To defend regular users from bad actors wielding quantum computing power like Majorana 1, Windows 11 Insider Preview now includes built-in support for post-quantum cryptography (PQC), giving developers and security teams early access to algorithms designed to withstand the capabilities of future quantum computers. Available in Canary Channel Build 27852 and above, this update integrates two new schemes, ML-KEM for key exchange and ML-DSA for digital signatures, directly into the Cryptography API: Next Generation (CNG) and certificate management functions. ML-KEM addresses the "harvest now, decrypt later" threat model, in which adversaries collect encrypted data today to decrypt it once quantum hardware has advanced. Microsoft offers three levels of ML-KEM security: a Level 1 option that produces 800-byte ciphertexts and a 32-byte shared secret; a Level 3 configuration with 1,184-byte ciphertexts and the same 32-byte secret; and a Level 5 tier that increases ciphertext size to 1,568 bytes while keeping the shared secret at 32 bytes. These parameter sets allow organizations to balance performance and protection according to their threat models and operational requirements.

IBM is working with Oracle to bring the power of watsonx, IBM's flagship portfolio of AI products, to Oracle Cloud Infrastructure (OCI). Leveraging OCI's native AI services, the latest milestone in IBM's technology partnership with Oracle is designed to fuel a new era of multi-agentic, AI-driven productivity and efficiency across the enterprise. Organizations today are deploying AI throughout their operations, looking to take advantage of the extraordinary advancements in generative AI models, tools, and agents. AI agents that can provide a single, easy-to-use interface to complete tasks are emerging as key tools to help simplify the deployment and use of AI across enterprise operations and functions. "AI delivers the most impactful value when it works seamlessly across an entire business," said Greg Pavlik, executive vice president, AI and Data Management Services, Oracle Cloud Infrastructure. "IBM and Oracle have been collaborating to drive customer success for decades, and our expanded partnership will provide customers new ways to help transform their businesses with AI."

Watsonx Orchestrate to support multi-agent workflows
To give customers a consistent way to build and manage agents across multi-agent, multi-system business processes, spanning both Oracle and non-Oracle applications and data sources, IBM is making its watsonx Orchestrate AI agent offerings available on OCI in July. This multi-agent approach using wastonx Orchestrate is designed to work with the expansive AI agent offerings embedded within the Oracle AI Agent Studio for Fusion Applications, as well as OCI Generative AI Agents, and OCI's other AI services. It extends the ecosystem around Oracle Fusion Applications to enable further functionality across third-party and custom applications and data sources. The first use cases being addressed are in human resources. The watsonx Orchestrate agents will perform AI inferencing on OCI, which many customers use to host their data, AI, and other applications. IBM agents run in watsonx Orchestrate on Red Hat OpenShift on OCI, including in public, sovereign, government, and Oracle Alloy regions, to enable customers to address specific regulatory and privacy requirements. The agents can also be hosted on-premises or in multicloud environments for true hybrid cloud capabilities.

Microsoft has confirmed that the Windows 11 version 24H2 update is now in its final rollout phase and will soon be delivered automatically to millions of Home and Pro users around the world. As of May 2, 2025, any unmanaged device running Windows 11 versions 21H2, 22H2, or 23H2—or even Windows 10—will see the 2024 Update download in the background. After the download completes, users can choose when to install the update or postpone it by going to Settings, then Windows Update. This release introduces a variety of useful improvements. File Explorer search has become more intuitive, the Clock app now includes focus sessions to help you stay on task, and Snap Layouts provide greater flexibility when organizing open windows. If you own a Copilot+ PC, you will continue to receive additional AI‑powered features in stages; these releases start within the Windows Insider community and may differ depending on your device's processor and region.

Although automatic delivery makes it easier to stay current, devices with limited storage may struggle if the update files consume too much space. To avoid disruptions, Windows Update offers a four‑week postponement option. Should you need more time, you can use command‑line tools or adjust local policies to stop or block the update permanently. Microsoft has published a detailed list of known issues and safeguard holds alongside the rollout information. For example, Azure Virtual Desktop users who experienced App Attach failures will see those problems fixed, and Remote Desktop freezes caused by the January 2025 preview update have been resolved. At the same time, devices running certain Dirac Audio drivers, sprotect.sys applications, or outdated Easy Anti‑Cheat or Intel Smart Sound Technology drivers will not receive the update until compatible versions become available. Some wallpaper customization and camera‑dependent apps may also encounter temporary glitches while patches are prepared. IT administrators looking for programmatic access to update health data can use the Windows Updates API in Microsoft Graph. For immediate assistance with update issues, open the Get Help app or visit the Microsoft Support website.

AI is rapidly reshaping what's possible on a PC—whether for real-time image generation or voice-controlled workflows. As AI capabilities grow, so does their complexity. Tapping into the power of AI can entail navigating a maze of system settings, software and hardware configurations. Enabling users to explore how on-device AI can simplify and enhance the PC experience, Project G-Assist—an AI assistant that helps tune, control and optimize GeForce RTX systems—is now available as an experimental feature in the NVIDIA app. Developers can try out AI-powered voice and text commands for tasks like monitoring performance, adjusting settings and interacting with supporting peripherals. Users can even summon other AIs powered by GeForce RTX AI PCs.

And it doesn't stop there. For those looking to expand Project G-Assist capabilities in creative ways, the AI supports custom plug-ins. With the new ChatGPT-based G-Assist Plug-In Builder, developers and enthusiasts can create and customize G-Assist's functionality, adding new commands, connecting external tools and building AI workflows tailored to specific needs. With the plug-in builder, users can generate properly formatted code with AI, then integrate the code into G-Assist—enabling quick, AI-assisted functionality that responds to text and voice commands.

Yesterday, OpenAI unveiled its new GPT-4.1 model family, which includes GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano. These models promise significantly improved coding, instruction following, and long-context understanding compared to earlier versions like GPT-4o. All three support up to one million tokens of context, so they can handle much larger documents, codebases, or even hour-long video transcripts. In coding tests, GPT-4.1 scored 54.6% on the SWE-bench Verified benchmark, a jump of 21.4 points over GPT-4o. That makes it one of the strongest models for real-world software engineering tasks. It's better at exploring code repositories, creating patches that actually compile and pass tests, and following diff formats without extra edits. Areas like instruction following got a boost, too. On Scale's MultiChallenge benchmark, GPT-4.1 scored 38.3%, up 10.5 points from GPT-4o. That means it can stick to multi-step prompts more reliably and format its responses the way you ask.

The models' long-context skills stand out on the Video-MME benchmark, where GPT-4.1 scored 72.0% in the "long, no subtitles" category, 6.7 points higher than GPT-4o. Thanks to its one-million-token window, GPT-4.1 can pull together information spread across huge inputs, whether it's scattered text in a document or key moments in a video. OpenAI says these gains come from close work with developers, tuning the models for tasks that matter while cutting costs and latency. GPT-4.1 mini cuts cost 83% and nearly half the response time compared to GPT-4o. GPT-4.1 nano is even faster and cheaper, making it ideal for classification or autocompletion. All three models are available now through OpenAI's API. They won't appear directly in ChatGPT initially, though many of their improvements have already made it into the latest GPT-4o chatbot. Developers using the GPT-4.5 Preview should plan to switch over by July 14, 2025, when that version will be retired. While o3-mini remains the most powerful thinking model, the non-thinking GPT-4.1 family is closing the gap to deliver faster response times.

AMD has launched a new open-source project called, GAIA (pronounced /ˈɡaɪ.ə/), an awesome application that leverages the power of Ryzen AI Neural Processing Unit (NPU) to run private and local large language models (LLMs). In this blog, we'll dive into the features and benefits of GAIA, while introducing how you can take advantage of GAIA's open-source project to adopt into your own applications.

Introduction to GAIA
GAIA is a generative AI application designed to run local, private LLMs on Windows PCs and is optimized for AMD Ryzen AI hardware (AMD Ryzen AI 300 Series Processors). This integration allows for faster, more efficient processing - i.e. lower power- while keeping your data local and secure. On Ryzen AI PCs, GAIA interacts with the NPU and iGPU to run models seamlessly by using the open-source Lemonade (LLM-Aid) SDK from ONNX TurnkeyML for LLM inference. GAIA supports a variety of local LLMs optimized to run on Ryzen AI PCs. Popular models like Llama and Phi derivatives can be tailored for different use cases, such as Q&A, summarization, and complex reasoning tasks.

We're stepping up our multiplatform gaming offering with exciting news dropping at this year's Game Developers Conference (GDC). We're bringing users more games, more ways to play your games across devices, and improved gameplay. You can read all about the updates for users from The Keyword. At GDC, we'll be diving into all of the latest games coming to Play, plus new developer tools that'll help improve gameplay across the Android ecosystem.

We're sharing a closer look at what's new from Android. We're making Vulkan the official graphics API on Android, enabling you to build immersive visuals, and we're enhancing the Android Dynamic Performance Framework (ADPF) to help you deliver longer, more stable gameplays. Check out our video, or keep reading below.

TerraMaster, in collaboration with its partner Imagery Business Systems, has launched API-in-a-Box, marking a significant milestone in the field of software and hardware development. This pre-configured open-source solution integrates artificial intelligence (AI) and low-code technology with the TerraMaster F4-424 Max TNAS hardware, aiming to accelerate the creation of full-stack applications. It offers a seamless experience from requirement description to production deployment. Below is an analysis of its detailed features, target audience, and unique advantages.

Product Features and Technical Highlights
API-in-a-Box integrates several innovative features, making it an ideal tool for rapid development and deployment.

Khronos introduced version 1.4 of its Vulkan graphics API last December—at the time, industry watchdogs believed that this iteration was prepared with NVIDIA "Blackwell" GPU conformance in mind. A mid-January leak indicated that the GeForce RTX 5090 SKU was already present on the Vulkan API's support list. Recent official additions—of GeForce RTX 5070 Ti and RTX 5070 GPUs to the cross-platform API's compatibility registry—suggest an imminent launch at retail; insiders reckon that the 5070 Ti will arrive on February 20.

Last week, HWiNFO's development team revealed that they were readying an incoming build (8.21) with support for Team Green's GeForce RTX 5070 Ti GPU. Their "upcoming changes" list did not include the lower-specced GeForce RTX 5070 (non-Ti)—online speculation posits that this model will launch later on in February. The GeForce RTX 5070's inclusion on the latest Vulkan API conformance list is an encouraging sign. VideoCardz spent its weekend searching for any entries alluding to GeForce RTX 5060 Ti or GeForce RTX 5060 (non-Ti) SKUs—they discovered zero evidence. The developers at Khronos are likely keeping these lower-end models under a "confidential" category.

Companies and organizations are increasingly using AI to protect their customers and thwart the efforts of fraudsters around the world. Voice security company Hiya found that 550 million scam calls were placed per week in 2023, with INTERPOL estimating that scammers stole $1 trillion from victims that same year. In the U.S., one of four noncontact-list calls were flagged as suspected spam, with fraudsters often luring people into Venmo-related or extended warranty scams.

Traditional methods of fraud detection include rules-based systems, statistical modeling and manual reviews. These methods have struggled to scale to the growing volume of fraud in the digital era without sacrificing speed and accuracy. For instance, rules-based systems often have high false-positive rates, statistical modeling can be time-consuming and resource-intensive, and manual reviews can't scale rapidly enough.

At yesterday's J.P. Morgan Healthcare Conference NVIDIA announced new partnerships to transform the $10 trillion healthcare and life sciences industry by accelerating drug discovery, enhancing genomic research and pioneering advanced healthcare services with agentic and generative AI. The convergence of AI, accelerated computing and biological data is turning healthcare into the largest technology industry. Healthcare leaders IQVIA, Illumina and Mayo Clinic, as well as Arc Institute, are using the latest NVIDIA technologies to develop solutions that will help advance human health.

These solutions include AI agents that can speed clinical trials by reducing administrative burden, AI models that learn from biology instruments to advance drug discovery and digital pathology, and physical AI robots for surgery, patient monitoring and operations. AI agents, AI instruments and AI robots will help address the $3 trillion of operations dedicated to supporting industry growth and create an AI factory opportunity in the hundreds of billions of dollars.

IQVIA, the world's leading provider of clinical research services, commercial insights and healthcare intelligence, is working with NVIDIA to build custom foundation models and agentic AI workflows that can accelerate research, clinical development and access to new treatments. AI applications trained on the organization's vast healthcare-specific information and guided by its deep domain expertise will help the industry boost the efficiency of clinical trials and optimize planning for the launch of therapies and medical devices—ultimately improving patient outcomes.

Operating in over 100 countries, IQVIA has built the largest global healthcare network and is uniquely connected to the ecosystem with the most comprehensive and granular set of information, analytics and technologies in the industry. Announced today at the J.P. Morgan Conference in San Francisco, IQVIA's collection of models, AI agents and reference workflows will be developed with the NVIDIA AI Foundry platform for building custom models, allowing IQVIA's thousands of pharmaceutical, biotech and medical device customers to benefit from NVIDIA's agentic AI capabilities and IQVIA's technologies, life sciences information and expertise.

Microsoft announced updates to the DirectX API that would pave the way for neural rendering. Neural rendering is a concept where portions of a frame in real-time 3D graphics are drawn using a generative AI model that works in tandem with classic raster 3D graphics pipeline, along with other advancements, such as real-time ray tracing. This is different from AI-based super resolution technologies. The generative AI here is involved in rendering the input frames for a super resolution technology. One of the nuts and bolts of neural rendering is cooperative vectors, enable an information pathway between the conventional graphics pipeline and the generative AI, telling it what it's doing, what needs to be done by the AI model, and what the ground truth for the model is.

Microsoft says that its HLSL team is working with AMD, Intel, NVIDIA, and Qualcomm to bring cross-vendor support for cooperative vectors in the DirectX ecosystem. The very first dividends of this effort will be seen in the upcoming NVIDIA GeForce RTX 50-series "Blackwell" GPUs, which will use cooperative vectors to drive neural shading. "Neural shaders can be used to visualize game assets with AI, better organize geometry for improved path tracing performance and tools to create game characters with photo-realistic visuals," Microsoft says.

NVIDIA today unveiled NVIDIA Project DIGITS, a personal AI supercomputer that provides AI researchers, data scientists and students worldwide with access to the power of the NVIDIA Grace Blackwell platform. Project DIGITS features the new NVIDIA GB10 Grace Blackwell Superchip, offering a petaflop of AI computing performance for prototyping, fine-tuning and running large AI models.

With Project DIGITS, users can develop and run inference on models using their own desktop system, then seamlessly deploy the models on accelerated cloud or data center infrastructure. "AI will be mainstream in every application for every industry. With Project DIGITS, the Grace Blackwell Superchip comes to millions of developers," said Jensen Huang, founder and CEO of NVIDIA. "Placing an AI supercomputer on the desks of every data scientist, AI researcher and student empowers them to engage and shape the age of AI."

At AWS re:Invent, Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company, today announced the general availability of AWS Trainium2-powered Amazon Elastic Compute Cloud (Amazon EC2) instances, introduced new Trn2 UltraServers, enabling customers to train and deploy today's latest AI models as well as future large language models (LLM) and foundation models (FM) with exceptional levels of performance and cost efficiency, and unveiled next-generation Trainium3 chips.

"Trainium2 is purpose built to support the largest, most cutting-edge generative AI workloads, for both training and inference, and to deliver the best price performance on AWS," said David Brown, vice president of Compute and Networking at AWS. "With models approaching trillions of parameters, we understand customers also need a novel approach to train and run these massive workloads. New Trn2 UltraServers offer the fastest training and inference performance on AWS and help organizations of all sizes to train and deploy the world's largest models faster and at a lower cost."

Today, the Khronos Group, an open consortium of industry-leading companies dedicated to creating advanced interoperability standards, has announced the release of Vulkan 1.4, the latest version of its cross-platform 3D graphics and compute API. Vulkan 1.4 integrates and mandates support for many proven features into its core specification, expanding the functionality that is consistently available to developers, greatly simplifying application development and deployment across multiple platforms.

"Vulkan 1.4 is a developer-driven update that enhances Vulkan's value as a stable, reliable framework for creating graphics-intensive applications on any platform," said Tom Olson, outgoing Vulkan Working Group Chair. "As I step down, I'm proud to see the groundwork we've laid through our roadmaps come to fruition. Our roadmap milestone plans have empowered developers with new levels of flexibility and performance, setting Vulkan on a path for continued innovation and broader adoption in the years to come."

Steam is highly valued by many gamers, not only for being a fairly inexpensive, easy way to buy and manage games, but also because it provides statistics on player count and play times, via tools like SteamDB, which are a neat way for gamers to see how the community is participating in games before buying them. According to a post on the FandomPulse Substack, however, Ubisoft has taken issue with Valve's player statistics.

The Substack post quotes Ubisoft insiders who claim that the game developer and "other companies" want Valve to disable or restrict the APIs used by tools like SteamDB and Steam Charts as a direct response to the disappointing performance of Star Wars Outlaws. This news also comes ahead of the early 2025 launch of Assassin's Creed Shadows, which has already caused significant apprehension as a result of game previews. The claims also mention that Ubisoft seeks to control the narrative of its games and potentially present a rosier image to its investors. If Ubisoft has its way, the gaming industry would lose even more transparency, since tools like SteamDB are often used by game journalists to evaluate the popularity and commercial success of games.

The Khronos Group, an open consortium of industry leaders in interoperability standards, has announced the launch of the new Slang Initiative. This initiative will oversee and advance the open-source Slang shading language and compiler, building on 15 years of research, development, and deployment experience. Supported by NVIDIA since 2017, Slang has been widely adopted in production projects across the industry.

Slang empowers real-time graphics developers with innovative features that complement existing shading languages, including modular code development, portable deployment to multiple target APIs, and neural computation in graphics shaders. Hosting under multi-company governance at Khronos will enable and foster industry-wide collaboration to drive Slang's continued evolution.

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.