Microsoft has taken another significant step in its AI integration strategy by introducing "Terminal Chat," an AI assistant now available in Windows Terminal. This latest feature brings conversational AI capabilities directly to the command-line interface, marking a notable advancement in making terminal operations more accessible to users of all skill levels. The new feature, currently available in Windows Terminal (Canary), leverages various AI services, including ChatGPT, GitHub Copilot, and Azure OpenAI, to provide interactive assistance for command-line operations. What sets Terminal Chat apart is its context-aware functionality, which automatically recognizes the specific shell environment being used—whether it's PowerShell, Command Prompt, WSL Ubuntu, or Azure Cloud Shell—and tailors its responses accordingly.

Users can interact with Terminal Chat through a dedicated interface within Windows Terminal, where they can ask questions, troubleshoot errors, and request guidance on specific commands. The system provides shell-specific suggestions, automatically adjusting its recommendations based on whether a user is working in Windows PowerShell, Linux, or other environments. For example, when asked about creating a directory, Terminal Chat will suggest "New-Item -ItemType Directory" for PowerShell users while providing "mkdir" as the appropriate command for Linux environments. This intelligent adaptation helps bridge the knowledge gap between different command-line interfaces. Below are some examples courtesy of Windows Latest and their testing:

Microsoft's Direct3D and HLSL teams have unveiled plans to integrate SPIR-V support into DirectX 12 with the upcoming release of Shader Model 7. This significant transition marks a new era in GPU programmability, as it aims to unify the intermediate representation for graphical-shader stages and compute kernels. SPIR-V, an open standard intermediate representation for graphics and compute shaders, will replace the proprietary DirectX Intermediate Language (DXIL) as the shader interchange format for DirectX 12. The adoption of SPIR-V is expected to ease development processes across multiple GPU runtime environments. By embracing this open standard, Microsoft aims to enhance HLSL's position as the premier language for compiling graphics and compute shaders across various devices and APIs. This transition is part of a multi-year development process, during which Microsoft will work closely with The Khronos Group and the LLVM Project. The company has joined Khronos' SPIR and Vulkan working groups to ensure smooth collaboration and rapid feature adoption.

While the transition will take several years, Microsoft is providing early notice to allow developers and partners to plan accordingly. The company will offer translation tools between SPIR-V and DXIL to facilitate a gradual transition for both application and driver developers. For those not familiar with graphics development, graphics APIs ship with virtual instruction set architectures (ISA) that abstracts standard hardware features at a higher level. As GPUs don't follow the same ISA as CPUs (x86, Arm, RISC-V), this virtual ISA is needed to define some generics in the GPU architecture and allow various APIs like DirectX and Vulkan to run. Instead of focusing support on several formats like DXIL, Microsoft is embracing the open SPIR-V standard, which will become de facto for API developers in the future, allowing focus on more features instead of constantly replicating each other's functions. While DXIL is used mainly for gaming environments, SPIR-V has adoption in high-performance computing as well, with OpenCL and SYCL. Gaming presence is also there with Vulkan API, and we expect to see SPIR-V join DirectX 12 games.

SambaNova Systems, provider of the fastest and most efficient chips and AI models, announced SambaNova Cloud, the world's fastest AI inference service enabled by the speed of its SN40L AI chip. Developers can log on for free via an API today — no waiting list — and create their own generative AI applications using both the largest and most capable model, Llama 3.1 405B, and the lightning-fast Llama 3.1 70B. SambaNova Cloud runs Llama 3.1 70B at 461 tokens per second (t/s) and 405B at 132 t/s at full precision.

"SambaNova Cloud is the fastest API service for developers. We deliver world record speed and in full 16-bit precision - all enabled by the world's fastest AI chip," said Rodrigo Liang, CEO of SambaNova Systems. "SambaNova Cloud is bringing the most accurate open source models to the vast developer community at speeds they have never experienced before."

The market for artificial intelligence (AI) platforms software grew at a rapid pace in 2023 and is projected to maintain its remarkable momentum, driven by the increasing adoption of AI across many industries. A new International Data Corporation (IDC) forecast shows that worldwide revenue for AI platforms software will grow to $153.0 billion in 2028 with a compound annual growth rate (CAGR) of 40.6% over the 2023-2028 forecast period.

"The AI platforms market shows no signs of slowing down. Rapid innovations in generative AI is changing how companies think about their products, how they develop and deploy AI applications, and how they leverage technology themselves for reinventing their business models and competitive positioning," said Ritu Jyoti, group vice president and general manager of IDC's Artificial Intelligence, Automation, Data and Analytics research. "IDC expects this upward trajectory will continue to accelerate with the emergence of unified platforms for predictive and generative AI that supports interoperating APIs, ecosystem extensibility, and responsible AI adoption at scale."

While we are all used to having a system with a CPU, GPU, and, recently, NPU—X-Silicon Inc. (XSi), a startup founded by former Silicon Valley veterans—has unveiled an interesting RISC-V processor that can simultaneously handle CPU, GPU, and NPU workloads in a chip. This innovative chip architecture, which will be open-source, aims to provide a flexible and efficient solution for a wide range of applications, including artificial intelligence, virtual reality, automotive systems, and IoT devices. The new microprocessor combines a RISC-V CPU core with vector capabilities and GPU acceleration into a single chip, creating a versatile all-in-one processor. By integrating the functionality of a CPU and GPU into a single core, X-Silicon's design offers several advantages over traditional architectures. The chip utilizes the open-source RISC-V instruction set architecture (ISA) for both CPU and GPU operations, running a single instruction stream. This approach promises lower memory footprint execution and improved efficiency, as there is no need to copy data between separate CPU and GPU memory spaces.

Called the C-GPU architecture, X-Silicon uses RISC-V Vector Core, which has 16 32-bit FPUs and a Scaler ALU for processing regular integers as well as floating point instructions. A unified instruction decoder feeds the cores, which are connected to a thread scheduler, texture unit, rasterizer, clipping engine, neural engine, and pixel processors. All is fed into a frame buffer, which feeds the video engine for video output. The setup of the cores allows the users to program each core individually for HPC, AI, video, or graphics workloads. Without software, there is no usable chip, which prompts X-Silicon to work on OpenGL ES, Vulkan, Mesa, and OpenCL APIs. Additionally, the company plans to release a hardware abstraction layer (HAL) for direct chip programming. According to Jon Peddie Research (JPR), the industry has been seeking an open-standard GPU that is flexible and scalable enough to support various markets. X-Silicon's CPU/GPU hybrid chip aims to address this need by providing manufacturers with a single, open-chip design that can handle any desired workload. The XSi gave no timeline, but it has plans to distribute the IP to OEMs and hyperscalers, so the first silicon is still away.

AMD at GDC 2024 announced the FidelityFX Super Resolution 3.1 (FSR 3.1). While the original FSR 3.0 feature-set largely carries forward the super resolution upscaler from FSR 2.2, adding frame generation on top; the new FSR 3.1 adds several image quality improvements to the upscaler itself, improving image quality at every performance preset. Specifically, it improves the temporal stability of the output at rest and in movement, to reduce flickering and shimmering, or "fizziness" around objects in motion. The new upscaler also reduces ghosting, and better preserves detail.

Next up, is a rather important change in the way the frame generation technology works. AMD has decoupled FSR 3.1 frame generation from the upscaling tech, which allows frame generation to work with other upscaling solutions, such as DLSS or XeSS. The possibilities of such a decoupling are endless—have an RTX 30-series "Ampere" GPU that lacks DLSS 3 frame generation support? No worries, use DLSS 2 for the upscaling, and FSR 3.1 for the frame generation. AMD is also clumping its FidelityFX family of technologies into a new FidelityFX API that makes it easier for developers to debug, and paves the way for forward-compatibility with future versions of FSR. Lastly, FSR 3.1 supports Vulkan API, and the Microsoft Xbox GDK. AMD plans to release FSR 3.1 to developers through its GPUOpen platform in Q2-2024, and its first implementations on games are expected later this year. In the meantime, AMD implemented FSR 3.1 on "Ratchet & Clank: Rift Apart," to showcase the new upscaler.

In the world where the largest companies are riding the AI train, the biggest of them all—Apple—seemed to stay quiet for a while. Even with many companies announcing their systems/models, Apple has stayed relatively silent about the use of LLMs in their products. However, according to Bloomberg, Apple is not pushing out an AI model of its own; rather, it will license Google's leading Gemini models for its iPhone smartphones. Gemini is Google's leading AI model with three variants: Gemini Nano 1/2, Gemini Pro, and Gemini Ultra. The Gemini Nano 1 and Nano 2 are designed to run locally on hardware like smartphones. At the same time, Gemini Pro and Ultra are inferenced from Google's servers onto a local device using API and the internet.

Apple could use a local Gemini Nano for basic tasks while also utilizing Geminin Pro or Ultra for more complex tasks, where a router sends user input to the available model. That way, users could use AI capabilities both online and offline. Since Apple is readying a suite of changes for iOS version 18, backed by Neural Engine inside A-series Bionic chips, the LLM game of Apple's iPhones might get a significant upgrade with the Google partnership. While we still don't know the size of the deal, it surely is a massive deal for Google to tap into millions of devices Apple ships every year and for Apple to give its users a more optimized experience.

Microsoft's DirectX department is scheduled to show off several innovations at this month's Game Developers Conference (GDC), although a late February preview has already spilled their DirectSR Super Resolution API's beans. Today, retail support for Shader Model 6.8 and Work Graphs has been introduced with an updated version of the company's Agility Software Development Kit. Program manager, Joshua Tucker, stated that these technologies will be showcased on-stage at GDC 2024—Shader Model 6.8 arrives with a "host of new features for shader developers, including Start Vertex/Instance Location, Wave Size Range, and Expanded Comparison Sampling." A linked supplementary article—D3D12 Work Graphs—provides an in-depth look into the cutting-edge API's underpinnings, best consumed if you have an hour or two to spare.

Tucker summarized the Work Graphs API: "(it) utilizes the full potential of your GPU. It's not just an upgrade to the existing models, but a whole new paradigm that enables more efficient, flexible, and creative game development. With Work Graphs, you can generate and schedule GPU work on the fly, without relying on the host. This means you can achieve higher performance, lower latency, and greater scalability for your games with tasks such as culling, binning, chaining of compute work, and much more." AMD and NVIDIA are offering driver support on day one. Team Red has discussed the launch of "Microsoft DirectX 12 Work Graphs 1.0 API" in a GPUOpen blog—they confirm that "a deep dive" into the API will happen during their Advanced Graphics Summit presentation. NVIDIA's Wessam Bahnassi has also discussed the significance of Work Graphs—check out his "Advancing GPU-driven rendering" article. Graham Wihlidal—of Epic Games—is excited about the latest development: "we have been advocating for something like this for a number of years, and it is very exciting to finally see the release of Work Graphs."

2024 will be the year generative AI gets personal, the CEOs of NVIDIA and HP said today in a fireside chat, unveiling new laptops that can build, test and run large language models. "This is a renaissance of the personal computer," said NVIDIA founder and CEO Jensen Huang at HP Amplify, a gathering in Las Vegas of about 1,500 resellers and distributors. "The work of creators, designers and data scientists is going to be revolutionized by these new workstations."

Greater Speed and Security
"AI is the biggest thing to come to the PC in decades," said HP's Enrique Lores, in the runup to the announcement of what his company billed as "the industry's largest portfolio of AI PCs and workstations." Compared to running their AI work in the cloud, the new systems will provide increased speed and security while reducing costs and energy, Lores said in a keynote at the event. New HP ZBooks provide a portfolio of mobile AI workstations powered by a full range of NVIDIA RTX Ada Generation GPUs. Entry-level systems with the NVIDIA RTX 500 Ada Generation Laptop GPU let users run generative AI apps and tools wherever they go. High-end models pack the RTX 5000 to deliver up to 682 TOPS, so they can create and run LLMs locally, using retrieval-augmented generation (RAG) to connect to their content for results that are both personalized and private.

NVIDIA's Compute Unified Device Architecture (CUDA) has long been the de facto standard programming interface for developing GPU-accelerated software. Over the years, NVIDIA has built an entire ecosystem around CUDA, cementing its position as the leading GPU computing and AI manufacturer. However, rivals AMD and Intel have been trying to make inroads with their own open API offerings—ROCm from AMD and oneAPI from Intel. The idea was that developers could more easily run existing CUDA code on non-NVIDIA GPUs by providing open access through translation layers. Developers had created projects like ZLUDA to translate CUDA to ROCm, and Intel's CUDA to SYCL aimed to do the same for oneAPI. However, with the release of CUDA 11.5, NVIDIA appears to have cracked down on these translation efforts by modifying its terms of use, according to developer Longhorn on X.

"You may not reverse engineer, decompile or disassemble any portion of the output generated using Software elements for the purpose of translating such output artifacts to target a non-NVIDIA platform," says the CUDA 11.5 terms of service document. The changes don't seem to be technical in nature but rather licensing restrictions. The impact remains to be seen, depending on how much code still requires translation versus running natively on each vendor's API. While CUDA gave NVIDIA a unique selling point, its supremacy has diminished as more libraries work across hardware. Still, the move could slow the adoption of AMD and Intel offerings by making it harder for developers to port existing CUDA applications. As GPU-accelerated computing grows in fields like AI, the battle for developer mindshare between NVIDIA, AMD, and Intel is heating up.

Microsoft has just announced that their new DirectSR Super Resolution API for DirectX will provide a unified interface for developers to implement super resolution in their games. This means that game studios no longer have to choose between DLSS, FSR, XeSS, or spend additional resources to implement, bug-test and support multiple upscalers. For gamers this is huge news, too, because they will be able to run upscaling in all DirectSR games—no matter the hardware they own. While AMD FSR and Intel XeSS run on all GPUs from all vendors, NVIDIA DLSS is exclusive to Team Green's hardware. With their post, Microsoft also confirms that DirectSR will not replace FSR/DLSS/XeSS with a new upscaler by Microsoft, rather that it builds on existing technologies that are already available, unifying access to them.

While we have to wait until March 21 for more details to be revealed at GDC 2024, Microsoft's Joshua Tucker stated in a blog post: "We're thrilled to announce DirectSR, our new API designed in partnership with GPU hardware vendors to enable seamless integration of Super Resolution (SR) into the next generation of games. Super Resolution is a cutting-edge technique that increases the resolution and visual quality in games. DirectSR is the missing link developers have been waiting for when approaching SR integration, providing a smoother, more efficient experience that scales across hardware. This API enables multi-vendor SR through a common set of inputs and outputs, allowing a single code path to activate a variety of solutions including NVIDIA DLSS Super Resolution, AMD FidelityFX Super Resolution, and Intel XeSS. DirectSR will be available soon in the Agility SDK as a public preview, which will enable developers to test it out and provide feedback. Don't miss our DirectX State of the Union at GDC to catch a sneak peek at how DirectSR can be used with your games!"

ServiceNow, Hugging Face, and NVIDIA today announced the release of StarCoder2, a family of open-access large language models for code generation that sets new standards for performance, transparency, and cost-effectiveness. StarCoder2 was developed in partnership with the BigCode Community, managed by ServiceNow, the leading digital workflow company making the world work better for everyone, and Hugging Face, the most-used open-source platform, where the machine learning community collaborates on models, datasets, and applications. Trained on 619 programming languages, StarCoder2 can be further trained and embedded in enterprise applications to perform specialized tasks such as application source code generation, workflow generation, text summarization, and more. Developers can use its code completion, advanced code summarization, code snippets retrieval, and other capabilities to accelerate innovation and improve productivity.

StarCoder2 offers three model sizes: a 3-billion-parameter model trained by ServiceNow; a 7-billion-parameter model trained by Hugging Face; and a 15-billion-parameter model built by NVIDIA with NVIDIA NeMo and trained on NVIDIA accelerated infrastructure. The smaller variants provide powerful performance while saving on compute costs, as fewer parameters require less computing during inference. In fact, the new 3-billion-parameter model matches the performance of the original StarCoder 15-billion-parameter model. "StarCoder2 stands as a testament to the combined power of open scientific collaboration and responsible AI practices with an ethical data supply chain," emphasized Harm de Vries, lead of ServiceNow's StarCoder2 development team and co-lead of BigCode. "The state-of-the-art open-access model improves on prior generative AI performance to increase developer productivity and provides developers equal access to the benefits of code generation AI, which in turn enables organizations of any size to more easily meet their full business potential."

According to a Game Developers Conference (GDC) 2024 schedule page, Microsoft is planning to present next-gen technologies with their upcoming "DirectX State of the Union Ft. Work Graphs and Introducing DirectSR" presentation. Shawn Hargreaves, Direct3D's Development Manager and Austin Kinross (PIX Developer Lead, Microsoft) are scheduled to discuss matters with representatives from NVIDIA and AMD. Wessam Bahnassi, a "20-year veteran in 3D engine design and optimization," is Team Green's Principal Engineer of Developer Technology. Rob Martin, a Fellow Software Engineer, will be representing all things Team Red—where he leads development on implementations for GPU Work Graphs. According to GDC, the intended audience will be: "graphics developers or technical directors from game studios or engine companies."

Earlier this month, an "Automatic super resolution" feature was discovered in Windows 11 Insider Preview build (24H2)—the captioned part stated: "use AI to make supported games play more smoothly with enhanced details," although further interface options granted usage in desktop applications as well. Initial analysis and user impressions indicated that Microsoft engineers had created a proprietary model, separate from familiar technologies: NVIDIA DLSS, AMD FSR and Intel XeSS. It is interesting to note that Team Blue is not participating in the upcoming March 21 "DirectX State of the Union" panel discussion (a sponsored session). GDC's event description states (in full): "The DirectX team will showcase the latest updates, demos, and best practices for game development with key partners from AMD and NVIDIA. Work graphs are the newest way to take full advantage of GPU hardware and parallelize workloads. Microsoft will provide a preview into DirectSR, making it easier than ever for game devs to scale super resolution support across Windows devices. Finally, dive into the latest tooling updates for PIX."

AMD has quietly funded an effort over the past two years to enable binary compatibility for NVIDIA CUDA applications on their ROCm stack. This allows CUDA software to run on AMD Radeon GPUs without adapting the source code. The project responsible is ZLUDA, which was initially developed to provide CUDA support on Intel graphics. The developer behind ZLUDA, Andrzej Janik, was contracted by AMD in 2022 to adapt his project for use on Radeon GPUs with HIP/ROCm. He spent two years bringing functional CUDA support to AMD's platform, allowing many real-world CUDA workloads to run without modification. AMD decided not to productize this effort for unknown reasons but did open-source it once funding ended per their agreement. Over at Phoronix, there were several benchmarks testing AMD's ZLUDA implementation over a wide variety of benchmarks.

Benchmarks found that proprietary CUDA renderers and software worked on Radeon GPUs out-of-the-box with the drop-in ZLUDA library replacements. CUDA-optimized Blender 4.0 rendering now runs faster on AMD Radeon GPUs than the native ROCm/HIP port, reducing render times by around 10-20%, depending on the scene. The implementation is surprisingly robust, considering it was a single-developer project. However, there are some limitations—OptiX and PTX assembly codes still need to be fully supported. Overall, though, testing showed very promising results. Over the generic OpenCL runtimes in Geekbench, CUDA-optimized binaries produce up to 75% better results. With the ZLUDA libraries handling API translation, unmodified CUDA binaries can now run directly on top of ROCm and Radeon GPUs. Strangely, the ZLUDA port targets AMD ROCm 5.7, not the newest 6.x versions. Only time will tell if AMD continues investing in this approach to simplify porting of CUDA software. However, the open-sourced project now enables anyone to contribute and help improve compatibility. For a complete review, check out Phoronix tests.

An Open Image Denoise 2.2 release candidate was released earlier today—as discovered by Phoronix's founder and principal writer; Michael Larabel. Intel's dedicated website has not been updated with any new documentation or changelogs (at the time of writing), but a GitHub release page shows all of the crucial information. Team Blue's open-source oneAPI has been kept up-to-date with the latest technologies—not only limited to Intel's stable of Xe-LP, Xe-HPG and Xe-HPC components—the Phonorix article highlights updated support on competing platforms. The v2.2 preview adds support for Meteor Lake's integrated Arc graphics solution, and additional "denoising quality enhancements and other improvements."

Non-Intel platform improvements include updates for Apple's M-series chipsets, AArch64 processors, and NVIDIA CUDA. OIDn 2.2-rc: "adds Metal device support for Apple Silicon GPUs on recent versions of macOS. OIDn has already been supporting ARM64/AArch64 for Apple Silicon CPUs while now Open Image Denoise has extended that AArch64 support to work on Windows and Linux too. There is better performance in general for Open Image Denoise on CPUs with this forthcoming release." The changelog also highlights a general improvement performance across processors, and a fix that resolves a crash incident: "when releasing a buffer after releasing the device."

Apple today announced changes to iOS, Safari, and the App Store impacting developers' apps in the European Union (EU) to comply with the Digital Markets Act (DMA). The changes include more than 600 new APIs, expanded app analytics, functionality for alternative browser engines, and options for processing app payments and distributing iOS apps. Across every change, Apple is introducing new safeguards that reduce—but don't eliminate—new risks the DMA poses to EU users. With these steps, Apple will continue to deliver the best, most secure experience possible for EU users.

The new options for processing payments and downloading apps on iOS open new avenues for malware, fraud and scams, illicit and harmful content, and other privacy and security threats. That's why Apple is introducing protections—including Notarization for iOS apps, an authorization for marketplace developers, and disclosures on alternative payments—to reduce risks and deliver the best, most secure experience possible for users in the EU. Even with these safeguards in place, many risks remain.

Today, The Khronos Group, an open consortium of industry-leading companies creating advanced interoperability standards, announced the latest roadmap milestone for Vulkan, the cross-platform 3D graphics and compute API. The Vulkan roadmap targets the "immersive graphics" market, made up of mid- to high-end smartphones, tablets, laptops, consoles, and desktop devices. The Vulkan Roadmap 2024 milestone captures a set of capabilities that are expected to be supported in new products for that market, beginning in 2024. The roadmap specification provides a significant increase in functionality for the targeted devices and sets the evolutionary direction of the API, including both new hardware capabilities and improvements to the programming model for Vulkan developers.

Vulkan Roadmap 2024 is the second milestone release on the Vulkan Roadmap. Products that support it must be Vulkan 1.3 conformant and support the extensions and capabilities defined in both the 2022 and 2024 Roadmap specifications. Vulkan roadmap specifications use the Vulkan Profile mechanism to help developers build portable Vulkan applications; roadmap requirements are expressed in machine-readable JSON files, and tooling in the Vulkan SDK auto-generates code that makes it easy for developers to query for and enable profile support in their applications.

Baidu, Inc., a leading AI company with strong Internet foundation, today hosted its annual flagship technology conference Baidu World 2023 in Beijing, marking the conference's return to an offline format after four years. With the theme "Prompt the World," this year's Baidu World conference saw Baidu launch ERNIE 4.0, Baidu's next-generation and most powerful foundation model offering drastically enhanced core AI capabilities. Baidu also showcased some of its most popular applications, solutions, and products re-built around the company's state-of-the-art generative AI.

"ERNIE 4.0 has achieved a full upgrade with drastically improved performance in understanding, generation, reasoning, and memory," Robin Li, Co-founder, Chairman and CEO of Baidu, said at the event. "These four core capabilities form the foundation of AI-native applications and have now unleashed unlimited opportunities for new innovations."

Useful Sensors, an AI-focused start-up, today launched the world's first low-cost, off-the-shelf AI module to enable intuitive, natural language interaction with electronic devices, locally and privately, with no need for an account or internet connection. The new AI-In-A-Box module can answer queries and solve problems in a way similar to well-known AI tools based on a large language model (LLM). But thanks to compression and acceleration technologies developed by Useful Sensors, the module hosts its LLM file locally, enabling its low-cost microprocessor to understand and respond instantly to spoken natural language queries or commands without reference to a data center.

Disconnected from the internet, the AI-In-A-Box module definitively eliminates user concerns about privacy, snooping, or dependence on third-party cloud services that are prevalent with conventional LLM-based AI products and services marketed by large technology companies. The AI-In-A-Box module is available to buy now at CrowdSupply, priced at $299.

KIOXIA America, Inc. today announced that it has donated a command set specification to the Linux Foundation vendor-neutral Software-Enabled FlashTM Project. Built to deliver on the promise of software-defined flash, Software-Enabled Flash technology gives storage developers control over their data placement, latency outcomes, and workload isolation requirements. Through its open API and SDKs, hyperscale environments may optimize their own flash protocols, such as flexible direct placement (FDP) or zoned namespace (ZNS), while accelerating adoption of new flash technologies. This unique combination of open source software and purpose-built hardware can help data centers maximize the value of flash memory. KIOXIA has developed working samples of hardware modules for hyperscalers, storage developers and application developers.

"We are delighted to provide command set specifications to the Software-Enabled Flash Project," said Eric Ries, senior vice president and general manager of the Memory and Storage Strategy Division for KIOXIA America, Inc. "This is an important step that allows the ecosystem to bring products to market, and enables customers to extract the maximum value from flash memory."

Thanks to the latest report from Phoronix, we know that Intel is working on supporting the latest "Xe2" graphics architecture for their upcoming Lunar Lake processors. Today, the latest enablement comes in the Mesa Linux drivers. By employing a new technique that allows for importing prior-generation XML files within the Intel Mesa driver code, Intel engineers have managed to streamline the overall file size. This is significant not just for the efficiency it brings but also because it signifies the beginning of work on enabling Xe2 graphics support. It suggests a thoughtful approach to building upon existing architectures, making it easier to adapt and evolve the software support for each new generation of Intel graphics.

Even though we are at the early stage and Lunar Lake is far away, the progress on Xe2 doesn't stop at Mesa driver changes. There is already some work at the kernel level, and new merge requests for draft compiler changes and shader compiler patches have also been spotted. This proactive development strategy positions Intel well in offering robust open-source graphics support for Linux, and it sends a strong signal to the developer community about Intel's dedication to the platform. After the Linux kernel driver works, this Mesa driver will enable better OpenGL/Vulkan API compatibility, so Lunar Lake arrives with proper software support.

KIOXIA America, Inc. today announced the availability of the first hardware samples that support the Linux Foundation's vendor-neutral Software-Enabled Flash Community Project, which is making flash software-defined. The company is expecting to deliver customer samples in August 2023. Built for the demanding needs of hyperscale environments, Software-Enabled Flash technology helps hyperscale cloud providers and storage developers maximize the value of flash memory. The hardware from KIOXIA is the first step to putting this working technology in the hands of developers.

The first running units will be showcased in live demonstrations in the KIOXIA booth (#307) next week at Flash Memory Summit 2023 (FMS 2023). This new class of drive consists of purpose-built, media-centric flash hardware focused on hyperscale requirements that work with an open source API and libraries to provide the needed functionality. By unlocking the power of flash, this technology breaks free from legacy hard disk drive (HDD) protocols and creates a platform specific to flash media in a hyperscale environment.

Announced today, Ultra Ethernet Consortium (UEC) is bringing together leading companies for industry-wide cooperation to build a complete Ethernet-based communication stack architecture for high-performance networking. Artificial Intelligence (AI) and High-Performance Computing (HPC) workloads are rapidly evolving and require best-in-class functionality, performance, interoperability and total cost of ownership, without sacrificing developer and end-user friendliness. The Ultra Ethernet solution stack will capitalize on Ethernet's ubiquity and flexibility for handling a wide variety of workloads while being scalable and cost-effective.

Ultra Ethernet Consortium is founded by companies with long-standing history and experience in high-performance solutions. Each member is contributing significantly to the broader ecosystem of high-performance in an egalitarian manner. The founding members include AMD, Arista, Broadcom, Cisco, Eviden (an Atos Business), HPE, Intel, Meta and Microsoft, who collectively have decades of networking, AI, cloud and high-performance computing-at-scale deployments.

We are happy to share that our AMD FidelityFX Software Development Kit (SDK) is now available for download!

What is the AMD FidelityFX SDK?
The AMD FidelityFX SDK is our new and easy to integrate solution for developers looking to include AMD FidelityFX technologies into their games without any of the hassle of complicated porting procedures. In a nutshell, it is AMD FidelityFX graphics middleware.

NVIDIA today announced that it is integrating its NVIDIA AI Enterprise software into Microsoft's Azure Machine Learning to help enterprises accelerate their AI initiatives. The integration will create a secure, enterprise-ready platform that enables Azure customers worldwide to quickly build, deploy and manage customized applications using the more than 100 NVIDIA AI frameworks and tools that come fully supported in NVIDIA AI Enterprise, the software layer of NVIDIA's AI platform.

"With the coming wave of generative AI applications, enterprises are seeking secure accelerated tools and services that drive innovation," said Manuvir Das, vice president of enterprise computing at NVIDIA. "The combination of NVIDIA AI Enterprise software and Azure Machine Learning will help enterprises speed up their AI initiatives with a straight, efficient path from development to production."