Take a look at the Steam Hardware & Software Survey for January 2025, and you'll find no fewer than three graphics cards from the now-venerable NVIDIA GeForce GTX 10-Series lineup. We mean no offense to these battle-proven units, but we suspect that if your machine is still rocking one of these cards, you're probably looking for an upgrade. While we won't deter you from leapfrogging into next-gen territory with a GeForce RTX 50 Series card, we understand that not every gamer's budget can cover one of these chart-topping models.

So here's a wallet-friendly alternative that's still very relevant in 2025: the ASUS Dual GeForce RTX 3060. Available for just about $300 (USD), equipped with 12 GB of VRAM, compatible with the most popular GeForce RTX features, and ready for a wide range of builds with its low wattage requirements and compact design, this is the best budget graphics card we offer in 2025 for gamers who prefer NVIDIA GPUs.

Advantech, a global leader in industrial and embedded computing, today announced the launch of seven new server platforms built on Intel Xeon 6 processors, optimized for industrial, transportation and communications applications. Designed to meet the increasing demands of complex AI storage and networking workloads, these innovative edge servers and network appliances provide superior performance, reliability, and scalability for system integrators, solutions, and service provider customers.

Intel Xeon 6 - Exceptional Performance for the Widest Range of Workloads
Intel Xeon 6 processors feature advanced performance and efficiency cores, delivering up to 86 cores per CPU, DDR5 memory support with speeds up to 6400 MT/s, and PCIe Gen 5 lanes for high-speed connectivity. Designed to optimize both compute-intensive and scale-out workloads, these processors ensure seamless integration across a wide array of applications.

Businesses across every industry are rolling out AI services this year. For Microsoft, Oracle, Perplexity, Snap and hundreds of other leading companies, using the NVIDIA AI inference platform—a full stack comprising world-class silicon, systems and software—is the key to delivering high-throughput and low-latency inference and enabling great user experiences while lowering cost. NVIDIA's advancements in inference software optimization and the NVIDIA Hopper platform are helping industries serve the latest generative AI models, delivering excellent user experiences while optimizing total cost of ownership. The Hopper platform also helps deliver up to 15x more energy efficiency for inference workloads compared to previous generations.

AI inference is notoriously difficult, as it requires many steps to strike the right balance between throughput and user experience. But the underlying goal is simple: generate more tokens at a lower cost. Tokens represent words in a large language model (LLM) system—and with AI inference services typically charging for every million tokens generated, this goal offers the most visible return on AI investments and energy used per task. Full-stack software optimization offers the key to improving AI inference performance and achieving this goal.

NVIDIA's deep learning super sampling (DLSS) has undergone many iterations to the current version 4 with the transformer model, delivering new technologies such as DLSS Multi Frame Generation, predicting multiple frames in advance to generate the upcoming frame, and increasing the frame output per second. However, not every NVIDIA GPU generation supports these more modern DLSS technologies. In an interview with Digital Foundry, Bryan Catanzaro, VP of Applied Deep Learning Research at NVIDIA, commented on trickling down some DLSS technologies to older GPU generations. For example, DLSS Ray Reconstruction, Super Resolution, and Deep Learning Anti-Aliasing (DLAA) work on NVIDIA GeForce RTX 20/30/40/50 series GPUs. However, the RTX 40 series carries an exclusive DLSS Frame Generation, and the newest RTX 50 series carries the DLSS Multi Frame Generation as an exclusive feature.

However, there is hope for older hardware. "I think this is primarily a question of optimization and also engineering and then the ultimate user experience. We're launching this Frame Generation, the best Multi Frame Generation technology, with the 50 Series, and we'll see what we're able to squeeze out of older hardware in the future." So, frame generation will most likely arrive on the older RTX 30 series, with even a slight possibility of the RTX 20 series getting the DLSS frame generation. Due to compute budget constraints, the multi-frame generation will most likely stay an RTX 50 series exclusive as it has more raw computing power to handle this technology.

At the RTX "Blackwell" Editor's Day during CES 2025, NVIDIA pulled back the curtain on one of its most powerful tools: a dedicated supercomputer that has been continuously improving DLSS (Deep Learning Super Sampling) for the past six years. Brian Catanzaro, NVIDIA's VP of applied deep learning research, disclosed that thousands of the company's latest GPUs have been working round-the-clock, analyzing and perfecting the technology that has revolutionized gaming graphics. "We have a big supercomputer at NVIDIA that is running 24/7, 365 days a year improving DLSS," Catanzaro explained during his presentation on DLSS 4. The supercomputer's primary task involves analyzing failures in DLSS performance, such as ghosting, flickering, or blurriness across hundreds of games. When issues are identified, the system augments its training data sets with new examples of optimal graphics and challenging scenarios that DLSS needs to address.

DLSS 4 is the first move from convolutional neural networks to a transformer model that runs locally on client PCs. The continuous learning process has been crucial in refining the technology, with the dedicated supercomputer serving as the backbone of this evolution. The scale of resources allocated to DLSS development is massive, as the entire pipeline for a self-improving DLSS model must consist of not only thousands but tens of thousands of GPUs. Of course, a company making 100,000 GPU data centers (xAI's Colossus) must save some for itself and is proactively using it to improve its software stack. NVIDIA's CEO Jensen Huang famously said that DLSS can predict the future. Of course, these statements are to be tested when the Blackwell series launches. However, the approach of using massive data centers to improve DLSS is quite interesting, and with each new GPU generation NVIDIA release, the process is getting significantly sped up.

ADLINK Technology Inc., a global leader in edge computing, unveiled its new "DLAP Supreme Series", an edge generative AI platform. By integrating Phison's innovative aiDAPTIV+ AI solution, this series overcomes memory limitations in edge generative AI applications, significantly enhancing AI computing capabilities on edge devices. Without increasing high hardware costs, the DLAP Supreme series achieves notable AI performance improvements, helping enterprises reduce the cost barriers of AI deployment and accelerating the adoption of generative AI across various industries, especially in edge computing.

Lower AI Computing Costs and Significantly Improved Performance
As generative AI continues to penetrate various industries, many edge devices encounter performance bottlenecks due to insufficient DRAM capacity when executing large language models, affecting model operations and even causing issues such as inadequate token length. The DLAP Supreme series, leveraging aiDAPTIV+ technology, effectively overcomes these limitations and significantly enhances computing performance. Additionally, it supports edge devices in conducting generative language model training, enabling them with AI model training capabilities and improving their autonomous learning and adaptability.

Basemark announced today the release of a groundbreaking cross-platform ray tracing benchmark, GPUScore: Breaking Limit. This new benchmark is designed to evaluate the performance of the full range of ray tracing capable devices, including smartphones, tablets, laptops and high-end desktops with discrete GPUs. With support for multiple operating systems and graphics APIs, Breaking Limit provides a comprehensive performance evaluation across various platforms and devices.

As ray tracing technology becomes increasingly prevalent in consumer electronics, from high-end desktops to portable devices like laptops and smartphones, there is a critical need for a benchmark that can accurately assess and compare performance across different devices and platforms. Breaking Limit addresses this gap, providing valuable insights into how various devices handle hardware-accelerated graphics rendering. The benchmark is an essential tool for developers, manufacturers, and consumers to measure and compare the performance of real-time ray tracing rendering across different hardware and software environments reliably.

Yesterday, NVIDIA released the latest version of its Deep Learning Super Sampling (DLSS) 3.7.0. The newest version promises to improve image quality. Among the most notable additions is the now default "E" quality preset. This builds upon the previous DLSS versions but introduces noticeably sharper images, generally improved fine detail stability, reduced ghosting, and better temporal stability in general compared to DLSS 3.5. It has been tested with Cyberpunk 2077 in the YouTube video with the comparison between DLSS 3.5.10, DLSS 3.6.0, and the newest DLSS 3.7.0. Additionally, some Reddit users reported seeing a noticeable difference on Horizon Forbidden West at 1440p.

Generally, the DLSS 3.7.0 version can be a drop-in replacement to the older DLSS versions. Using DLSS Tweaks, or even manually, users can patch in the latest DLSS 3.7.0 DLL and force games that weren't shipped initially or updated to support the latest DLSS 3.7.0 DLL file. We have the latest DLL download up on our Downloads section on TechPowerUp, so users can install DLSSTweaks and grab the desired file version on our website.

Grab the latest DLSS 3.7.0 DLL file here.

MSI, a forefront leader in True Gaming hardware, proudly announces the incorporation of NVIDIA GeForce RTX 40 SUPER Series graphics cards into its latest 14th generation AI gaming desktops. The MEG Trident X2 14th, MPG Infinite X2 14th, MPG Trident AS 14th, MAG Infinite S3 14th, and MAG Codex 6 14th, initially featuring the NVIDIA GeForce RTX 40 Series graphics cards, now boast the cutting-edge RTX 40 SUPER Series, ushering in a new era of gaming excellence.

At the heart of these 14th gen AI gaming desktops lies the revolutionary RTX 40 SUPER Series, which are GeForce RTX 4080 SUPER, GeForce RTX 4070 Ti SUPER, and GeForce RTX 4070 SUPER. This series reshapes the gaming experience with cutting-edge AI capabilities, surpassing the speed of their predecessors. Equipped with RTX platform superpowers, these GPUs elevate the performance of games, applications, and AI tasks, marking a significant advancement in the gaming landscape.

GIGABYTE TECHNOLOGY Co. Ltd, a leading manufacturer of premium gaming hardware, today launched GeForce RTX 40 SUPER series graphics cards powered by NVIDIA ADA Lovelace architecture. Featuring AORUS, AERO, GAMING, EAGLE and WINDFORCE series, the lineup completely serves the needs for every customer, from gamers, creators, to AI developers.

The new GeForce RTX SUPER GPUs are the ultimate way to experience AI on PCs. Specialized AI Tensor Cores deliver up to 836 AI TOPS to deliver transformative capabilities for AI in gaming, creating and everyday productivity. PC gamers demand the very best in visual quality, and AI-powered NVIDIA Deep Learning Super Sampling (DLSS) Super Resolution, Frame Generation and Ray Reconstruction combine with ray tracing to offer stunning worlds. With DLSS, seven out of eight pixels can be AI-generated, accelerating full ray tracing by up to 4x with better image quality.

Samsung Electronics Co., Ltd. today announced the release of its most intelligent PC lineup yet: Galaxy Book4 Ultra, Book4 Pro and Book4 Pro 360. The latest series comes with a new intelligent processor, a more vivid and interactive display and a robust security system—beginning a new era of AI PCs that offers ultimate productivity, mobility and connectivity. These enhancements not only improve the device itself but also elevate the entire Samsung Galaxy ecosystem, advancing the PC category and accelerating Samsung's vision of AI innovation—for both today and tomorrow.

"Samsung is committed to empowering people to experience new possibilities that enhance their everyday lives. This new paradigm can be achieved through our expansive Galaxy ecosystem and open collaboration with other industry leaders," said TM Roh, President and Head of Mobile eXperience Business at Samsung Electronics. "The Galaxy Book4 series plays a key role in bringing best-in-class connectivity to our ecosystem that will broaden how people interact with their PC, phone, tablet and other devices for truly intelligent and connected experiences."

AMD FidelityFX Super Resolution (FSR) is an open-source resolution upscaling technology that takes lower-resolution input and uses super-resolution temporal upscaling technology, frame generation using AMD Fluid Motion Frames (AFMF) technology, and built-in latency reduction technology to provide greater-resolution output images from lower-resolution settings. While the technology is open-source, it battles in market share with NVIDIA and the company's Deep Learning Super Sampling (DLSS). However, in the mobile space, there hasn't been much talk about implementing upscaling technology up until now. According to a popular leaker @Tech_Reve on X/Twitter, we have information that AMD is collaborating with Samsung and Qualcomm to standardize on upscaling technology implementations in mobile SoCs.

Not only does the leak imply that the AMD FSR technology will be used in Samsung's upcoming Exynos SoC, but some AMD ray tracing will be present as well. The leaker has mentioned Qualcomm, which means that future iterations of Snapdragon are up to adopt the FSR algorithmic approach to resolution upscaling. We will see how and when, but with mobile games growing in size and demand, FSR could come in handy to provide mobile gamers with a better experience. Primarily, this targets Android devices, which Qualcomm supplies, where Apple's iPhone recently announced MetalFX Upscaling technology with an A17 Pro chip.

Three leading European generative AI startups joined NVIDIA founder and CEO Jensen Huang this week to talk about the new era of computing. More than 500 developers, researchers, entrepreneurs and executives from across Europe and further afield packed into the Spindler and Klatt, a sleek, riverside gathering spot in Berlin. Huang started the reception by touching on the message he delivered Monday at the Berlin Summit for Earth Virtualization Engines (EVE), an international collaboration focused on climate science. He shared details of NVIDIA's Earth-2 initiative and how accelerated computing, AI-augmented simulation and interactive digital twins drive climate science research.

Before sitting down for a fireside chat with the founders of the three startups, Huang introduced some "special guests" to the audience—four of the world's leading climate modeling scientists, who he called the "unsung heroes" of saving the planet. "These scientists have dedicated their careers to advancing climate science," said Huang. "With the vision of EVE, they are the architects of the new era of climate science."

Geoffrey Hinton, British-Canadian psychologist, computer scientist, and 2018 Turing Award winner in deep learning, has departed the Google Brain team after a decade-long tenure. His research on AI and neural networks dating back to the 1980s has helped shape the current landscape of deep learning, neural processing, and artificial intelligence algorithms with direct and indirect contributions over the years. 2012's AlexNet, designed and developed in collaboration with his students Alex Krizhevsky and Ilya Sutskever, formed the modern backbone of computer vision and AI image recognition used today in Generative AI. Hinton joined Google when the company won the bid for the tiny startup he and his two students formed in the months following the reveal of AlexNet. Ilya Sutskever left their cohort at Google in 2015 to become co-founder and Chief Scientist of OpenAI; creators of ChatGPT and one of Google's most prominent competitors.

In an interview with the New York Times Hinton says that he quit his position at Google so that he may speak freely about the risks of AI, and that a part of him regrets his life's work in the field. He said that during his time there Google has acted as a "proper steward" of AI development, and was careful about releasing anything that might be harmful. His viewpoint on the industry shifted within the last year as Microsoft's Bing Chat took shots at Google's core business, the web browser, leading to Google being more reactionary than deliberate in response with Bard. The concern arises that as these companies battle it out for AI supremacy they won't take proper precautions against bad-faith actors using the technologies to flood the internet with false photos, text, and even videos. That the average person would no longer be able to tell what was real, and what was manufactured by AI prompt.

Microsoft, Tencent and Baidu are adopting NVIDIA CV-CUDA for computer vision AI. NVIDIA CEO Jensen Huang highlighted work in content understanding, visual search and deep learning Tuesday as he announced the beta release for NVIDIA's CV-CUDA—an open-source, GPU-accelerated library for computer vision at cloud scale. "Eighty percent of internet traffic is video, user-generated video content is driving significant growth and consuming massive amounts of power," said Huang in his keynote at NVIDIA's GTC technology conference. "We should accelerate all video processing and reclaim the power."

CV-CUDA promises to help companies across the world build and scale end-to-end, AI-based computer vision and image processing pipelines on GPUs. The majority of internet traffic is video and image data, driving incredible scale in applications such as content creation, visual search and recommendation, and mapping. These applications use a specialized, recurring set of computer vision and image-processing algorithms to process image and video data before and after they're processed by neural networks.

NVIDIA today announced that company founder and CEO Jensen Huang will deliver the opening keynote at GTC 2023, covering the latest advancements in generative AI, the metaverse, large language models, robotics, cloud computing and more. More than 250,000 people are expected to register for the four-day event, which will include 650+ sessions from researchers, developers and industry leaders in virtually every computing domain. GTC will also feature a fireside chat with Huang and OpenAI co-founder Ilya Sutskever, plus talks by DeepMind's Demis Hassabis, Stability AI's Emad Mostaque and many others.

"This is the most extraordinary moment we have witnessed in the history of AI," Huang said. "New AI technologies and rapidly spreading adoption are transforming science and industry, and opening new frontiers for thousands of new companies. This will be our most important GTC yet."

Intel today announced the new Intel Xeon W-3400 and Intel Xeon W-2400 desktop workstation processors (code-named Sapphire Rapids), led by the Intel Xeon w9-3495X, Intel's most powerful desktop workstation processor ever designed. Built for professional creators, these new Xeon processors provide massive performance for media and entertainment, engineering and data science professionals. With a breakthrough new compute architecture, faster cores and new embedded multi-die interconnect bridge (EMIB) packaging, the Xeon W-3400 and Xeon W-2400 series of processors enable unprecedented scalability for increased performance.

"For more than 20 years, Intel has been committed to delivering the highest quality workstation platforms - combining high-performance compute and rock-solid stability - for professional PC users across the globe. Our new Intel Xeon desktop workstation platform is uniquely designed to unleash the innovation and creativity of professional creators, artists, engineers, designers, data scientists and power users - built to tackle both today's most demanding workloads as well as the professional workloads of the future." -Roger Chandler, Intel vice president and general manager, Creator and Workstation Solutions, Client Computing Group

Dell Technologies expands the industry's top selling server portfolio, with an additional 13 next-generation Dell PowerEdge servers, designed to accelerate performance and reliability for powerful computing across core data centers, large-scale public clouds and edge locations. Next-generation rack, tower and multi-node PowerEdge servers, with 4th Gen Intel Xeon Scalable processors, include Dell software and engineering advancements, such as a new Smart Flow design, to improve energy and cost efficiency. Expanded Dell APEX capabilities will help organizations take an as-a-Service approach, allowing for more effective IT operations that make the most of compute resources while minimizing risk.

"Customers come to Dell for easily managed yet sophisticated and efficient servers with advanced capabilities to power their business-critical workloads," said Jeff Boudreau, president and general manager, Infrastructure Solutions Group, Dell Technologies. "Our next-generation Dell PowerEdge servers offer unmatched innovation that raises the bar in power efficiency, performance and reliability while simplifying how customers can implement a Zero Trust approach for greater security throughout their IT environments."

Supermicro, Inc., a Total IT Solution Provider for Cloud, AI/ML, Storage, and 5G/Edge, at the 2022 Super Computing Conference is unveiling the most extensive portfolio of servers and storage systems in the industry based on the upcoming 4th Gen Intel Xeon Scalable processor, formerly codenamed Sapphire Rapids. Supermicro continues to use its Building Block Solutions approach to deliver state-of-the-art and secure systems for the most demanding AI, Cloud, and 5G Edge requirements. The systems support high-performance CPUs and DDR5 memory with up to 2X the performance and capacities up to 512 GB DIMMs and PCIe 5.0, which doubles I/O bandwidth. Intel Xeon CPU Max Series CPUs (formerly codenamed Sapphire Rapids HBM High Bandwidth Memory (HBM)) is also available on a range of Supermicro X13 systems. In addition, support for high ambient temperature environments at up to 40° C (104° F), with servers designed for air and liquid cooling for optimal efficiency, are rack-scale optimized with open industry standard designs and improved security and manageability.

"Supermicro is once again at the forefront of delivering the broadest portfolio of systems based on the latest technology from Intel," stated Charles Liang, president and CEO of Supermicro. "Our Total IT Solutions strategy enables us to deliver a complete solution to our customers, which includes hardware, software, rack-scale testing, and liquid cooling. Our innovative platform design and architecture bring the best from the 4th Gen Intel Xeon Scalable processors, delivering maximum performance, configurability, and power savings to tackle the growing demand for performance and energy efficiency. The systems are rack-scale optimized with Supermicro's significant growth of rack-scale manufacturing of up to 3X rack capacity."

As part of Intel's Responsible AI work, the company has developed FakeCatcher, a technology that can detect fake videos with a 96% accuracy rate. Intel's deepfake detection platform is the world's first real-time deepfake detector that returns results in milliseconds. "Deepfake videos are everywhere now. You have probably already seen them; videos of celebrities doing or saying things they never actually did," said Ilke Demir, senior staff research scientist in Intel Labs.

Intel's real-time deepfake detection uses Intel hardware and software and runs on a server and interfaces through a web-based platform. On the software side, an orchestra of specialist tools form the optimized FakeCatcher architecture. Teams used OpenVino to run AI models for face and landmark detection algorithms. Computer vision blocks were optimized with Intel Integrated Performance Primitives (a multi-threaded software library) and OpenCV (a toolkit for processing real-time images and videos), while inference blocks were optimized with Intel Deep Learning Boost and with Intel Advanced Vector Extensions 512, and media blocks were optimized with Intel Advanced Vector Extensions 2. Teams also leaned on the Open Visual Cloud project to provide an integrated software stack for the Intel Xeon Scalable processor family. On the hardware side, the real-time detection platform can run up to 72 different detection streams simultaneously on 3rd Gen Intel Xeon Scalable processors.

DFI, the global leading provider of high-performance computing technology across multiple embedded industries, unveils a server-grade ATX motherboard, designed for Intel Ice Lake platform, powered by the 3rd Generation Intel Xeon Scalable processors, and equipped with ultra-high speed computing that can support up to 205 W. ICX610-C621A also comes with built-in Intel Speed Select Technology (Intel SST), which provides an excellent load balancing between CPUs and multiple accelerator cards to effectively distribute CPU resource, stabilize computation loads and maximize computing power. As a result, it improves the performance by 1.46 times compared to previous generation.

Featuring powerful performance, the offers three PCIe x 16, two PCIe x8 slots and one M.2 Key and enables ultra-performance computing, AI workload and deep learning, specifically for high-end inspection equipment, such as AOI, CT, and MRI application. The ICX610 also supports ECC RDIMM up to 512 GB 3200 MHz enhances high end performance for advanced inspection equipment and improves efficiency.

Intel has announced the availability of its 12th Gen Intel Core SoC processors for IoT Edge. Representing a new lineup of purpose-built edge products optimized for Internet of Things (IoT) applications, this first-of-its-kind socketed system-on-chip (SoC) delivers high performance integrated graphics and media processing for visual compute workloads, a compact footprint to enable smaller innovative form factor designs, and a wide operating thermal design power (TDP) that enables fanless designs and helps customers achieve product sustainability goals.

"As the digitization of business processes continues to accelerate—fueled by workforce demand, supply chain constraints and changing consumer behavior—the amount of data created at the edge and the need for it to be processed and analyzed locally continues to explode. Intel understands the challenges that businesses face—across a wide range of vertical industries—and is committed to help them continue to deliver innovative use cases," said Jeni Panhorst, Intel vice president and general manager of the Network and Edge Compute Division.

Intel's upcoming Sapphire Rapids processors will not only be present in the server sector but will also span the high-end desktop (HEDT) platform. Today, according to the findings of a Twitter user, @InstLatX64, we have an appearance of Intel's upcoming Sapphire Rapids HEDT SKU in Kernel.org boot logs. Named Intel Xeon W9-3495, this model features 56 cores and 112 threads. While there is no specific information about base and boost frequencies, we know that the SKU supports AVX-512 and AMX instructions. This is a welcome addition, as we have seen Intel disable AVX-512 on consumer chips altogether.

With a high core count and additional instructions for Deep Learning, this CPU will power workstations sometimes in the future. With the late arrival of Sapphire Rapids for servers, a HEDT variant should follow.

Today at the Intel Vision conference, Habana Labs, an Intel company, announced its second-generation deep learning processors, the Habana Gaudi 2 Training and Habana Greco Inference processors. The processors are purpose-built for AI deep learning applications, implemented in 7nm technology and build upon Habana's high-efficiency architecture to provide customers with higher-performance model training and inferencing for computer vision and natural language applications in the data center. At Intel Vision, Habana Labs revealed Gaudi2's training throughput performance for the ResNet-50 computer vision model and the BERT natural language processing model delivers twice the training throughput over the Nvidia A100-80GB GPU.

"The launch of Habana's new deep learning processors is a prime example of Intel executing on its AI strategy to give customers a wide array of solution choices - from cloud to edge - addressing the growing number and complex nature of AI workloads. Gaudi2 can help Intel customers train increasingly large and complex deep learning workloads with speed and efficiency, and we're anticipating the inference efficiencies that Greco will bring."—Sandra Rivera, Intel executive vice president and general manager of the Datacenter and AI Group

Lambda, the Deep Learning Company, today in collaboration with Razer, released the new Lambda Tensorbook, the world's most powerful laptop designed for deep learning, available with Linux and Lambda's deep learning software. The sleek laptop, coupled with the Lambda GPU Cloud, gives engineers all the software tools and compute performance they need to create, train, and test deep learning models locally. Since its launch in 2012, Lambda has quickly become the de-facto deep learning infrastructure provider for the world's leading research and engineering teams. Thousands of businesses and organizations use Lambda including: all of the top five tech companies, 97 percent of the top research universities in the U.S. including MIT and Caltech, and the Department of Defense. These teams use Lambda's GPU clusters, servers, workstations, and cloud instances to train neural networks for cancer detection, autonomous aircraft, drug discovery, self-driving cars, and much more.

"Most ML engineers don't have a dedicated GPU laptop, which forces them to use shared resources on a remote machine, slowing down their development cycle." said Stephen Balaban, co-founder and CEO of Lambda. "When you're stuck SSHing into a remote server, you don't have any of your local data or code and even have a hard time demoing your model to colleagues. The Razer x Lambda Tensorbook solves this. It's pre-installed with PyTorch and TensorFlow and lets you quickly train and demo your models: all from a local GUI interface. No more SSH!"