New ASUS AI PC Runs Copilot Locally – No Cloud Needed

Highlights  

  • Experience top AI performance with Copilot Plus PC, which features up to an AMD Ryzen AI7 processor (a fast advanced chip for AI), up to 50 TOPS NPU (neural processing unit capable of 50 trillion operations per second), up to 64 GB DDR5 memory (high-speed system memory), and up to a 2 TB SSD (solid-state drive for storage).  
  • Boost daily productivity with ExpertCenter P600 AIO, MyExpert AI noise cancellation, and an AI-powered camera.  
  • Enjoy an immersive experience with a 27-inch FHD touch screen, a 93% screen-to-body ratio, TÜV certification, and a retractable camera.  
  • Stay secure and sustainable with ExpertCenter P600 AIO Guardian Security, MIL-STD 810H durability, and ASUS Carbon Partner Services.  

Asus has introduced two new Expert Center P600 AIO models, the 27-inch PM640 GA and the 24-inch class PM6700 GA.  

The ExpertCenter P600 AIO is an all-in-one co-pilot and PC built for cutting-edge AI performance in business, featuring up to an AMD Ryzen AI 7 processor and 50 NPU TOPS. It offers immersive visuals, AI-powered collaboration, and strong security in a modern, flexible design.  

The ExpertCenter P600 AIO features an edge-to-edge touch screen, adjustable stand options, and built-in security. Designed for modern offices, retail, and education, it helps employees work faster, collaborate better, and stay secure.  

Leading AI Performance to Drive Workplace Progress 

ExpertCenter P600 AIO includes AMD Ryzen AI7 with NPU acceleration, delivering up to 50 TOPS of AI performance, up to 64 GB of DDR5 memory, and dual storage up to 2 TB. It delivers the speed and capacity needed for today’s business and AI tasks.  

The advanced performance enables fluid multitasking, real-time content creation, and smart workflow automation, making it a powerful productivity tool. It processes AI tasks, handles data quickly, and provides ample storage for large files and applications.  

Expert Center P600 AIO features the latest Wi-Fi 7 connectivity (the newest and fastest wireless standard), providing users with fast, reliable access to cloud services and collaboration tools for smooth, uninterrupted work.  

Smart Tools for Everyday Business 

The Expert Center P600 AIO is an ASUS all-in-one co-pilot plus PC that brings next-generation AI productivity to a versatile, powerful, and stylish desktop. ASUS, my expert, offers smart AI tools to streamline daily tasks and boost productivity, improving performance, and helping users work efficiently in a simple desktop environment. The Expert Center P600 AIO uses AI noise-cancelling technology to keep voices clear. It’s built-in AI camera automatically adjusts lighting and framing, ensuring users look professional on calls. These AI-powered tools make hybrid work easier, improve meeting productivity, and support smooth communication. Cut four teams around the world.  

Immersive Design 

The Expert Center P600 AIO has a modern edge-to-edge design with a 93% screen-to-body ratio. Its 27-inch or 24-inch FHD display offers bright, true-to-life visuals, wide viewing angles, and 99% sRGB color gamut coverage. The optional touchscreen allows intuitive navigation. The glare screen is TUV Rhineland certified to reduce blue light. The retractable camera provides privacy when not in use.  

The height-adjustable stand lets you sit, easily tilt, swivel, and adjust for comfort. It supports portrait and landscape modes for easy multitasking and video calls. VESA compatibility allows wall- or arm-mounting.  

Strong Security and Lasting Durability 

The ExpertCenter P600AIO uses ASUS Expert Guardian, a comprehensive security suite that protects data at every level. It features a NIST SP 800-155-compliant BIOS with 5 years of updates, biometric login with FIDO authentication, TPM 2.0, and a 1-year McAfee Plus Premium membership. A conjunction log helps protect the device in high-risk areas. ASUS Product Adaptive Lock uses an infrared camera to automatically log users in when they are present and lock the system when they leave. A retractable camera can be hidden when not in use, giving users full control over their privacy.  

Export center P600 AIO is built to last and tested to meet TUF MIL-STD 810H US military standards. It can handle the daily bumps and stresses of business, giving you reliable performance and a calm mind.  

Sustainable Innovation 

Expert Center P600 AIO is designed for an increasingly sustainable future, with AS Carbon Partner Services helping organizations reduce and offset their products’ carbon footprint via verified, high-quality credits and the ACES digital product passport (DPP), which provides transparent, traceable life-cycle data to support responsible IT decisions built for durability and reliability. Expert Center P600 AIO extends its usable life to reduce waste, while SS’s broader ESG programs from responsible sourcing to circular-economy initiatives ensure every device contributes to environmental progress without jeopardizing performance, security, or productivity. 

Source: ASUS Announces ExpertCenter P600 AiO 

NVIDIA Unveils Vera Rubin-New Platform Aims To Cut AI Costs

News Summary 

  • The NVIDIA Vera Rubin platform is leading the way into the next AI era with:  
  • Vera Rubin NVL 72 GPU Raks  
  • Vera CPU racks, GPU3, LPX racks for faster AI answers, Bluefield 4, STX, storage racks, 4 data, and Spectrum X. SPX Ethernet racks for connecting everything.  

At GTC, Nvidia announced that the Nvidia Vera Rubin platform is launching the next phase of agentic AI: 7 new chains. Chips are now in full production to help scale the world’s largest AI factories.  

The platform brings together the Vera CPU, the Ruben GPU, a fast Ethernet link switch, a special network card, the BlueField 4 processing chip, a Spectrum 6 switch for network connections, and the new GROC3 chip for fast inference. All these parts work together as one powerful computer for every task, from training to giving instant answers.  

“ There is a generational gap: seven breakthrough chips, five racks, one giant supercomputer all built to power every phase of AI, said Jensen Huang, founder and CEO of Nvidia. The agentic AI inflection point has arrived, with Vera Rubin kicking off one of the greatest infrastructures build-outs in history.  

Enterprises and developers are using cloud for more intricate reasoning, agentic workflows, and mission-critical decisions that require infrastructure we have that can keep up, said Dario Amodei, CEO and co‑founder of Anthropic. NVIDIA’s Vera Rubin platform provides the compute, networking, and system design we need to continue delivering safe and reliable solutions for our customers.  

“Nvidia infrastructure is the foundation that lets us keep advancing AI,” said Sam Altman, CEO of OpenAI, with Nvidia. Vera Rubin will run more powerful models and agents at scale, delivering faster, more reliable systems to hundreds of millions of people.  

Shift To Pod-Scale Systems 

AI tools are evolving rip rapidly, moving from separate components to integrated systems and large-scale AI centers. These changes make AI tools evolve rapidly, moving from separate components to integrated systems and large-scale AI centers. These changes make AI fine. faster and cheaper for all types of organizations. They also make AI easier to use and consume less power.  

With close integration among computing, networking, and storage, and support from over 80 partners, where Rubin is the largest platform. For large-scale AI systems, it brings many AI racks together into a single system.  

NVIDIA, Vera Rubin, NVL 72 

The Vera Rubin NBL72 commands 72 Rubin GPUs and 36 Vera CPUs connected by NVLink 6. Plus, ConnectX9 SuperNics and BlueField 4 DPUs. This setup trains large mixture-of-experts models using only a quarter of the GPUs needed for the NVIDIA Blackwell platform and delivers up to 10× higher inference throughput per watt at one-tenth of the cost per token.  

NVL72 is built for large-scale AI factories worldwide. It works smoothly with NVIDIA Quantum X800. InfiniBand and Spectrum X Ethernet keep graphics processing unit clusters highly utilized while reducing training time and overall costs.  

NVIDIA Vera CPU Rack 

Testing AI often requires many CPUs to verify results from GPU systems.  

The Vera CPU rack is compact and uses liquid cooling. It has 256 CPUs, making it both powerful and energy-saving for running big AI projects.  

With Spectrum X networking, CPU racks stay in sync in the AI center. Together with GPU RACs, they help AI run faster and more efficiently than older CPUs.  

NVIDIA Groq 3 Lpx Rack 

NVIDIA GROC 3 LPX makes AI much faster. LPX works with Vera Rubin to give up to 35% more output for the same power and up to 10× more business value with huge models  

Many LPUs together act as one big processor for fast answers. The LPX rack has 256 LPUs, ample built-in memory, and high data speeds used with NBL72. They share the job of solving each part of AI tasks.  

LPX is designed for large AI models with substantial data. It makes computing more efficient and lets providers offer better AI services. It’s fully liquid code and will be part of the new Vera Rubin AI Centers later this year.  

NVIDIA Blue Field – 4 RTX Storage Rack 

The BlueField‑4 STX system is made for AI storage, helping expand GPU memory. Powered by BlueField‑4, it provides a fast way to store and find large amounts of AI data.  

NVIDIA DOCA memos – a new DOCA framework that enhances BlueField for storage, allowing dedicated KV cache storage processing. This boosts inference throughput by up to 5x and greatly improves power efficiency compared to general-purpose storage. As a result, the system provides POD-wide context to enable faster multi-turn interactions with AI agents, more scalable AI services, and better overall infrastructure utilization. The Four EGG4 STX rack-scale context memory storage system will enable a critical performance boost needed to exponentially scale our agentic AI efforts, said Timothee Lacroix, co-founder and chief technology officer of Mistral AI. By delivering a new storage tier purpose-built for AI agents and memory, STX is ideally positioned to ensure our model can maintain coherence and speed when reasoning across large datasets.  

NVIDIA Spectrum 6 SPX Ethernet Rack 

Spectrum-6 SPX Ethernet moves data quickly inside AI centers. It can be used with other fast network switches to provide quick, reliable connections between systems.  

Spectrum-X Ethernet Photonics uses light to transmit data, making it five times more energy efficient and ten times more powerful than conventional methods.  

Improving Resiliency and Energy Efficiency 

NVIDIA and its partners announced the DSX platform for VeraRubin. DSX Max-Q enables the AI center to use 30% more systems in the same power envelope. DSXFlex helps AI centers use unused grid power.  

By closely integrating compute, networking, storage, power, and cooling, the architecture boosts energy efficiency and helps factories scale up under constant dense workloads with maximum uptime.  

Broad Ecosystem Support 

Vera Rubin-based products will be available from partners in the second half of this year. This includes top cloud providers like Amazon Web Services, Google Cloud, Microsoft Azure, and Oracle Cloud Infrastructure, as well as Nvidia Cloud partners such as CoreWeave, Cursoe, Lambada, Nibius, NScale, and Together AI.  

Global systems manufacturers like Cisco, Dell Technologies, HPE, Lenovo, and Supermicro are expected to offer a wide range of servers based on Vera Rubin products. Other partners include Avarice, SS, Foxconn, Gigabyte, Inventec, Pegatron, Qanta, Cloud Technology (QCT), Wistron, and Wiwynn.  

AI labs and leading model developers such as Anthropic, Meta, Mistral AI, and OpenAI plan to use the Nvidia Vera Rubin platform to train larger, more advanced models. They intend to deliver long-context multimodal systems with lower latency and lower cost than previous GPU generations.

Source: NVIDIA Vera Rubin Opens Agentic AI Frontier 

AI Can Now Run Full Experiments-Researchers Reveal New System 

An AI scientist is now capable of independently completing every phase of a research experiment. It can generate ideas, conduct tests, and write and review its own papers, all without human intervention.  

A new study in Nature by Rajas from UBC and Computer Science, Sakana, AI, the Vector Institute, and the University of Oxford shows that the entire research process can be automated. This could potentially speed up scientific discovery.  

While AI has helped scientists with tasks like predicting protein structures or analyzing medical images, this is the first demonstration of AI independently completing the full scientific research process, says UBC Computer Science Professor Jeff Clune, lead author.  

It’s amazing to see what it’s been able to do so far, but even more incredible to consider what lies ahead in the near future.  

The AI scientist generates ideas, checks originality, and conducts experiments. It analyzes data, writes papers, and reviews its own work. Built on foundational models like ChatGPT, it handles a variety of research tasks.  

To test the AI’s work, the researchers submitted a fully written AI paper to a major machine learning conference workshop, where it passed peer review.  

The team also created an automated reviewer for AI-generated papers. Finding it could predict conference acceptance with a score comparable to that of humans, improving the AI model, and further raising paper quality.  

One exciting direction is the potential for AI scientists’ self-improvement, said Shengran Wu, PhD, at USB Computer Science and a co-author.  

The AI scientist opens doors to reclusive self-improvement, enabling the system not just to discover new knowledge but to use those discoveries to enhance itself and drive further breakthroughs. This is a fundamentally new kind of scientific progress. Says Hu?  

When the AI scientists completed every stage of research, the team also found some limitations, such as weak ideas and citation errors. So far, its research is limited to computer science, but it could expand to other fields in the future.  

With additional research, this system could be used to create entire scientific communities of AI agents, says Dr. Clune.  

Each new discovery could build on the system’s prior discoveries, creating an open-ended process of endless scientific discovery, just as it does in communities of human scientists. That is when we’ll see the next major scientific revolution.

Source: New AI scientist conducts its own research 

OpenAI Adds Write Tools to Apps – ChatGPT Now Edits Your Files

OpenAI has improved the ChatGPT desktop and web apps by adding tools that let the AI edit and work with your files directly. Now, ChatGPT can do more than just generate text – it can actively collaborate with you. New features include a canvas workspace for editing app integrations for working with files and a library for managing your documents.   

Key Edit And Write Features 

  • Canvas is a special workspace for writing and coding projects where you can work alongside ChatGPT.  It lets you edit text directly, making specific changes without recording anything, and use tools to adjust length, polish your writing, or add emojis.  
  • With the ChatGPT app on macOS, you can now connect to IDEs, terminals, and note-taking apps. ChatGPT can read your own open files and suggest edits that you can apply right away in tools like VS Code, Xcode, and JetBrains. So you no longer need to copy and paste changes.  
  • Chat GPT now works with app connectors like Google Drive, Notion, and Handbox. You can read, create, and edit files, write in your conversation, including Word documents, sheets, and project files, for a period.  
  • Library (web): the file library is a central place where you can store, manage, and reuse files like PDFs, sheets, and images that you can upload or create during conversations. This helps you to keep track of files for long-term projects.  
  • When using IDEs, ChatGPT can edit your open files and show you the changes to review and apply, so you can skip manual copy-pasting.  
  • In Canvas, you can click to edit text or code directly, and ChatGPT will suggest edits as you work.  
  • Canvas includes a black button that lets you easily go back to earlier versions of your work.  
  • ChatGPT can now edit images by letting you select an area and describe what you want changed, rather than creating a whole new image.  

Availability 

These features will be released to ChatGPT Plus, Team, Business, and Pro users on the web, macOS, and Windows. Canvas will be available on the website and on mobile devices soon.  

On March 27, 2026, OpenAI’s latest release brings conversational interfaces and productivity tools closer together. OpenAI added direct write support to popular third-party services, letting users manage cloud-based content such as documents and project boards with simple commands.  

Unified Integration With Cloud Ecosystems 

This evolution is best seen in how connectors have transformed into more capable apps. Previously, users could link only accounts from services like Google Drive, Microsoft OneDrive, and Dropbox to search for or reference files. With this update, the platform now enables direct changes within those environments rather than creating drafts. For manual copying, it can now open a file, add new sections, or rewrite paragraphs directly in the source document.  

Building on this broader functionality, the new feature integrates with major productivity tools like Google Docs, Sheets, Slides, and Microsoft Outlook for both business and creative work. It streamlines workflow by reducing the need to switch between apps and helps maintain focus. For example, you can now instruct the system to add rows to a Google Sheets spreadsheet or revise an output, look at a draft for formality without leaving the main chat window. Every change still requires a clear request, ensuring ongoing user control over their files.  

Collaborative Drafting and Task Management 

The right tools now work with services such as Notion, Box, Linear, and Jira, going beyond common office software in project management. This helps teams keep documentation up to date and track progress more easily. Users can ask the system to create new GRO issues or update project statuses in Linear after meetings or ideation sessions. This makes the platform an active part of project management rather than just a place to store notes.  

The interface has improved with new features, such as interactive code blocks and a dedicated canvas view when editing a file. Users see the base text and propose changes side-by-side in real time. This arrangement lets users highlight phrases and request quick edits, whether updating a technical manual on the go or handling a marketing inbox breeze. The system keeps the drafting and editing process in sync with the file stored in the cloud.  

Security And Administrative Oversight 

Because these tools can change sensitive company files. OpenAI uses a tiered permission system. To protect data for enterprise and education accounts, the right actions are off by default and must be turned on by an administrator. This lets organizations review security risks before letting the system access their files. Every change is also logged, providing a clear record of what was changed and when.  

For Plus and Pro users, the system re-authenticates when someone connects an app for read-only access before they need to reconnect to allow new write permissions. This ensures users know exactly what access they are granting. There is also a new library feature in the sidebar that lets users view, search, and manage all files they have uploaded or edited across conversations. This helps keep things organized, especially for users with many files.  

The Evolution of the Digital Workspace 

The new writing tools signal the end of the old, isolated digital assistant. Now the tools we use to think and to build are coming together, making it much easier to turn ideas into finished work. Our digital notebooks now respond quickly and accurately to our input. In the future, we might not need to open or save files as we do now. Instead, we will work in a continuous, shared space where every idea is captured right away. The workspace of tomorrow will be organized and seamless, letting us concentrate on creativity while the system manages the details in the background.

Source: Updated Box, Notion, Linear, and Dropbox apps 

NVIDIA Expands 6G Research to Support Future AI Networks

NVIDIA develops 6G technology through its research, which uses artificial intelligence as a core element for upcoming network systems. The company’s initiatives shift telecom networks from merely faster systems to AI-native platforms that support autonomous decisions at scale.  

Today’s conventional network systems struggle to keep up with the growing demand for AI-driven services worldwide. NVIDIA develops its research programme to integrate artificial intelligence across all telecom infrastructure centres. This approach has led the industry to develop networks that combine connectivity with computational awareness.  

Reimagining Networks as AI Infrastructure  

Telecommunications operators developed 6G as an advanced AI system that integrates AI with network infrastructure. NVIDIA research shows that networks should have built-in intelligence, enabling systems to assess current situations and make predictions while executing real-time responses.  

The current digital landscape needs to address increasing complexity, as its various components have created more complex systems. Autonomous vehicles, smart cities, and industrial automation systems demand networks capable of handling high-volume data traffic and processing it in real time. The 6G system uses artificial intelligence to optimise network performance, manage traffic flow, and increase system reliability, without requiring human operators to make continuous updates.  

This development marks a crucial transformation for American telecommunications companies. Networks have evolved from their original function as data transmission systems to become integral components of contemporary computing processes.  

AI-RAN: The Foundation of 6G Development  

NVIDIA’s research focuses on developing Artificial Intelligence Radio Access Network (AI-RAN) technology. The system enables RAN to process wireless signals in real time while handling AI workloads and conducting standard communication operations.  

Researchers use the NVIDIA AI Aerial platform to create and evaluate machine learning algorithms that operate throughout all RAN stack components. The systems enable engineers to create network models that replicate actual conditions, using synthetic and real-time data to train and test their solutions in over-the-air environments. Communication workloads on shared infrastructure are a key advantage. The system enables organisations to operate their resources. more efficiently, reducing costs and increasing innovation speed compared to separate network systems.  

Industry Collaboration and Global Alignment  

NVIDIA is not developing 6G technology through its own independent research efforts. The company has partnered with various telecommunications operators, technology companies, and research organisations to build AI-based wireless communication systems.  

The international collaboration involves major organisations working to develop open and secure 6G network standards that enable multiple systems to interoperate. The project aims to develop systems that will continue running without interruption while meeting future growth requirements and enabling multiple artificial intelligence technologies. Siders consider these technological developments to be crucial. The government and industry decision-makers consider 6G technology to be an essential national asset that drives economic development and protects national security and technological leadership. NVIDIA establishes a unified research direction for all 6G network development partners through its research alignment method.  

Enabling Real-Time AI Applications  

NVIDIA conducts research on 6G technology to develop solutions that can handle large-scale, real-time AI operations. self-driving vehicles, state-of-the-art robotic systems, full virtual reality environments, and extensive Internet-of-Things networks.  

The applications need connections that meet their critical requirements for extremely low latency, dependable service, and continuous data processing. The AI-native 6G system solves these challenges through its design, which connects computing resources with communication networks in a single unified system. The system provides real-time edge analysis of sensor data, while central systems manage decision-making across the network. The distributed intelligence architecture will be a vital element of sixth-generation telecommunication networks. 

From 5G to 6G: A Strategic Transition  

6G development remains active, but its foundation construction depends on the current 5G network systems. 5G networks already implement virtualised RAN (vRAN) and edge computing with AI network optimisation technologies as pathways leading to 6G capabilities.  

NVIDIA extends its technology through the development of artificial intelligence-focused systems that use advanced computing technologies. The company establishes itself as a major player in network evolution by leveraging its expertise in accelerated computing and artificial intelligence to build intelligent systems from traditional connectivity networks. Yes. The transition to AI-native operations requires telecom companies to make major infrastructure investments, creating new business opportunities and revenue streams.  

Implications for the US Telecom Landscape  

The United States needs more advanced, high-performance networks, as demand for them continues to increase. The United States needs 6G research and development to address its growing demand for advanced network technology. The demand for scalable, intelligent infrastructure solutions has reached critical levels as urban smart city programmes and rural connectivity initiatives expand their operations. 

AI-native 6G networks enable better spectrum utilisation by enhancing network reliability and supporting new technologies that require real-time data processing. These applications include healthcare, transportation, defence, and manufacturing.  

US carriers can gain a competitive edge by adopting technology, as international markets link network infrastructure innovation to economic development.  

Looking Ahead: The Future of AI Networks  

NVIDIA research shows that network technology development paths will move toward 6G implementation, which commercial companies plan to roll out during the 2020s. The deployment of AI across all infrastructure components marks a major shift, enabling networks to function as smart systems that will power upcoming digital services. The research investigates advanced spectrum usage methods, energy-saving techniques, and distributed computing systems. Businesses, educational institutions, and governmental bodies must establish ongoing partnerships to successfully develop standards and implement them. 

NVIDIA’s ecosystem role shows AI organisations now critically shape the future of telecommunications development.

Sources: Into the Omniverse: NVIDIA GTC Showcases Virtual Worlds Powering the Physical AI Era

Samsung Improves Galaxy Buds Audio with AI Voice Clarity Update

Samsung has introduced a major sound improvement for its new Galaxy Buds, which uses artificial intelligence to improve voice understanding. The Galaxy Buds4 series update uses artificial intelligence for noise reduction, together with an extended audio range, to create natural-sounding conversations that function better in actual noisy situations.  

The company’s latest update shows how voice communication via wireless earbuds has evolved, alongside AI-based audio processing technology. The company uses machine learning as its primary method to improve audio recording and filtering, as well as sound transmission, rather than relying solely on hardware upgrades.  

A Shift Toward AI-Driven Call Quality  

The main purpose of this update is to support Samsung’s HD Voice system, which uses artificial intelligence for noise reduction and voice enhancement. The system uses multiple microphones positioned across the earbuds to capture sound from different directions, while a Voice Pick-Up Unit (VPU) isolates the user’s voice from surrounding noise.    

The system processes data in real time using machine learning models trained to identify spoken words from background noise, including traffic, wind, and nearby conversations. The result yields a clearer audio signal that emphasises the speaker’s voice in difficult listening conditions.    

This method enhances the quality of outgoing voice during calls, whereas traditional noise-cancellation methods block surrounding sounds to improve listening experiences.  

Expanding the Limits of Bluetooth Audio  

The update provides a major technical advancement by increasing the bandwidth for Bluetooth audio transmission.  

Samsung’s update delivers “super wideband” audio, which doubles the existing bandwidth to 16 kHz. The system now records all vocal frequencies, including the consonant sounds that normal calls fail to transmit. The elements that include “s”, “z”, and “th” sounds serve as essential components that enable people to understand spoken language. The updated Galaxy Buds retain the features that enable users to experience calls that feel like face-to-face conversations. The process shows how small protocol adjustments can yield major benefits for users in their daily activities.  

Real-Time Processing and Environmental Adaptation  

The AI voice clarity system must operate in real time to adjust its functions as environmental conditions change. The system tracks incoming street sounds while people use it to test its performance in busy streets and cafes, as well as during their daily commutes.  

The system achieves real-time processing because its AI components operate inside the earbuds instead of depending on the attached smartphone. The Buds function as part of Samsung’s Galaxy AI system because they can perform specific processing tasks independently, helping reduce delays and make the system more responsive.  

The results improve call quality by reducing interruptions while maintaining steady audio performance across different usage situations.  

Integration with the Galaxy Ecosystem  

The Galaxy Buds perform best when connected to Galaxy smartphones that meet the latest requirements, including the Galaxy S26 series. The combination of hardware and software components. The system creates features that enable users to connect devices easily while the system processes AI tasks and delivers better sound quality.    

Samsung has positioned the Galaxy Buds4 series as an extension of its broader AI strategy, where devices work together to deliver context-aware experiences. The system improves voice clarity while it provides users with adaptive noise cancellation and hands-free voice control.    

Samsung has built AI capabilities into all its devices, creating a complete user experience that extends beyond hardware updates.  

Beyond Calls: A Smarter Audio Experience  

The update centers on improving call clarity, but the underlying AI technology also provides additional benefits for audio quality. The system uses machine learning models for voice separation, which also enhances its capacity to manage ambient noise during music playback and voice assistant operations.  

The same processing techniques that isolate speech during calls can optimise voice commands and enhance the accuracy of AI assistants. This aligns with Samsung’s vision of earbuds functioning as intelligent audio companions rather than passive listening devices.  

The Galaxy Buds4 series already shows its evolution toward more interactive audio devices through the introduction of real-time translation, gesture controls, and AI-powered assistants.  

Competitive Positioning in the Wearables Market  

Samsung is currently pursuing AI-powered audio enhancements amid heightened competition in the wireless earbuds market. Companies have shifted their product differentiation strategy, prioritising software features and ecosystem compatibility over performance and battery life.  

Samsung uses AI technology to improve voice clarity, which solves a major problem for users who need earbuds to make phone calls and join virtual meetings. Clear audio exists as a fundamental requirement in professional environments because it directly affects work efficiency.  

The update enables Samsung to adopt better technologies while demonstrating that AI is a key differentiator for wearable devices.  

Implications for Everyday Use  

Users will experience the most visible benefits from this update in situations with constant background noise. Better voice transmission during outdoor calls and at busy public locations enables users to communicate more effectively.  

The system uses AI-based noise cancellation, along with increased bandwidth, to reduce the need for users to repeat their words or search for quiet spaces. The earbuds now offer users multiple options for their personal and work needs.  

The current trend toward increased remote work, together with mobile communication, requires these technological improvements as mandatory requirements.  

Looking Ahead  

Samsung will introduce new audio processing capabilities through the ongoing development of its Galaxy AI ecosystem. The upcoming updates will deliver enhanced contextual understanding abilities, together with better user personalisation features and improved service integration across multiple AI-powered platforms.   

Current voice clarity enhancements demonstrate the transformative power of AI technology in people’s daily interactions with technology. The changes might seem minor, yet they create major improvements in both usability and communication.  

Samsung has shown through its latest update that even small improvements in AI processing technology can change essential functions like voice calls, which establishes new standards for wireless earbud performance.

Sources: Samsung Newsletter Global 

Samsung Unveils Galaxy Buds4 Series: Ultimate Hi-Fi Sound with Enhanced Comfort and Fit

OpenAI Updates Sora Rollout Plans With Focus on Safe Deployment

We are training AI to understand and simulate how the physical world moves. Our goal is to create models that help people solve problems that involve practical interactions.  

Meet Sora, our text-to-video model. Sora can create videos up to a minute long, maintaining both visual quality and the details you request in your instructions.  

Today, we are sharing Sora with the Red team to identify any risks or harms. At the same time, we are inviting visual artists, designers, and filmmakers to provide feedback to improve Sora’s usefulness for creative work. This collaborative input helps shape Sora for future applications.  

To support all of these goals, we are sharing our research progress early. This helps us collaborate with people outside OpenAI, gather diverse feedback, and give the public insight into near-future AI capabilities.  

Sora can create elaborate scenes with several characters, varied movements, and accurate details in both the subject and the background. The model understands what you ask for in your instructions and how these elements work in the real world.  

The model understands language well; it can interpret prompts accurately. Sora creates interesting characters with several shots, keeping them and the visual style uniform throughout.  

The current model is not perfect yet. It can struggle to convey physics in complex scenes and may miss some cause-and-effect details such as a cookie not showing a bite mark after someone bites it. The model might also mix up directions (e.g., left and right) or struggle with detailed descriptions of events over time (e.g., camera movements).  

Safety 

We will take important safety steps before Sora becomes available in OpenAI’s products. We are working with Red Teamers. They are experts in areas like misinformation, hateful content, and bias. Their job is to test the model in challenging ways.  

We are also creating tools to help spot misleading content. These include a detection classifier that determines whether a video was made by Sora. In the future, if we release Sora in an OpenAI product, we plan to include C2PA metadata.  

Along with developing new safety techniques for Sora, we are also using the safety methods we created for our DAL·E3 products. These methods work for Soratoo.  

For example, when Sora is part of an OpenAI product, our text classifier will block prompts that break our usage policies. These include those asking for extreme violence, sexual content, hateful images, celebrity likenesses, or someone else’s intellectual property. We have also built strong image classifiers. They review every video frame to ensure it complies with our policies before it is shown to users.  

We will talk with policymakers, educators, and artists worldwide to learn about their concerns. We want to find ways to use this new technology. Even with extensive research and testing, we cannot predict every potential positive or negative use. That is why we think learning from real-world use is key to making AI systems safer over time.  

Research Techniques 

Sora is a diffusion model. It starts with a video that looks like white noise, gradually becoming clearer as the noise is removed step by step. Sora can create entire videos at once or extend existing videos by letting the model see many frames at once. We solve the tough problem of keeping a subject the same even if it leaves the frame for a moment.  

Like GPT models, Sora uses a transformer architecture, which allows it to scale up its performance.  

We represent videos and images as collections. We break videos and images into small pieces called patches, similar to tokens in GPT. By using this unified representation of data, we can train diffusion transformers on a wider range of visual data, including images and videos of varying lengths, resolutions, and aspect ratios, as well as GPT models. It uses the recaptioning technique from DALL·E 3, which entails generating highly descriptive captions for the visual training data. As a result, the model can more faithfully follow the user’s text instructions in the generated video.  

Besides generating videos from text instructions, the model can turn a still image into a video by animating its contents with careful attention to detail. It can also extend an existing video or fill in missing frames. You can learn more in our technical report.  

Sora is a starting point for models that can understand and simulate the real world. We believe this is an important step toward reaching AGI.

Source: Creating video from text 

Samsung Showcases AI Upgrades for Clear Photos in Motion

Mobile photography has come a long way. Still, getting clear, sharp photos of moving subjects has always been tough for smartphone cameras. While tail shots and portraits now look almost professional, moments like a child’s first step, a pet jumping, or a fast sports move often lead to unwanted motion blur. In March 2026, Samsung introduced AI-powered tools designed to solve this problem. The latest ProVisual Engine uses cutting-edge optical and computational photography. It captures crisp photos of action scenes with impressive accuracy.  

Samsung’s new technology, launched with the Galaxy S26 series, marks a shift from relying on hardware shutter speeds to an AI-driven approach to photo capture. For photographers and tech fans, these changes are more than just another filter  they completely change how smartphones capture movement.  

The Provisual Engine: Establishing a New Standard for Capturing Motion 

Samsung’s 2026 camera improvements center on the upgraded ProVisual engine. This is an AI-powered image processing system, meaning it uses artificial intelligence to automatically analyze and enhance photos. The system is designed to overcome the physical limits of small smartphone sensors (the part of the camera that receives light to create images). When something moves quickly in the frame, the engine starts processing the scene even before you take the photo.  

The main innovation is a process called semantic motion deblur that goes beyond simply fixing blurry edges. After a photo is taken, the ProVisual Engine uses fast AI sampling to track how objects move in the frame. It compares the object’s speed to tiny camera movements, then combines data from several quick shots. The final image keeps the natural lighting of a longer exposure and also has the sharp edges you would expect from a high-speed burst.  

Enhanced Motion Photo: A Wider Storytelling Window 

Motion Photo has been part of Galaxy phones for years, but the 2026 version adds much more depth. Previously, these clips were seen as low-resolution extras. Now, thanks to new AI upgrades, Samsung has expanded the capture window to 3 full seconds  1.5 seconds before and after you press the shutter using AI to pick the best frames. With this update, Motion Photo shifts from a novelty to a true storytelling tool.  

To further enhance the experience, a new frame interpolation algorithm makes the switch from still photo to video smooth and natural. Motion Photo is now more than just a looping GIF. If it’s a high-definition mini movie, the AI finds the best moment in those 3 seconds and suggests it as your main photo. So even if your timing is off, the camera has already saved the perfect shot for you.  

Video Stabilization: Super Steady With Horizontal Lock 

At the March 2026 showcase, Samsung introduced a big upgrade to super steady video. The new system uses improved sensor-shift OIS (optical image stabilization using a sensor that moves to counteract hand shake) and an AI-powered horizontal lock (which uses artificial intelligence to keep your video straight even if you rotate your phone), so you can rotate your phone a full 360 degrees and your video still stays level with the horizon. These new features are designed to further advance content creation.  

This upgrade is especially helpful for action sports and vlogging, where you are often on the move while filming. The AI image signal processor and the phone’s gyroscope work together to predict movement, then crop and smooth your video in real time just like a professional 3-axis gimbal. As a result, you get studio-quality stability from a device that fits in your pocket, so you don’t need to carry heavy gear when creating content on the go.  

Proscler And The Detail Of Distance 

Taking photos of moving objects from far away is tricky because digital zoom often makes images blurrier. To solve this, Samsung added ProScaler technology to the Galaxy S26 Ultra and Plus. ProScaler uses 128 distinct neural networks to instantly sharpen and improve textures.  

When you use the telephoto optical zoom to photograph something moving like a football player far away or a bird in flight. ProScaler examines the fine details of hair, fabric, and skin. It highlights the difference between the subject and the background, then reduces noise on the moving object to reduce blur. This way, the 200 MP sensor can capture sharp images even as the subject moves across the frame.  

Low Light Motion: The Nightography Revolution 

Getting a clear photo of something moving in low light has always been one of the toughest challenges in mobile photography. Because cameras need more time to gather light in the dark (meaning a longer exposure), moving objects often end up blurry. Samsung’s 2026 Nightography video and stills update tackles this with a fast AI noise-filtering system (a tool that quickly removes unwanted graininess from images). Camera’s main sensor now has a much wider f/1.4 aperture, letting in 47% more light than before. The AI then reduces noise caused by fast movement in low light. This means you can get clear, colorful photos of moments like a friend laughing by a campfire or a performer on stage without the blurry textures and ghosting that used to be a problem.  

AI, ISP, and Naturalism: Beyond the Plastic Look 

People often say that AI-enhanced photos look too processed or give skin and textures a plastic look. With the March 2026 update, Samsung focused on keeping photos looking natural. The new AI ISP was trained on a wider range of skin tones and lighting conditions, so it removes blur while keeping the scene looking real.  

Now the system can pick out details such as single hair strands, fabric patterns, and even small reflections in a moving person’s eyes. This focus on detail helps the AI make photos look natural. The aim is to create images that look just as bright, sharp, and lively as what you see with your own eyes, not like a computerized copy.  

The Ghost in the Lens: Atemporal Reflection 

We are entering a new era in which cameras can use AI to reduce blur, making flawed moments less common. There used to be something special about a blurry car’s headlights or a child’s hazy smile and reminders that time keeps moving. Now, with Samsung’s new AI features, every moment can be captured in perfect detail with every blur removed. One day, our photo galleries might feel like collections of frozen moments where nothing moves except the still presence of AI, always trying to capture what we missed.

Source: What are the key features of Galaxy AI? 

Google Expands AI Protections to Limit Risky Ads for Minors

As technology advances, we continually develop new strategies to safeguard our users’ online security. Today, we are announcing updates that reinforce our protections for users under 18. These improvements are designed to shield young people online and offer parents and guardians greater peace of mind.  

Protecting Kids and Teens Online 

In recent years, we’ve introduced several updates to give kids and teens experiences tailored to their ages on our products. For users under 18, we now enable SafeSearch by default, strictly block sensitive ads and age-restricted content on YouTube and Play, and introduce teen well-being features in our AI tools on YouTube. We are also launching a sensitive content warning in Google Messages. Adults can activate this in Android settings, but for users under 18, it’s enabled by default on supervised accounts with parental controls.  

One of the most complex aspects of delivering age-appropriate protection is accurately identifying a user’s age. This year, we will pilot a machine learning model in the US to reliably estimate whether users are over or under 18. This enables us to apply the right protections. We plan to expand this technology globally in the future.  

More Controls for Families 

Every family is unique, so we designed Google Family Link to help parents shape their children’s digital habits in ways that suit them. Today, we are updating Family Link to make the primary tools for managing screen time easier to find. This streamlines the process for parents managing multiple children’s online activities across Android and Chrome devices.  

We are adding features to Family Link that help kids concentrate during class by reducing distractions on their devices. Starting next week, we will roll out School Time on Android phones and tablets. This enables parents to automatically limit device use and restrict app access during school hours.  

Next month, parents will be able to add contacts directly to their children’s devices and choose to limit calls and texts to those contacts. This ensures kids connect safely and intentionally.  

Helpful Experiences for Kids and Teens 

We want everyone, including kids and teens, to have access to the best of Google. That’s why we offer devices like Fitbit Ace LTE, Samsung Galaxy Watch for Kids, YouTube Kids, and Supervised Access to Gemini for teens at home and in school. Here are new ways we’re enabling kids and teens to explore, learn, and play securely online.  

Soon, supervised Android users below the age of consent can use Tap to Play on their phones. Beginning this spring, parents can connect a payment card to their child’s Google Wallet. For in-store purchases, parents will manage card approval or removal and monitor recent transactions. Kids can also add gift cards and event tickets.  

We aim to help teens develop essential skills for a future shaped by generative AI. We also want to demonstrate how this technology sparks creativity and enhances learning. Over the past two years, we have introduced features for teens such as AI overviews, Gemini, and Circle to Search. In the coming months, we will further expand access to these tools, including a new feature called Learn About, which uses generative AI for interactive learning.  

We are committed to advancing technologies and partnerships that help keep kids and teens safe online.

Source: New digital protections for kids, teens and parents