — enabling hyper-customized generation with minimal compute cost. LoRA models allow Theriault to ideate on visuals quickly. Image courtesy of FITY. “Over the last few months, I’ve been shifting from AI-assisted computer graphics renders to fully AI-generated product imagery using a custom Flux LoRA I trained in house. My RTX 4080 SUPER GPU has been essential for getting the performance I need to train and iterate quickly.” – Mark Theriault, founder of FITY  Theriault also taps into generative AI to create marketing assets like FITY Flex product packaging. He uses FLUX.1, which excels at generating legible text within images, addressing a common challenge in text-to-image models. Though FLUX.1 models can typically consume over 23GB of VRAM, NVIDIA has collaborated with Black Forest Labs to help reduce the size of these models using quantization — a technique that reduces model size while maintaining quality. The models were then accelerated with TensorRT, which provides an up to 2x speedup over PyTorch. To simplify using these models in ComfyUI, NVIDIA created the FLUX.1 NIM microservice, a containerized version of FLUX.1 that can be loaded in ComfyUI and enables FP4 quantization and TensorRT support. Combined, the models come down to just over 11GB of VRAM, and performance improves by 2.5x. Theriault uses the Blender Cycles app to render out final files. For 3D workflows, NVIDIA offers the AI Blueprint for 3D-guided generative AI to ease the positioning and composition of 3D images, so anyone interested in this method can quickly get started. Photorealistic renders. Image courtesy of FITY. Finally, Theriault uses large language models to generate marketing copy — tailored for search engine optimization, tone and storytelling — as well as to complete his patent and provisional applications, work that usually costs thousands of dollars in legal fees and considerable time. Generative AI helps Theriault create promotional materials like the above. Image courtesy of FITY. “As a one-man band with a ton of content to generate, having on-the-fly generation capabilities for my product designs really helps speed things up.” – Mark Theriault, founder of FITY Every texture, every word, every photo, every accessory was a micro-decision, Theriault said. AI helped him survive the “death by a thousand cuts” that can stall solo startup founders, he added. Each week, the RTX AI Garage blog series features community-driven AI innovations and content for those looking to learn more about NVIDIA NIM microservices and AI Blueprints, as well as building AI agents, creative workflows, digital humans, productivity apps and more on AI PCs and workstations.  Plug in to NVIDIA AI PC on Facebook, Instagram, TikTok and X — and stay informed by subscribing to the RTX AI PC newsletter. Follow NVIDIA Workstation on LinkedIn and X.  See notice regarding software product information.

You can trust VideoGamer. Our team of gaming experts spend hours testing and reviewing the latest games, to ensure you're reading the most comprehensive guide possible. Rest assured, all imagery and advice is unique and original. Check out how we test and review games here PlayStation’s annoying regional restrictions on PC games have proved infuriating for gamers all across the world. While most gamers were unaffected, those in some regions found themselves unable to play games like Helldivers 2 and other titles due to the restrictions.  Thankfully, after months of complaints, it appears that PlayStation is finally removing the regional restrictions of its PC releases for a large number of countries. However, not every title has been altered at the time of writing.  Regional restrictions removed from Helldivers 2 and more  As spotted by players online (thanks, Wario64), a number of Steam database updates have changed the regional restrictions of PlayStation games on PC.  Games such as Helldivers 2, Spider-Man 2, God of War: Ragnarok and The Last of Us: Part 2 are now available to purchase in a large number of additional countries. The change appears to be rolling out to PlayStation PC releases at the time of writing. It’s been a long time coming, and the introduction of the restrictions last year was a huge controversy for the company. Since the restrictions were put in place, players who previously purchased Helldivers 2 were unable to play the title online without a VPN.  Additionally, Ghost of Tsushima could be played in a number of countries, but its Legends multiplayer mode was inaccessible due to the regional issues.  Honestly, PlayStation should’ve removed these restrictions far quicker than they initially did. However, the phrase “better late than never” exists for a reason, and we’re happy that more gamers around the world are no longer punished for simply being born in a different country.  For more PlayStation news, read the company’s recent comments about the next generation PlayStation 6 console. Additionally, read about potential PS Plus price increases that could be on the way as the company aims to “maximise profitability”.  Helldivers 2 Platform(s): PC, PlayStation 5 Genre(s): Action, Shooter, Third Person 8 VideoGamer Subscribe to our newsletters! By subscribing, you agree to our Privacy Policy and may receive occasional deal communications; you can unsubscribe anytime. Share

June 13, 20256 min readAir-Conditioning Can Surprisingly Help the Power Grid during Extreme HeatSwitching on air-conditioning during extreme heat doesn’t have to make us feel guilty—it can actually boost power grid reliability and help bring more renewable energy onlineBy Johanna Mathieu & The Conversation US Imagedepotpro/Getty ImagesThe following essay is reprinted with permission from The Conversation, an online publication covering the latest research.As summer arrives, people are turning on air conditioners in most of the U.S. But if you’re like me, you always feel a little guilty about that. Past generations managed without air conditioning – do I really need it? And how bad is it to use all this electricity for cooling in a warming world?If I leave my air conditioner off, I get too hot. But if everyone turns on their air conditioner at the same time, electricity demand spikes, which can force power grid operators to activate some of the most expensive, and dirtiest, power plants. Sometimes those spikes can ask too much of the grid and lead to brownouts or blackouts.On supporting science journalismIf you're enjoying this article, consider supporting our award-winning journalism by subscribing. By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today.Research I recently published with a team of scholars makes me feel a little better, though. We have found that it is possible to coordinate the operation of large numbers of home air-conditioning units, balancing supply and demand on the power grid – and without making people endure high temperatures inside their homes.Studies along these lines, using remote control of air conditioners to support the grid, have for many years explored theoretical possibilities like this. However, few approaches have been demonstrated in practice and never for such a high-value application and at this scale. The system we developed not only demonstrated the ability to balance the grid on timescales of seconds, but also proved it was possible to do so without affecting residents’ comfort.The benefits include increasing the reliability of the power grid, which makes it easier for the grid to accept more renewable energy. Our goal is to turn air conditioners from a challenge for the power grid into an asset, supporting a shift away from fossil fuels toward cleaner energy.Adjustable equipmentMy research focuses on batteries, solar panels and electric equipment – such as electric vehicles, water heaters, air conditioners and heat pumps – that can adjust itself to consume different amounts of energy at different times.Originally, the U.S. electric grid was built to transport electricity from large power plants to customers’ homes and businesses. And originally, power plants were large, centralized operations that burned coal or natural gas, or harvested energy from nuclear reactions. These plants were typically always available and could adjust how much power they generated in response to customer demand, so the grid would be balanced between power coming in from producers and being used by consumers.But the grid has changed. There are more renewable energy sources, from which power isn’t always available – like solar panels at night or wind turbines on calm days. And there are the devices and equipment I study. These newer options, called “distributed energy resources,” generate or store energy near where consumers need it – or adjust how much energy they’re using in real time.One aspect of the grid hasn’t changed, though: There’s not much storage built into the system. So every time you turn on a light, for a moment there’s not enough electricity to supply everything that wants it right then: The grid needs a power producer to generate a little more power. And when you turn off a light, there’s a little too much: A power producer needs to ramp down.The way power plants know what real-time power adjustments are needed is by closely monitoring the grid frequency. The goal is to provide electricity at a constant frequency – 60 hertz – at all times. If more power is needed than is being produced, the frequency drops and a power plant boosts output. If there’s too much power being produced, the frequency rises and a power plant slows production a little. These actions, a process called “frequency regulation,” happen in a matter of seconds to keep the grid balanced.This output flexibility, primarily from power plants, is key to keeping the lights on for everyone.Finding new optionsI’m interested in how distributed energy resources can improve flexibility in the grid. They can release more energy, or consume less, to respond to the changing supply or demand, and help balance the grid, ensuring the frequency remains near 60 hertz.Some people fear that doing so might be invasive, giving someone outside your home the ability to control your battery or air conditioner. Therefore, we wanted to see if we could help balance the grid with frequency regulation using home air-conditioning units rather than power plants – without affecting how residents use their appliances or how comfortable they are in their homes.From 2019 to 2023, my group at the University of Michigan tried this approach, in collaboration with researchers at Pecan Street Inc., Los Alamos National Laboratory and the University of California, Berkeley, with funding from the U.S. Department of Energy Advanced Research Projects Agency-Energy.We recruited 100 homeowners in Austin, Texas, to do a real-world test of our system. All the homes had whole-house forced-air cooling systems, which we connected to custom control boards and sensors the owners allowed us to install in their homes. This equipment let us send instructions to the air-conditioning units based on the frequency of the grid.Before I explain how the system worked, I first need to explain how thermostats work. When people set thermostats, they pick a temperature, and the thermostat switches the air-conditioning compressor on and off to maintain the air temperature within a small range around that set point. If the temperature is set at 68 degrees, the thermostat turns the AC on when the temperature is, say, 70, and turns it off when it’s cooled down to, say, 66.Every few seconds, our system slightly changed the timing of air-conditioning compressor switching for some of the 100 air conditioners, causing the units’ aggregate power consumption to change. In this way, our small group of home air conditioners reacted to grid changes the way a power plant would – using more or less energy to balance the grid and keep the frequency near 60 hertz.Moreover, our system was designed to keep home temperatures within the same small temperature range around the set point.Testing the approachWe ran our system in four tests, each lasting one hour. We found two encouraging results.First, the air conditioners were able to provide frequency regulation at least as accurately as a traditional power plant. Therefore, we showed that air conditioners could play a significant role in increasing grid flexibility. But perhaps more importantly – at least in terms of encouraging people to participate in these types of systems – we found that we were able to do so without affecting people’s comfort in their homes.We found that home temperatures did not deviate more than 1.6 Fahrenheit from their set point. Homeowners were allowed to override the controls if they got uncomfortable, but most didn’t. For most tests, we received zero override requests. In the worst case, we received override requests from two of the 100 homes in our test.In practice, this sort of technology could be added to commercially available internet-connected thermostats. In exchange for credits on their energy bills, users could choose to join a service run by the thermostat company, their utility provider or some other third party.Then people could turn on the air conditioning in the summer heat without that pang of guilt, knowing they were helping to make the grid more reliable and more capable of accommodating renewable energy sources – without sacrificing their own comfort in the process.This article was originally published on The Conversation. Read the original article.

Generative AI has reshaped how people create, imagine and interact with digital content. As AI models continue to grow in capability and complexity, they require more VRAM, or video random access memory. The base Stable Diffusion 3.5 Large model, for example, uses over 18GB of VRAM — limiting the number of systems that can run it well. By applying quantization to the model, noncritical layers can be removed or run with lower precision. NVIDIA GeForce RTX 40 Series and the Ada Lovelace generation of NVIDIA RTX PRO GPUs support FP8 quantization to help run these quantized models, and the latest-generation NVIDIA Blackwell GPUs also add support for FP4. NVIDIA collaborated with Stability AI to quantize its latest model, Stable Diffusion (SD) 3.5 Large, to FP8 — reducing VRAM consumption by 40%. Further optimizations to SD3.5 Large and Medium with the NVIDIA TensorRT software development kit (SDK) double performance. In addition, TensorRT has been reimagined for RTX AI PCs, combining its industry-leading performance with just-in-time (JIT), on-device engine building and an 8x smaller package size for seamless AI deployment to more than 100 million RTX AI PCs. TensorRT for RTX is now available as a standalone SDK for developers. RTX-Accelerated AI NVIDIA and Stability AI are boosting the performance and reducing the VRAM requirements of Stable Diffusion 3.5, one of the world’s most popular AI image models. With NVIDIA TensorRT acceleration and quantization, users can now generate and edit images faster and more efficiently on NVIDIA RTX GPUs. Stable Diffusion 3.5 quantized FP8 (right) generates images in half the time with similar quality as FP16 (left). Prompt: A serene mountain lake at sunrise, crystal clear water reflecting snow-capped peaks, lush pine trees along the shore, soft morning mist, photorealistic, vibrant colors, high resolution. To address the VRAM limitations of SD3.5 Large, the model was quantized with TensorRT to FP8, reducing the VRAM requirement by 40% to 11GB. This means five GeForce RTX 50 Series GPUs can run the model from memory instead of just one. SD3.5 Large and Medium models were also optimized with TensorRT, an AI backend for taking full advantage of Tensor Cores. TensorRT optimizes a model’s weights and graph — the instructions on how to run a model — specifically for RTX GPUs. FP8 TensorRT boosts SD3.5 Large performance by 2.3x vs. BF16 PyTorch, with 40% less memory use. For SD3.5 Medium, BF16 TensorRT delivers a 1.7x speedup. Combined, FP8 TensorRT delivers a 2.3x performance boost on SD3.5 Large compared with running the original models in BF16 PyTorch, while using 40% less memory. And in SD3.5 Medium, BF16 TensorRT provides a 1.7x performance increase compared with BF16 PyTorch. The optimized models are now available on Stability AI’s Hugging Face page. NVIDIA and Stability AI are also collaborating to release SD3.5 as an NVIDIA NIM microservice, making it easier for creators and developers to access and deploy the model for a wide range of applications. The NIM microservice is expected to be released in July. TensorRT for RTX SDK Released Announced at Microsoft Build — and already available as part of the new Windows ML framework in preview — TensorRT for RTX is now available as a standalone SDK for developers. Previously, developers needed to pre-generate and package TensorRT engines for each class of GPU — a process that would yield GPU-specific optimizations but required significant time. With the new version of TensorRT, developers can create a generic TensorRT engine that’s optimized on device in seconds. This JIT compilation approach can be done in the background during installation or when they first use the feature. The easy-to-integrate SDK is now 8x smaller and can be invoked through Windows ML — Microsoft’s new AI inference backend in Windows. Developers can download the new standalone SDK from the NVIDIA Developer page or test it in the Windows ML preview. For more details, read this NVIDIA technical blog and this Microsoft Build recap. Join NVIDIA at GTC Paris At NVIDIA GTC Paris at VivaTech — Europe’s biggest startup and tech event — NVIDIA founder and CEO Jensen Huang yesterday delivered a keynote address on the latest breakthroughs in cloud AI infrastructure, agentic AI and physical AI. Watch a replay. GTC Paris runs through Thursday, June 12, with hands-on demos and sessions led by industry leaders. Whether attending in person or joining online, there’s still plenty to explore at the event. Each week, the RTX AI Garage blog series features community-driven AI innovations and content for those looking to learn more about NVIDIA NIM microservices and AI Blueprints, as well as building AI agents, creative workflows, digital humans, productivity apps and more on AI PCs and workstations.  Plug in to NVIDIA AI PC on Facebook, Instagram, TikTok and X — and stay informed by subscribing to the RTX AI PC newsletter. Follow NVIDIA Workstation on LinkedIn and X.  See notice regarding software product information.

AI researchers have recently been asking themselves a version of the question, “Is that really Zuck?”As first reported by Bloomberg, the Meta CEO has been personally asking top AI talent to join his new “superintelligence” AI lab and reboot Llama. His recruiting process typically goes like this: a cold outreach via email or WhatsApp that cites the recruit’s work history and requests a 15-minute chat. Dozens of researchers have gotten these kinds of messages at Google alone. For those who do agree to hear his pitch (amazingly, not all of them do), Zuckerberg highlights the latitude they’ll have to make risky bets, the scale of Meta’s products, and the money he’s prepared to invest in the infrastructure to support them. He makes clear that this new team will be empowered and sit with him at Meta’s headquarters, where I’m told the desks have already been rearranged for the incoming team.Most of the headlines so far have focused on the eye-popping compensation packages Zuckerberg is offering, some of which are well into the eight-figure range. As I’ve covered before, hiring the best AI researcher is like hiring a star basketball player: there are very few of them, and you have to pay up. Case in point: Zuckerberg basically just paid 14 Instagrams to hire away Scale AI CEO Alexandr Wang. It’s easily the most expensive hire of all time, dwarfing the billions that Google spent to rehire Noam Shazeer and his core team from Character.AI (a deal Zuckerberg passed on). “Opportunities of this magnitude often come at a cost,” Wang wrote in his note to employees this week. “In this instance, that cost is my departure.”Zuckerberg’s recruiting spree is already starting to rattle his competitors. The day before his offer deadline for some senior OpenAI employees, Sam Altman dropped an essay proclaiming that “before anything else, we are a superintelligence research company.” And after Zuckerberg tried to hire DeepMind CTO Koray Kavukcuoglu, he was given a larger SVP title and now reports directly to Google CEO Sundar Pichai. I expect Wang to have the title of “chief AI officer” at Meta when the new lab is announced. Jack Rae, a principal researcher from DeepMind who has signed on, will lead pre-training. Meta certainly needs a reset. According to my sources, Llama has fallen so far behind that Meta’s product teams have recently discussed using AI models from other companies (although that is highly unlikely to happen). Meta’s internal coding tool for engineers, however, is already using Claude. While Meta’s existing AI researchers have good reason to be looking over their shoulders, Zuckerberg’s $14.3 billion investment in Scale is making many longtime employees, or Scaliens, quite wealthy. They were popping champagne in the office this morning. Then, Wang held his last all-hands meeting to say goodbye and cried. He didn’t mention what he would be doing at Meta. I expect his new team will be unveiled within the next few weeks after Zuckerberg gets a critical number of members to officially sign on. Tim Cook. Getty Images / The VergeApple’s AI problemApple is accustomed to being on top of the tech industry, and for good reason: the company has enjoyed a nearly unrivaled run of dominance. After spending time at Apple HQ this week for WWDC, I’m not sure that its leaders appreciate the meteorite that is heading their way. The hubris they display suggests they don’t understand how AI is fundamentally changing how people use and build software.Heading into the keynote on Monday, everyone knew not to expect the revamped Siri that had been promised the previous year. Apple, to its credit, acknowledged that it dropped the ball there, and it sounds like a large language model rebuild of Siri is very much underway and coming in 2026.The AI industry moves much faster than Apple’s release schedule, though. By the time Siri is perhaps good enough to keep pace, it will have to contend with the lock-in that OpenAI and others are building through their memory features. Apple and OpenAI are currently partners, but both companies want to ultimately control the interface for interacting with AI, which puts them on a collision course. Apple’s decision to let developers use its own, on-device foundational models for free in their apps sounds strategically smart, but unfortunately, the models look far from leading. Apple ran its own benchmarks, which aren’t impressive, and has confirmed a measly context window of 4,096 tokens. It’s also saying that the models will be updated alongside its operating systems — a snail’s pace compared to how quickly AI companies move. I’d be surprised if any serious developers use these Apple models, although I can see them being helpful to indie devs who are just getting started and don’t want to spend on the leading cloud models. I don’t think most people care about the privacy angle that Apple is claiming as a differentiator; they are already sharing their darkest secrets with ChatGPT and other assistants. Some of the new Apple Intelligence features I demoed this week were impressive, such as live language translation for calls. Mostly, I came away with the impression that the company is heavily leaning on its ChatGPT partnership as a stopgap until Apple Intelligence and Siri are both where they need to be. AI probably isn’t a near-term risk to Apple’s business. No one has shipped anything close to the contextually aware Siri that was demoed at last year’s WWDC. People will continue to buy Apple hardware for a long time, even after Sam Altman and Jony Ive announce their first AI device for ChatGPT next year. AR glasses aren’t going mainstream anytime soon either, although we can expect to see more eyewear from Meta, Google, and Snap over the coming year. In aggregate, these AI-powered devices could begin to siphon away engagement from the iPhone, but I don’t see people fully replacing their smartphones for a long time. The bigger question after this week is whether Apple has what it takes to rise to the occasion and culturally reset itself for the AI era. I would have loved to hear Tim Cook address this issue directly, but the only interview he did for WWDC was a cover story in Variety about the company’s new F1 movie.ElsewhereAI agents are coming. I recently caught up with Databricks CEO Ali Ghodsi ahead of his company’s annual developer conference this week in San Francisco. Given Databricks’ position, he has a unique, bird’s-eye view of where things are headed for AI. He doesn’t envision a near-term future where AI agents completely automate real-world tasks, but he does predict a wave of startups over the next year that will come close to completing actions in areas such as travel booking. He thinks humans will need (and want) to approve what an agent does before it goes off and completes a task. “We have most of the airplanes flying automated, and we still want pilots in there.”Buyouts are the new normal at Google. That much is clear after this week’s rollout of the “voluntary exit program” in core engineering, the Search organization, and some other divisions. In his internal memo, Search SVP Nick Fox was clear that management thinks buyouts have been successful in other parts of the company that have tried them. In a separate memo I saw, engineering exec Jen Fitzpatrick called the buyouts an “opportunity to create internal mobility and fresh growth opportunities.” Google appears to be attempting a cultural reset, which will be a challenging task for a company of its size. We’ll see if it can pull it off. Evan Spiegel wants help with AR glasses. I doubt that his announcement that consumer glasses are coming next year was solely aimed at AR developers. Telegraphing the plan and announcing that Snap has spent $3 billion on hardware to date feels more aimed at potential partners that want to make a bigger glasses play, such as Google. A strategic investment could help insulate Snap from the pain of the stock market. A full acquisition may not be off the table, either. When he was recently asked if he’d be open to a sale, Spiegel didn’t shut it down like he always has, but instead said he’d “consider anything” that helps the company “create the next computing platform.”Link listMore to click on:If you haven’t already, don’t forget to subscribe to The Verge, which includes unlimited access to Command Line and all of our reporting.As always, I welcome your feedback, especially if you’re an AI researcher fielding a juicy job offer. You can respond here or ping me securely on Signal.Thanks for subscribing.See More:

You can trust VideoGamer. Our team of gaming experts spend hours testing and reviewing the latest games, to ensure you're reading the most comprehensive guide possible. Rest assured, all imagery and advice is unique and original. Check out how we test and review games here The Squid Game collaboration is the next big thing for Fortnite. Its release date is right around the corner, and Epic Games has already revealed some of the things that will come with it. The iconic South Korean series will bring much more than just cosmetics, and here’s everything you need to know about it. In this article, we will reveal everything we know about Squid Game skins in Fortnite, as well as Creative tools. Furthermore, we will reveal the release date and take a look at several leaks that have come out since the collab announcement. Will the Squid Game collaboration bring Fortnite skins? According to trusted Fortnite leakers, the Squid Game partnership will introduce new cosmetics, including character skins. At the moment, it’s unknown what these skins will look like, but we should find out more details soon. The release date of the Squid Game collab is set for Friday, June 27, which is also the release date of the last season of the series. Earlier this month, Epic Games confirmed that the collaboration will bring new UEFN (Unreal Editor for Fortnite) tools. Thanks to this, creators will be able to make Squid Game-themed maps with new items and mechanics. The Squid Game collaboration will bring new Fortnite cosmetics. Image by VideoGamer Epic has already released a cryptic teaser for the collab which reveals the following: “Red Greens, Square Meals, Affluent Arrivals, June 27th.” With less than two weeks to go until the big update, we expect even more teasers and possibly skin leaks. Considering how popular Squid Game is, this could become one of Fortnite’s most iconic collaborations. The next Fortnite update is set to come out on Tuesday, June 17. Since this update will contain Squid Game data, we could see more early leaks in just a few more days. Fortnite Platform(s): Android, iOS, macOS, Nintendo Switch, PC, PlayStation 4, PlayStation 5, Xbox One, Xbox Series S/X Genre(s): Action, Massively Multiplayer, Shooter 9 VideoGamer Subscribe to our newsletters! By subscribing, you agree to our Privacy Policy and may receive occasional deal communications; you can unsubscribe anytime. Share

June 13, 20255 min readFive Climate Issues to Watch When Trump Goes to CanadaPresident Trump will attend the G7 summit on Sunday in a nation he threatened to annex. He will also be an outlier on climate issuesBy Sara Schonhardt & E&E News Saul Loeb/AFP via Getty ImagesCLIMATEWIRE | The world’s richest nations are gathering Sunday in the Canadian Rockies for a summit that could reveal whether President Donald Trump's policies are shaking global climate efforts.The Group of Seven meeting comes at a challenging time for international climate policy. Trump’s tariff seesaw has cast a shade over the global economy, and his domestic policies have threatened billions of dollars in funding for clean energy programs. Those pressures are colliding with record-breaking temperatures worldwide and explosive demand for energy, driven by power-hungry data centers linked to artificial intelligence technologies.On top of that, Trump has threatened to annex the host of the meeting — Canada — and members of his Cabinet have taken swipes at Europe’s use of renewable energy. Rather than being aligned with much of the world's assertion that fossil fuels should be tempered, Trump embraces the opposite position — drill for more oil and gas and keep burning coal, while repealing environmental regulations on the biggest sources of U.S. carbon pollution.On supporting science journalismIf you're enjoying this article, consider supporting our award-winning journalism by subscribing. By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today.Those moves illustrate his rejection of climate science and underscore his outlying positions on global warming in the G7.Here are five things to know about the summit.Who will be there?The group comprises Canada, France, Germany, Italy, Japan, the United Kingdom and the United States — plus the European Union. Together they account for more than 40 percent of gross domestic product globally and around a quarter of all energy-related carbon dioxide pollution, according to the International Energy Agency. The U.S. is the only one among them that is not trying to hit a carbon reduction goal.Some emerging economies have also been invited, including Mexico, India, South Africa and Brazil, the host of this year’s COP30 climate talks in November.Ahead of the meeting, the office of Canada's prime minister, Mark Carney, said he and Brazilian President Luiz Inácio Lula da Silva agreed to strengthen cooperation on energy security and critical minerals. White House press secretary Karoline Leavitt said Trump would be having "quite a few" bilateral meetings but that his schedule was in flux.The G7 first came together 50 years ago following the Arab oil embargo. Since then, its seven members have all joined the United Nations Framework Convention on Climate Change and the Paris Agreement. The U.S. is the only nation in the group that has withdrawn from the Paris Agreement, which counts almost every country in the world as a signatory.What’s on the table?Among Canada’s top priorities as host are strengthening energy security and fortifying critical mineral supply chains. Carney would also like to see some agreement on joint wildfire action.Expanding supply chains for critical minerals — and competing more aggressively with China over those resources — could be areas of common ground among the leaders. Climate change is expected to remain divisive. Looming over the discussions will be tariffs — which Trump has applied across the board — because they will have an impact on the clean energy transition.“I think probably the majority of the conversation will be less about climate per se, or certainly not using climate action as the frame, but more about energy transition and infrastructure as a way of kind of bridging the known gaps between most of the G7 and where the United States is right now,” said Dan Baer, director of the Europe program at the Carnegie Endowment for International Peace.What are the possible outcomes?The leaders could issue a communique at the end of their meeting, but those statements are based on consensus, something that would be difficult to reach without other G7 countries capitulating to Trump. Bloomberg reported Wednesday that nations won’t try to reach a joint agreement, in part because bridging gaps on climate change could be too hard.Instead, Carney could issue a chair’s summary or joint statements based on certain issues.The question is how far Canada will go to accommodate the U.S., which could try to roll back past statements on advancing clean energy, said Andrew Light, former assistant secretary of Energy for international affairs, who led ministerial-level negotiations for the G7.“They might say, rather than watering everything down that we accomplished in the last four years, we just do a chair's statement, which summarizes the debate,” Light said. “That will show you that you didn't get consensus, but you also didn't get capitulation.”What to watch forIf there is a communique, Light says he’ll be looking for whether there is tougher language on China and any signal of support for science and the Paris Agreement. During his first term, Trump refused to support the Paris accord in the G7 and G20 declarations.The statement could avoid climate and energy issues entirely. But if it backtracks on those issues, that could be a sign that countries made a deal by trading climate-related language for something else, Light said.Baer of Carnegie said a statement framed around energy security and infrastructure could be seen as a “pragmatic adaptation” to the U.S. administration, rather than an indication that other leaders aren’t concerned about climate change.Climate activists have lower expectations.“Realistically, we can expect very little, if any, mention of climate change,” said Caroline Brouillette, executive director of Climate Action Network Canada.“The message we should be expecting from those leaders is that climate action remains a priority for the rest of the G7 … whether it's on the transition away from fossil fuels and supporting developing countries through climate finance,” she said. “Especially now that the U.S. is stepping back, we need countries, including Canada, to be stepping up.”Best- and worst-case scenariosThe challenge for Carney will be preventing any further rupture with Trump, analysts said.In 2018, Trump made a hasty exit from the G7 summit, also in Canada that year, due largely to trade disagreements. He retracted his support for the joint statement.“The best, [most] realistic case outcome is that things don't get worse,” said Baer.The worst-case scenario? Some kind of “highly personalized spat” that could add to the sense of disorder, he added.“I think the G7 on the one hand has the potential to be more important than ever, as fewer and fewer platforms for international cooperation seem to be able to take action,” Baer said. “So it's both very important and also I don't have super-high expectations.”Reprinted from E&E News with permission from POLITICO, LLC. Copyright 2025. E&E News provides essential news for energy and environment professionals.

You can trust VideoGamer. Our team of gaming experts spend hours testing and reviewing the latest games, to ensure you're reading the most comprehensive guide possible. Rest assured, all imagery and advice is unique and original. Check out how we test and review games here Season 2.5 of Marvel Rivals has completely shaken up the competitive meta. Ultron, a new Strategist, has performed much better than the community had expected him to, while Peni Parker has had the highest win rate ever since the season was released. Many other heroes have been changed, but one in particular has surpassed all expectations. In this article, we will dive deeper into Marvel Rivals win rates in Season 2.5. The situation has drastically changed over the past month, and some of the balance changes have turned out to be the right move. Marvel Rivals Season 2.5 has skyrocketed Jeff’s win rate With the release of Season 2.5, NetEase introduced a major rework for Jeff the Land Shark. The fan-favorite Strategist went through ground-breaking changes, which forced players to change their playstyle. Initially, the community believed that Jeff was nerfed to the ground. However, this Marvel Rivals rework has turned out to be the right move. So far this season, Jeff the Land Shark holds a 46.39% win rate. While this is certainly not impressive, it actually surpasses the win rates of Invisible Woman (45.54%) and Luna Snow (45.28%), both of whom are considered amazing healers. Jeff’s win rate has been much better in Marvel Rivals Season 2.5. Image by VideoGamer In addition to this, Jeff is the hero with the largest win rate increase in comparison to Season 2, as it increased by 4.35%. The only other hero with a comparable change is Peni Parker, whose win rate has jumped by 4.09%. Jeff is still far from a top-tier character in the game. However, there is no denying that he’s now a viable pick who can keep his teammates alive while also eliminating the enemy team. With Marvel Rivals Season 3 dropping in a few weeks, we expect even more balance changes to come out. While NetEase may buff Jeff even more, he seems to have reached a balanced “sweet spot” that doesn’t require immediate adjustments. Marvel Rivals Platform(s): macOS, PC, PlayStation 5, Xbox Series S, Xbox Series X Genre(s): Fighting, Shooter Subscribe to our newsletters! By subscribing, you agree to our Privacy Policy and may receive occasional deal communications; you can unsubscribe anytime. Share