OpenAI Adds Location Controls to Improve ChatGPT Local Responses

Large language models have quickly moved from offering general knowledge to providing more local, practical help. In late March 2026, OpenAI introduced location controls to improve the accuracy of ChatGPT’s local responses. This change addresses a common problem: AI giving regional advice without knowing exactly where the user is. It can make mistakes, such as geographic hallucinations. With this update, ChatGPT now understands a user’s surroundings in a more detailed, context-aware way, rather than just relying on general coordinates.  

For developers and advanced users, this shift is called Geospatial Grounding. With clear user permissions for each session, the model can now use detailed location data. This means ChatGPT can act like a real-time digital assistant, able to distinguish between a suggestion for an entire city and one for a specific street corner.  

The Architecture Of Geospatial Grounding 

In the past, if someone asked for a coffee shop with fast Wi-Fi, the model used older training data or conducted a wide web search, often returning results far away. The new location controls add a layer of surroundings to the process. When location access is enabled, the API sends a basic coordinate code that helps the model narrow its search and use its knowledge more locally.  

This update stops the proximity drift that previously made local searches less useful in busy cities like London and New York. Being off by just a few blocks can make a big difference. Now, ChatGPT uses GPS, IP-based geofencing, and past local search patterns to better understand local weather, transit times, and business hours where the user is.  

Enhancing Real-Time Utility With Local Context 

Mobile users benefit the most from these new location controls as ChatGPT is added to wearables like smartwatches and car systems. More people want smart help while they are out and about. The 2026 update introduces proactive proximity alerts, which are notifications triggered by your location. For example, if someone is walking through a neighborhood and asks about local landmarks, the AI can now give a live narrated tour that updates as the user moves.  

This goes beyond just finding places on a map. The model now understands local details, such as the difference between the park being closed for a concert today and the park being open, based on live local news and the user’s exact location. ChatGPT becomes more like a real-time interactive guide than a strategic encyclopedia.  

Privacy First, Location Management 

OpenAI knows that location data is sensitive, so it has set a zero-retention policy for exact coordinates. In the new settings, users can choose from three privacy levels: precise, neighborhood, or city.  

If users choose a neighborhood, the AI gets enough information to help, but doesn’t know their exact address. Also, these location settings only last for the current session. When the chat ends, the detailed location data is deleted so the AI can’t track users over time. The design supports building trust at a time when many people worry about data collection.  

Impact On The Local Business Ecosystem 

Improving ChatGPT’s local responses has a big impact on SEO and how people find small businesses. Before, businesses used search engine optimization to appear in local search results. Now, with ChatGPT’s location-aware features, discovery is more about contextual relevance.  

If someone asks for a quiet place to work near me, the AI doesn’t just pick the top-related spots. It looks at recent reviews for terms such as quiet, outlets, and strong coffee. This helps businesses that offer real value, not just those with big marketing budgets. For local economies, it means people find places that truly fit their needs.  

The Developer Frontier Localized API Hooks 

For developers using OpenAI, the new location controls and additional environment variables enable apps to send local context strings to the model, enabling the creation of highly specialized tools. For example, a real estate app can use ChatGPT to provide a neighborhood atmosphere check, including school ratings, crime stats, and how walkable a block is all using live data.  

This kind of integration enables the creation of geofenced AI agents. For example, an agent could return only when you enter a specific grocery store, helping you find items on your shopping list and navigate the store’s layout. The 26th position update lays the basics for many new local AI experiences. As we begin to match the physical contours of our world, we are witnessing the birth of a new kind of mapping. No longer are we looking at a flat, static representation of our streets and cities. We are inhabiting a world that is beginning to watch us back with a helpful, productive gaze. Eventually, the true heir of a city might feel charged with an invisible intelligence, a silent, helpful ghost that knows the history of the cobwebbed alleyway you are walking down and the name of the baker whose ovens are just beginning to warm. We are moving toward a state where the boundary between the digital prompt and the physical step finally dissolves, leaving us to wander across a landscape that is as much an extension of our own curiosity as it is a piece of brick and mortar, a world in which every corner whispers its messages to a machine that has finally learned how to listen to the beat of the pavement beneath our feet.

Source: ChatGPT — Release Notes 

Google Launches Gemini Flash Live for Real-Time Voice AI

We are excited to introduce Gemini 3.1 Flash Live, now available to all developers through the Google Live API in Google AI Studio.  

This update improves response latency, increases uptime, and enhances the realism of synthesized speech setting a technical benchmark for voice-first AI applications.  

Enjoy Improved Speed, Reliability, and Overall Quality 

In real-time conversations, even small delays can disrupt the natural flow users expect. The new model captures tone, emphasis, and implication more accurately, leading to several key improvements.  

  • Higher task completion in noisy environments. Their model is now much better at using external tools and sharing information during live conversations. It can distinguish between important speech and background sounds like traffic or TV, so it stays reliable and follows instructions even in busy settings.  
  • Instruction-following is improved via advanced intent parsing and context retention. The model maintains compliance with agent guidelines, even as conversational topics shift and tasks require adaptive understanding.  
  • Dialogue latency is minimized through model optimization, allowing rapid detection of nuanced audio features such as pitch and pace. This results in conversations that emulate natural human timing and turn-taking more effectively than prior versions.  
  • The model’s multilingual capabilities now support real-time voice interactions in over 90 languages, enabled by parallelized training and language-specific acoustic modeling.  

Watch the Gemini Live API at Work 

Developers are already using Gemini Flash Live models to build voice agents that communicate naturally and act reliably. Here are some real-world apps powered by the model.  

Take Advantage Of A Growing Range Of Integrations 

The Live API is designed for production use and can handle a variety of inputs, including live video, streams, and on-demand phone calls.  

If your system needs web, IC scaling, or global edge routing, check out our partner integrations to make it easier to build real-time voice and video agents.  

Start Building With The Live API 

Gemini 3.1 Flash Live is now available through the Gemini App API, and Google AI Studio developers can use the Gemini Live API to add the model to their apps. See developer documentation to learn how you can build real-time agents.  

  • Find details on multilingual support, tool use, session management, and more in the Gemini Live API documentation.  
  • Discover sample voice experiences you can build today with Gemini Drive API examples.  
  • Enhance your coding agents with the Gemini Live API SQL.  

Start using the Google Gen AI SDK.  

import asyncio from google import genai  

client = genai.Client(api_key=”YOUR_API_KEY”)  

model = “gemini-3.1-flash-live-preview” config = {“response_modalities”: [“AUDIO”]}  

async def main(): async with client.aio.live.connect(model=model, config=config) as session: print(“Session started”) # Send content…  

if name == “main”: asyncio.run(main()) 

Source: Build real-time conversational agents with Gemini 3.1 Flash Live 

NIST Introduces AI Security Standards for US Data Center Infrastructure

The National Institute of Standards and Technology (NIST) has introduced a new initiative to establish security and interoperability standards for artificial intelligence systems deployed across the US data center infrastructure. The announcement reflects growing concern among policymakers, enterprises, and researchers about the rapid integration of AI into critical systems without consistent governance frameworks.  

Data centers serve as the core operating structure for intelligent computing since enterprises across multiple sectors adopt artificial intelligence at an increasing pace. The environments support enterprise AI deployments and cloud platforms through their data processing models, which handle sensitive information and make automatic decisions to deliver critical services. NIST’s move signals a shift toward formalizing the security, evaluation, and management of these systems at scale.  

The initiative focuses on developing standards for AI agents. These are systems capable of performing tasks autonomously within digital environments. The agents can function within advanced systems, access various services, process multiple datasets, and run different applications. Without clear security protocols, such systems could introduce vulnerabilities that impact infrastructure stability and data integrity.  

Building a Framework for AI Agent Security  

NIST has established security standards that provide organisations with a unified framework for safeguarding their AI systems. The agency aims to define how these systems should be designed, tested, and deployed to ensure they operate safely within enterprise and cloud environments.  

AI agents differ from traditional software systems because of their ability to make decisions, adapt to inputs, and execute multi-step tasks. The system introduces new security challenges because it must control how agents access information, how their systems connect with each other, and how their activities are tracked.  

The NIST-developed framework will create standards that organisations can use to verify their users and control system access while monitoring user behaviour. The measures will establish operational limits for AI agents, preventing them from executing actions that are not permitted in data center spaces.  

The project aims to achieve interoperability by enabling AI systems from different vendors to work together securely. The requirement becomes vital for operational functions that handle multiple platforms and services in extensive data center environments.  

Addressing Risks in AI-Driven Infrastructure  

Data center infrastructure gains three major advantages from AI implementation: automated processes, increased operational efficiency, and expanded system capabilities. The implementation of these technologies creates fresh security challenges that existing protection systems cannot effectively address.  

Security experts view the possibility of AI systems being used for malicious purposes as a major security threat. An attacker who gains control of an AI system can manipulate all decision-making processes, acquire protected information, and halt system functions. NIST uses its standards to create guidelines that help organisations establish systems that identify and manage their unusual operational patterns.  

Data privacy protection presents a major challenge for organisations. AI systems require extensive training data, which may include confidential materials that organisations must protect in accordance with legal standards. The framework should provide data management rules that enable AI systems to operate in compliance with privacy regulations without sacrificing operational efficiency.  

The initiative works to create transparent systems. AI systems create complex decision-making processes that require advanced expertise to understand. NIST creates standards that organisations must follow to document their systems and explain their operations, thereby establishing trust in AI technologies.  

Implications for US Data Centers  

AI security standards have dual impacts on US data center operators, presenting both challenges and opportunities. The new guidelines will require organisations to modify their existing infrastructure system. This process requires organisations to enhance their security measures, establish new monitoring systems, and conduct staff training programmes for AI environment management.  

The standardised frameworks provide organisations with clear guidelines for implementing AI technologies within their existing processes. Security incidents decrease as organisations adhere to guidelines, while system reliability increases.  

The initiative serves as an important programme in multiple industry sectors. Secure and interoperable systems are crucial for establishing trust relationships that drive future development in the cloud computing industry.  

Interoperability as a Strategic Priority  

NIST demonstrates its dedication to interoperability through its implemented methods. Modern data centers use AI systems that operate alongside their databases, APIs, and other services across different platforms.  

The absence of standard protocols enables security vulnerabilities to emerge during system interactions. Attackers can exploit system vulnerabilities arising from the different authentication methods and data formats used by organisations.  

NIST seeks to establish an interconnected system through its interoperability efforts, enabling AI systems to exchange information securely and efficiently. Organisations will need this capability as they plan to implement multi- and hybrid cloud solutions, which require seamless connectivity across their multiple operating environments.  

Industry Collaboration and Adoption  

The NIST initiative needs partnerships with other organisations to succeed. The agency is working with industry partners, academic institutions, and government organisations to develop and refine the proposed standards.  

The collaborative approach establishes practical guidelines that can be used in multiple scenarios. The system enables stakeholders to share their knowledge, helping solve problems that arise during AI implementation.  

Organisations will begin implementing the standards gradually, requiring them to assess their current systems before aligning their operations with the new regulatory framework. NIST guidelines will become increasingly important for organisations when they need to comply with regulations and make procurement decisions.  

Preparing for the Future of AI Infrastructure  

The ongoing development of artificial intelligence will lead to greater use of AI technologies within data center systems. The systems will achieve higher levels of independence while creating deeper links to business functions that have become essential throughout the organisation. The need for robust security requirements has reached a critical point due to this development.  

The NIST initiative serves as an initial effort to solve existing problems. The agency creates fundamental rules for securing AI systems that will define how AI technology is used throughout the United States.  

Organisations that proactively adopt these standards will achieve better results when integrating artificial intelligence technologies. The two organisations will demonstrate their dedication to security and reliability, which are essential to success in the digital business world.

Source:  Announcing the “AI Agent Standards Initiative” for Interoperable and Secure Innovation 


SpaceX Files for Direct-to-Cell License to Expand US Satellite Coverage

SpaceX filed its direct-to-cell license application to expand its US satellite connectivity operations. The direct-to-cell license application threatens to disrupt all national mobile network systems. The company uses its Starlink network, which consists of low-Earth-orbit satellites that provide internet access, to develop its operational capabilities.  

SpaceX intends for standard smartphones to link directly to satellites, without additional hardware. People who live in remote areas that currently lack mobile service will benefit from this technology because it enables them to access mobile networks. Satellite systems are being integrated into standard mobile networks according to this industry trend, which the company uses as its operational approach. 

Expanding Beyond Traditional Satellite Internet  

Starlink provides satellite internet as its primary service, delivering broadband internet to people living in remote areas. SpaceX has reached a critical development phase with the introduction of direct-to-cell wireless technology.  

The system enables mobile phones to establish satellite connections without needing cellular network infrastructure. The system allows users to send messages and use basic data functions even in areas without cellular towers. The industry is developing hybrid networks that combine satellite systems with ground-based networks to expand service coverage. 

How Direct-to-Cell Technology Works  

Direct-to-cell technology enables satellites to function as cell towers from space. They interact directly with mobile devices using dedicated radio frequencies (specific segments of the radio spectrum that phones use for communication) and advanced networking protocols (techniques for orchestrating and transmitting data).  

SpaceX plans to use spectrum bands (radio frequency segments already assigned for communications) compatible with common smartphones. No new equipment will be needed, making the system easy to use. The technology will first offer basic services like text messaging and emergency communication. SpaceX will later expand these offerings to include voice and data services.  

Addressing Coverage Gaps in the United States  

The case aims to resolve existing coverage gaps that impact all regions of the United States. The current cellular network system does not provide reliable service across extensive areas. The existing coverage system does not meet the needs of rural and remote areas. 

Direct-to-cell satellite services could bridge these gaps without costly infrastructure. The emergency situation requires greater coverage because responders need reliable communication systems to protect themselves. Satellite connections will enhance access where service is minimal.  

Integration with Existing Mobile Networks  

SpaceX partners with telecom networks instead of replacing them. Users access mobile services via direct-to-cell signals, even outside terrestrial coverage.  

Mobile carriers and regulatory authorities must work together to create rules governing spectrum allocation and equipment interoperability. Research shows that telecom provider partnerships will be essential for achieving broad usage of this technology.  

Engineers must establish network integration processes enabling legacy systems to interoperate with new devices while ensuring reliability. The communications network combines satellite and cellular technology for greater dependability and flexibility.  

Regulatory and Licensing Considerations  

The process of obtaining a direct-to-cell license for market entry establishes essential requirements. The system must prove its regulatory compliance while it protects its ongoing business operations.  

US government agencies that oversee spectrum management and telecommunications regulations conduct a comprehensive approval process that evaluates new technology against essential requirements for reliable communication systems.  

SpaceX submitted its application to demonstrate its intention to increase service availability, but the actual service start date will depend on regulatory decisions.  

Competitive Landscape and Industry Impact  

SpaceX is currently developing direct-to-cell connectivity technology, while other companies pursue similar research. Competition among companies will drive rapid technological advancements.  

Satellite providers will enter mobile connectivity markets, leading to operational changes and new industry partnerships across the entire telecommunications sector. The telecommunications sector will undergo major changes as a result of this process.  

Telecom operators will gain better coverage through satellite systems but must tackle three specific operational challenges: network integration, spectrum management, and changes to revenue streams. Businesses must adapt their strategies to market conditions to remain competitive while creating value for their stakeholders. 

Implications for Consumers and Businesses  

The direct-to-cell system, which launched in 2023, allows customers to access better communication services during phone calls in regions that experience poor network connections. The system operates as an emergency communication system. 

The agricultural sector, logistics sector, and energy sector will benefit from better connectivity, which will enhance their operational capabilities. Organizations require strong communication systems for their daily operations. The satellite systems deliver vital support, which enables their fundamental operations to function correctly. 

The technology enables new applications, such as Internet of Things (IoT) deployments and remote monitoring systems that require continuous network connectivity. IoT refers to networks of physical devices, such as sensors or machines, that communicate and share data. 

Challenges and Technical Limitations  

Direct-to-cell technology offers benefits to users, but it must address three challenges: latency, signal degradation, and limited satellite communication capacity. Developers need to create comprehensive testing procedures to assess system performance under different environmental conditions and operational scenarios. The system needs to prove its ability to handle increased operational requirements without losing performance quality. Engineers need to develop methods that will enable current systems to work together with new technology while preserving network security. 

A New Phase for Satellite Connectivity  

SpaceX’s direct-to-cell license application marks a major advance in satellite communication. The company is developing ways for satellites to connect directly with mobile devices. The technology has strong potential but depends on regulatory approval and resolution of technical issues. It could change how communications reach areas with unreliable service. Upcoming project developments will influence how companies build connectivity services in the US. These developments will also affect other countries. The outcome could redefine expectations for universal mobile coverage in the coming years.

Source: xAI joins SpaceX to Accelerate Humanity’s Future 

US Energy Department Deploys AI System to Automate Power Grid Operations

The American electrical grid is at a turning point. More renewable energy sources make manual supervision less effective. To manage this complexity, the U.S. Energy Department is now using an AI system to automate grid operations. This marks a shift away from reactive methods. The move is part of the Grid Modernization Initiative, aiming for a self-healing, active grid that makes decisions in milliseconds.  

For power systems, engineers, and policy stakeholders, this is more than a software update. It is a major change in grid stability. By 2026, the rapid growth of distributed energy resources such as home solar, EV charging, and battery storage creates multidirectional electricity flows, making traditional centralized control less effective.  

The Architecture Of Self-Driving Load Balancing 

At the center of the new Department of Energy (DOE) system is a detailed digital model of the North American power grid. The AI uses a decentralized network of edge-computing core nodes, small local computers that process information close to its source, to process data from millions of phasor measurement units (PMUs), devices that monitor electrical flow, and smart meters in real time. Unlike older supervisory control and data acquisition (SCADA) systems, which can have 5-minute delays, the new framework uses neural state prediction to anticipate electrical changes and predict voltage changes before they cause problems.  

The automation system uses a constrained reinforcement learning model. This lets the AI balance frequency regulation and generator ramping while staying within the transmission limits. For example, if clouds reduce solar power in the south-west or a cold front increases heating demand in the north-east, the AI acts autonomously. It shifts flexible nodes and activates virtual power plants to keep the frequency steady at 60Hz.  

Enhancing Protection From Cyber and Physical Threats 

One main reason for this deployment is the growing number of threats. The American power grid is a major target for both cyberattacks and severe weather driven by climate change. The DOE’s AI system uses a specialized anomaly-detection engine (software) that identifies unusual patterns to distinguish between real equipment failures and digital attacks.  

The AI monitors electromagnetic signals from substation equipment. It looks for signs of compromised circuit breakers or unauthorized relay commands. If an attack is confirmed, the system isolates the affected grid section. Power remains for critical facilities like hospitals and water plants, ensuring the grid stays protected.  

The Role Of Sovereign AI And Domestic Silicon 

To support energy independence, the Energy Department requires that both hardware and AI model weights be produced in the US. The AI runs on high-performance computing with specialized accelerators for extreme temperatures. This sovereign AI approach avoids supply chain risks and keeps grid control in domestic hands.  

The system also uses explainable AI protocols, which are methods that show how AI makes decisions for every automated action, such as shutting down a transformer to prevent a wildfire or redirecting power during a heatwave. The system creates a logic trace, a record of the AI’s reasoning. This lets engineers review the AI’s decisions later to ensure its actions align with public safety and long-term goals.  

Integrating the Hydrogen and EV Ecosystems 

As the US works toward its 2050 net-zero goals, the power grid must coordinate with the growing hydrogen sector and the rise of electric vehicles. The AI system acts as an active market operator, managing the two-way flow of energy between the grid and EV batteries, including vehicle-to-grid (V2G).  

When there is surplus wind power at night, AI can automatically lower electricity prices for hydrogen plants and EV charging stations, absorbing excess energy. In the evening, the system draws small amounts from many car batteries to help meet demand until solar returns. This coordination makes the grid a flexible battery, maximizing every green electron.  

Addressing the Human Factor in the Control Room 

This deployment does not mean human grid operators are no longer needed. Instead, their roles are changing as routine tasks are automated, such as frequency and voltage control. The AI enables experts to focus on strategic planning and long-term maintenance. The DOE has started a training program to help current operators become grid architects who can work with the AI to design the next generation of resilient power systems.  

The Life Of A Thinking Continent 

As these digital systems connect across the country, the grid is becoming more intelligent and responsive. It is no longer just wires and transformers. The system now adapts to daily needs. The grid can respond to demand swings like a city turning off its lights or an industrial center starting up at night. In the future, power lines may become the nervous system of smart infrastructure, keeping homes powered and safe.

Source:  Gridmind powering the control room of the future with ai agents

IBM Partners With Eleven Labs to Add Natural Voice to Enterprise AI Systems

ElevenLabs and IBM announced a collaboration to bring ElevenLabs Text-to-Speech and Speech-to-Text (STT) technology to IBM WatsonX Orchestrate. This partnership equips clients with tools for natural language interactions that enhance AI-driven experiences while meeting enterprise security and scalability needs.  

Natural voice is key for customers and employees interacting with AI, but robotic voices, rigid flows, and long waits hurt the experience. ElevenLabs’ advanced TTS enables secure, natural-sounding voice agents in 70 languages that convey human emotion.  

AI agents are becoming central to everyday work, and voice is where AI either earns trust or loses it, said Mati Staniszewski, co‑founder at ElevenLabs. Together with IBM, we are helping organizations replace robotic interactions with AI agents that people actually want to talk to, built with the security and compliance controls that enterprises require.  

This integration enables organizations to use high-quality, multilingual AI voice agents, enhancing experiences across sectors such as government, banking, insurance, healthcare, and utilities in customer service and internal operations.  

IBM Watsonx Orchestrate is the platform for building, deploying, managing, and overseeing AI agents to automate workflows. It connects with existing systems, models, or automation tools, enabling agents to collaborate and providing a solid foundation for enterprise AI clients. Clients get access to ElevenLabs, high-quality speech, and a library of 10,000-plus voices, plus protections including PCI compliance, zero retention mode for HIPAA compliance, and data residency. This ensures consistency, security, and reliability for large deployments and high-volume global interactions.  

We are giving AI agents a voice in the enterprise. Clients are increasingly deploying agentic AI with customer and employee interactions. They want these experiences to be intuitive, responsive, and accessible, said Nick Holder, Vice President, AI Technology Partnerships at IBM. IBM’s open-ecosystem approach gives clients the flexibility to choose the models and tools that best fit their business. Our integration of ElevenLabs with WatsonX Orchestrate shows this. It enables enterprises to deploy AI agents that sound natural, scale globally, and address security, reliability, and governance.  

ElevenLabs and IBM plan to keep working together to help businesses move from text-only agents to voice-first, human-centered AI experiences that can grow with their needs. To discover how your organization can benefit from these advancements, explore IBM WatsonX Orchestrate with ElevenLabs today.  

Statements regarding 11 Labs and IBM’s future direction and aims are subject to change or withdrawal without notice and represent only goals and objectives.  

About ElevenLabs 

Eleven Labs is an AI research and product company changing how we communicate with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses across three main platforms. ElevenAgents enables businesses to deliver flawless intelligent customer experiences through integrations, testing, monitoring, and the reliability needed to deploy voice and chat agents at scale. ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. ElevenAPI gives developers access to our leading AI audio core models.  

About IBM 

IBM is a leading provider of global hybrid cloud, AI, and consulting expertise. We help clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs, and gain the advantage in their industries. Thousands of governments and corporate entities in critical infrastructure areas such as financial services, telecommunications, and healthcare rely on IBM’s hybrid cloud platform and Red Hat OpenShift to effect their digital transformations quickly, effectively, and securely. IBM’s breakthrough innovations in AI, quantum computing, industry-specific cloud solutions, and consulting deliver open and flexible options to our clients. All of this is backed by IBM’s strong, long-standing devotion to trust, transparency, responsibility, equity, and service. Visit www.ibm.com for more information. 

Source: Enterprise AI Finds its Voice: ElevenLabs and IBM Bring Premium Voice Capabilities to Agentic AI 

Apple Opens US Orders for AirPods Max 2 With On-Device AI Features

Apple today announced AirPods Max 2. These headphones deliver clearer calls, richer sound, and industry-leading noise cancellation, providing users with more immersive listening and recording experiences. With the H2 chip, AirPods Max 2 introduces adaptive audio for seamless transitions between environments, live translation for real-time communication, and a studio-quality recording feature, making them especially valuable for podcasters, musicians, and content creators.   

Be among the first to experience AirPods Max 2 by ordering yours starting March 25 at midnight in starlight, orange, purple, or blue. Act now to ensure early access next month.  

With the H2 chip, AirPods Max are upgraded. ANC is 1.5 times more effective, said Eric Treski, Apple’s director of audio product marketing. Sound quality is clean and detailed, and personalized spatial audio enhances the experience.  

Active Noise Cancellation Gets Even Better 

With H2 and new computational audio, AirPods Max 2 cut external noise by up to 1.5 times more than before. This lets users enjoy clearer music, conversations, and focus, even in busy airports or on trains.  

A new digital signal processing algorithm, organized for H2 and the AirPods Max microphone array, delivers more natural transparency, helping users remain aware of their surroundings.  

Highest Fidelity Listening Experience 

AirPods Max 2’s high-dynamic-range amplifier delivers cleaner, more detailed sound, letting users hear music, movies, and games with pinpoint instrument location and balanced bass, mids, and highs.   

AirPods Max 2 supports lossless audio and can be used professionally, with personalized spatial audio available via USB‑C.  

Reduced wireless audio latency ensures games feel responsive and immersive, giving users a competitive edge and smoother experience on iOS, macOS, and iPadOS devices.  

Intelligent features come to AirPods Max. 

The H2 chip brings new features that make AirPods Max 2 smarter and more helpful: users get instant audio optimization, clearer calls, and easier communication across languages for a seamless daily experience.  

  • Adaptive audio automatically adjusts ANC and transparency levels based on the environment to optimize the audio experience.  
  • Conversation awareness lowers content volume and reduces background noise when the user begins speaking to someone.  
  • Live translation is powered by Apple Intelligence. It enables users to communicate across languages in person.  
  • Voice isolation uses advanced computational audio with H2. It focuses on users’ voices during calls and blocks ambient noise.  
  • With the camera remote, users can take photos or start and stop video recording from a distance by pressing the Digital Crown on their Apple Watch. This feature works with the Camera app or compatible third-party apps on iPhone. It also enables creators to record content with higher-quality audio and a more natural vocal texture.  
  • Loud sound detection helps prevent exposure to loud environmental noise while preserving the audio’s sound signature.  
  • Personalized volume automatically fine-tunes the listening experience over time based on user preferences.  
  • Siri interactions enable users to respond to Siri announcements by nodding their head for yes or gently shaking their head for no.  

AirPods, Max 2, And The Environment 

Apple 2030 is the company’s plan to achieve carbon neutrality across its entire footprint by the end of the decade, reducing product emissions from materials, electricity, and transportation. AirPods Max 2 use 100% recycled rare-earth elements in all magnets, 100% recycled polyester in the ear cushions, and 100% recycled gold plating and tin solder on all Apple-designed printed circuit boards. The paper packaging is entirely fiber-based and can be easily recycled.

Source: Apple introduces AirPods Max 2 

Intel Launches Core Ultra vPro Chips Built on 18A for Enterprise AI PCs

News Highlights 

  • The Intel Core Ultra Series 3 for business PCs, built on Intel 18A, delivers advanced performance and efficiency for commercial computers, powering everything from lightweight business laptops to powerful workstations.  
  • The Intel vPro platform provides advanced security, AI-powered management, and easy fleet service activation used by over 1,300 commercial customers worldwide.  
  • The new Intel Arc Pro B-series GPUs provide cost-effective, high-performance graphics solutions for content creation, engineering, and AI applications.  
  • Intel Xeon 600 workstation processors are now available, offering scalable performance for professional and technical computing.  

New York, March 25, 2026 Intel has introduced its most advanced commercial client portfolio designed for all types of professionals and supporting over 125 different designs: the new Intel Core Ultra Series 3 vPro offers users efficient performance, strong security, and easy device management for IT teams. Intel also announced its high-end Intel Arc Pro B70 and B65 graphics cards, as well as the retail launch of Intel Xeon 600 workstation processors. These products are built to deliver high computing power and scalability for professionals, solving problems across any industry.  

The Intel Core Ultra Series 3, the first commercial PC platform on 18A, offers next-gen performance and built-in AI acceleration with Intel vPro. Organizations gain easy deployment, proactive, effective security, and smarter fleet operations.  

From laptops to workstations, this is Intel’s most expansive commercial portfolio, enabling IT and business leaders with the performance, efficiency, security, manageability, and AI capabilities needed for the next era of work. David Feng, vice president of Client Computing Group and GM of PC segments.  

Intel Core Ultra Series 3 Processors Built for Business 

The Intel Core Ultra Series 3 offers strong performance, better power efficiency for longer battery life, new graphics, and AI acceleration for business computers.  

Compared to 4-year-old systems, the average PC refresh business users can expect.  

  • Over 30 percent faster single- and multi-thread performance.  
  • Up to 30 percent higher productivity compared to the average 4‑year‑old business Pc’s.  
  • Up to 80 percent better graphics performance versus average 4-year-old business Pc’s.  
  • Up to 4x AI performance versus average 4-year-old business PCs.  

Together, these improvements help users work more efficiently, collaborate more effectively, and use AI-powered workflows across the company.  

Intel vPro: The Foundation of Modern Managed PCs 

Intel vPro continues to be a leader in business security and fleet management, offering built-in security, easy management, and trustworthy performance.  

New Capabilities Include 

  • The Intel vPro certification program boosts application and accessory performance by working closely with software vendors and partners. This reduces CPU usage, improves power efficiency, and reduces background activity. Early results show up to 59% less CPU use, 56% better power efficiency, and 74% less background activity.  
  • Intel vPro Intelligence with Device IQ uses AI-powered analytics to find, diagnose, and fix issues before they escalate. This helps reduce downtime and the need for IT support. Integration with digital experience (DEX) platforms is planned for the second half of 2026.  
  • Intel vPro Fleet Services makes out-of-band management and disaster recovery easier with the first fully managed turnkey SaaS-based activation. It is also the first silicon partner to work with Microsoft Intune, so there is no need for extra infrastructure. IT teams can quickly activate Intel vPro management from the Intune admin center, speeding up deployment and simplifying operations. Over 1,300 commercial customers worldwide started using the service last quarter.  
  • Intel vPro Security Enhancements now include Intel Total Storage Encryption for Microsoft BitLocker and AI-based Threat Detection with Intel Threat Detection Technology (DTECT). This is the only silicon that can detect the most advanced malware threats in real time.  

Intel Arc Pro Graphics Built for Creators and AI Developers 

The Intel Arc Pro B70 and B65 discrete GPUs provide high-performance, value-driven professional graphics for advanced content creation, engineering tasks, and demanding AI workloads.  

Built on the Xe2 architecture, these GPUs feature up to 32 Xe cores and 32 GB of VRAM and are optimized for multi-user AI workloads.  

  • They are optimized to handle AI workloads involving multiple users and agents.  
  • They offer a strong balance of price and performance for AI inference, whether employed in workstations or edge devices.  

Performance Benefits Include 

  • Up to 2.2x larger context windows with the Intel Arch Pro B70 compared to similar competitor graphics cards.  
  • Up to 6.2x faster responses in multi-agent/multi-user workloads with the Intel Arc Pro B70 compared to similar competitor graphics cards.  
  • Up to 2x tokens per dollar performance with the Intel Arc Pro B70 versus the competition.  

Intel Arc Pro has evolved from powering creative workflows to enabling AI builders at scale. With the Intel Arc Pro B70 and B65, we are providing high-performance workstation graphics products and AI inference at exceptional value. Anil Nanduri, Vice President, AI Products and GTM, Intel Data Center Group.  

Availability 

These commercial pieces powered by Intel Core Ultra Series 3 and Intel vPro will be available starting March 31, 2026.  

The Intel Arc Pro B70 discrete GPU will be available starting March 25, 2026, both as an Intel-branded card model and through Intel AIB partner cards from ARKN, ASRock, Gunnir, Maxsun, Sun, and Sparkle. Intel-branded Arc Pro B70 discrete GPUs will have a suggested starting price of $949. Pricing for Intel Arc Pro B70 discrete GPUs from AIB partners will vary based on final model configurations.  

Intel Arc Pro B65 discrete GPUs will be available starting in mid-April 2026 through Intel’s AIB partner network with a wide range of form factors. Intel Arc Pro B65 pricing will vary based on final model configurations.  

Intel Xeon 600 processors for client workstations will be available starting March 25, 2026. Suggested component pricing ranges from $499 to $7,699, and end-user system pricing depends on the final component configuration.

Source:  Intel Core Ultra Series 3 with Intel vPro Powers Next Generation of Commercial PCs Built on Intel 18A

CrowdStrike and AWS Name, AI Startup Winner in 2026 Security Accelerator

CrowdStrike announced at RSE 2026 that Jazz won the third annual Cybersecurity Startup Accelerator held in partnership with Amazon Web Services (AWS) and NVIDIA. Through the NVIDIA Inception program, JAIS was recognized for its novel AI-powered data loss prevention (DLP) approach and its promise to solve key security challenges for today’s enterprises.  

Nearly 1,000 startups from around the world applied to the 2026 accelerator. This interest shows a growing demand for AI-powered cloud security. Thirty-five startups joined the eight-week, equity-free program. They collaborated with experts from CrowdStrike, AWS, NVIDIA, and others to transform ideas into enterprise-ready security platforms and launch their businesses.  

On March 24, 2026, at the RSAC-2026 conference in San Francisco, Jazz was named the winner of the Cybersecurity Startup Accelerator. The choice was made from six finalists. The judges included George Kurtz, CEO and founder of CrowdStrike; CJ Moses, Chief Information and Security Officer (CISO) at Amazon; Richardson, senior director of Agentic AI and cybersecurity engineering at NVIDIA; and special guest judge Robert Herjavec, entrepreneur and Shark Tank judge.  

Above Security was named the runner-up for its use of AI agents, software that uses artificial intelligence to perform tasks autonomously to manage insider risk and security threats within an organization, and to reduce traditional alerts with detailed investigative reports.  

The accelerator highlights a trend seen at both the RSA Conference, a major cybersecurity event, and NVIDIA GTC 2026, NVIDIA’s AI and graphics conference. Hardware companies, enterprise service providers, and new founders are building on a shared security platform. This platform offers technology and infrastructure designed for collaborative deployment and protection.  

We are incredibly grateful to be the winner of the CrowdStrike, AWS, and NVIDIA cybersecurity startup accelerator. Said Ido Livneh, co-founder and CEO at JAIS: “DLP has been broken for decades by rule writing, alert floods, and no real answers. So, we rebuilt it from the ground up using first principles thinking as an AI-native system to truly understand how data moves through a business.” The advice and assistance we received through the accelerator were essential to sharpening the product and validating it against real-world enterprise demands as we scale.  

The path to becoming a defining cybersecurity company looks nothing like it did just three years ago, said Daniel Barnard, chief business officer at CrowdStrike. Today’s promising founders are building on leading platforms from the start. Together with AWS and N media, this accelerator supports early innovation. JAWS stood out for its context-aware, AI-native DLP approach, leveraging Melody and Context Vault to provide clear, actionable answers at scale and exemplify leadership in the new cybersecurity era.  

Security innovation only matters if it performs within real cloud environments, said CJ Moses, CISO of Integrated Security at Amazon. This accelerator connects founders directly with the infrastructure, operational expectations, and scale enterprises demand. What sets Jazz apart is its ability to investigate signals with full business context and surface meaningful incidents with minimal analyst overhead, meeting the standards modern security teams expect.  

The shift to agentic AI is transforming cybersecurity, requiring autonomous systems that can perceive, reason, and act against increasingly sophisticated threats, said Bartley Richardson, senior director of agentic AI and cybersecurity engineering at NVIDIA. The accelerator equips the next generation of security platforms with high-performance compute and foundational frameworks needed for secure, scalable AI. Judge distinguished itself by its agentic investigator, Melody. It can analyze multidimensional context across data, systems, people, and businesses. This helps drive precise, in-context prevention decisions and distills millions of events into a small set of usable insights.  

For more information, visit the program’s website. 

Source: CrowdStrike and AWS Announce Jazz as the Winner of the 2026 Cybersecurity Startup Accelerator, Supported by NVIDIA Inception 

Microsoft Defender Adds Identity Risk Scoring for AI-Driven Security Decisions

Next week, the RSAC conference celebrates its 35th anniversary as the security community’s pivotal event for meeting new challenges and discovering opportunities to make the world safer. As we reach this milestone, Agentic AI is quickly changing industries. 

Many customers are becoming frontier firms focusing on intelligence and trust and using agents to help people reach their goals and rethink how they do business. Our recent research shows that 80% of Fortune 500 companies are already using agents.  

At the same time, as these innovations expand, we are also seeing a rise in AI-powered attacks in which agents can act as double agents. CIOs, CISOs, and other security leaders now face important questions. How can they monitor, manage, and secure agents? How do they protect their core systems in this new era? And how can agentic AI help defend their organizations against both old and new threats?  

To address these challenges, the solution begins with trust, and security is the foundation of that trust. In this new era of agentic AI, security needs to be built into every part of the AI system. It should work in the background and on its own. Like the AI, it protects. This is our vision: making security the core of the AI stack.  

At RSAC 2026, we are bringing this vision to life with new tools that help organizations secure agents, protect core systems, and defend themselves with support from agents and experts. Microsoft Security processes over 100 trillion signals daily, protecting 1.6 million customers, 1 billion identities, and 24 billion Co-Pilot interactions. Keep reading to see how we can help you secure agentic AI.  

Secure Agents 

Agent 365, available May 1, centralizes agent management for IT, security, and business teams using existing infrastructure. It includes the new Defender Era and Purview features for secure access, data protection, and threat defense.  

Agent 365 is part of Microsoft 365 E7, the Frontier Suite, which also includes Copilot, Intra-Suite, and E5, offering advanced air security features for full protection.  

Secure Your Foundations 

In addition to securing agents, AI must also be protected at every level. Securing agent AI requires safeguarding its systems and the people who build and use it. At RSAC 2026, we are launching new features to help you spot organizational risks, secure identities and adaptive access controls, protect sensitive data in AI workflows, and defend against evolving threats.  

Gain Visibility Into Risks Across Your Enterprise 

As AI adoption accelerates, so does the need for comprehensive continuous visibility into AI risks across your environment. As more organizations adopt AI, it becomes even more important to have clear, ongoing visibility into AI risks across your environment—from agents to AI apps and services. We are meeting this need with new tools that show you where AI is being used, how it is used, and where your risks might be increasing. These new features are now generally available.  

  • Entra Internet Access Shadow AI Detection identifies unknown and unmanaged AI apps through network analysis. Available March 31.  
  • Enhanced Intune App Inventory provides rich visibility into the apps installed on your devices, including AI-enabled apps to support targeted remediation of high-risk software, generally available in May.  

Secure Identities With Continuous Adaptive Access 

Identity is the foundation of modern security, often the primary target in any system, and the first line of defense against threats. With Microsoft Entra, you can secure access and strengthen identity protection using new features that help you improve your identity setup, manage tenants better, update authentication methods, and make smarter access decisions.  

  • Entra backup and recovery strengthens resilience by automatically backing up Entra directory objects, enabling rapid recovery in the event of accidental data deletion or unauthorized changes. Now available in preview.  
  • Entra-Tenant Governance discovers and manages shadow tenants with consistent policies in preview.  
  • Entra passkey capabilities now include synced passkeys and other passkey profiles, enabling maximum flexibility for end users and making it easy to move between devices, while organizations seeking maximum control can still use device-bound passkeys. In addition, intra-passkeys are now natively integrated into Windows Hello, making phishing-resistant passkey authentication even more seamless across Windows services. Synced passkeys and passkey profiles are generally available. Passkey integration in Windows Hello is in preview.  
  • Entra External Multi-Factor Authentication allows organizations to connect external MFA providers directly to Microsoft Entra, enabling them to leverage pre-existing MFA investments or use highly specialized MFA methods that are now generally available.  
  • Entra Adaptive Risk Remediation helps users securely regain access without help desk friction by automatically self-remediating across authentication methods, adapting to where they are in their modern authentication journey. It will be generally available in April.  
  • Unified Identity Security offers complete protection across your identity systems, control center, and threat identification and response, all designed for quick action and instant decisions. The new identity security dashboard in Microsoft Defender displays the most important data for both human and non-human identities, helping you respond faster. The new Identity Risk Score combines risk signals from different accounts to provide a comprehensive view of user risk, supporting real-time access decisions and security investigations. Now available in preview.  

Secure Sensitive Data Across AI Workflows 

As AI becomes part of daily work, sensitive data now moves quickly through prompts, responses, and grounding flows, sometimes outpacing existing policies. Security teams need to see how AI uses data and be able to prevent oversharing or leaks. 

Microsoft now brings data security into the AI control pane, giving organizations a clear view of risks, real-time enforcement, and the confidence to use AI responsibly across the business. New Microsoft Purview features include.  

  • Expanded Purview Data Loss Prevention for Microsoft 365 Copilot helps block sensitive information such as PII, credit card numbers, and custom data types from being processed or used for web scraping. Generally available March 31.  
  • Purview embedded in the Copilot control system provides a unified view of AI-related data risk directly in the Microsoft 365 admin center. Generally available in April.  
  • Purview customizable data security reports enable tailored reporting and drilldowns to prioritized data risks. available in preview on March 31.  

Defend Against Threats Across Endpoints, Cloud, and AI Services 

Security teams need round-the-clock protection that can stop threats early and automatically contain them. Microsoft is expanding predictive shielding to limit risks and reduce exposure, improving container security, and adding network-level protection against harmful AI prompts.  

  • Entra, internet access, prompt injection protection helps block malicious AI prompts across apps and agents, enforcing universal network-level policies. Generally available March 31.  
  • Enhanced Defender for cloud container security includes binary drift and anti-malware protection to close gaps that attackers exploit in container enforcements, now available in preview.  
  • Defender for Cloud Posture Management adds broader coverage and supports Amazon Web Services and Google Cloud Platform, delivering security recommendations and compliance insights for newly discovered resources, now available in preview in April.  
  • Defender Predictive Shielding automatically adjusts identity and access policies during active attacks. Reducing Exposure and Limiting Impact is now available in preview.  

Defend With Agents And Experts 

To protect organizations in this new era, a defense approach designed for agents is needed. This includes deploying a defense platform and security agents embedded in daily workflows, all supported by expert knowledge and robust security services when required.  

Agents Are Built Into the Security Workflow 

Security teams work best when they get help, right where and when they need it. As alerts arise and investigations span identities, data, devices, and cloud networks, AI-powered tools should directly support defenders with Security Copilot. 

Now part of Microsoft 365 E5 and E7, we are giving defenders agents that are built into daily security and IT tasks. These agents help speed up responses and reduce manual work, so teams can focus on what matters most.  

New Agents Available Now Include 

  • Security Analyst Agent in Microsoft Defender helps accelerate threat investigations by providing contextual analysis and guided workflows. Available in preview on March 26th.  
  • The security alert triage agent in Microsoft Defender has the capabilities of the phishing triage agent and extends to cloud and identity, autonomously analyzing, classifying, prioritizing, and resolving repetitive low-value alerts at scale. Available in preview in April.   
  • Conditional Access Optimization Agent in Microsoft Intra Enhancements: Add context-aware recommendations, deeper analysis, and staged rollout to strengthen identity security. Agent is generally available, and enhancements are now available in preview.  
  • Data Security Posture Agent enhancement in Microsoft Purview includes a credential-scanning capability that can proactively detect credential exposure in your data. Now available in preview.  
  • Data Security, Tri-Age Agent Enhancements in Microsoft Purview include an advanced AI reasoning layer and improved interpretation of custom sensitive information types (SITs) to enhance agent outputs during alert triage. The agent is generally available, and enhancements are available in preview from March 31.  
  • Over 15 part-time built agents extend Security Copilot with additional capabilities, all available in the Security Store.  

Scale With an Agentic Defense Platform 

To help defenders and agents work together more smoothly and intelligently, Microsoft is expanding Sentinel as a defense platform. This update delivers context, automates workflows from start to finish, and standardizes access, governance, and deployment across security tools.  

  • Sentinel Data Federation, powered by Microsoft Fabric, investigates external security data in Databricks, Microsoft Fabric, Azure, and Azure Data Lake Storage while preserving governance. Now available in preview.  
  • The Sentinel Playbook Generator with natural-language orchestration helps accelerate investigations and automate sophisticated workflows. Now available in preview.  
  • Sentinel, Granule, Delegated Administrator privileges, and unified role-centric access control enable secure and scalable management for partners and enterprise customers, with cross-tenant collaboration now available in preview.  
  • Security store embedded in Purview and Entra makes it easier to discover and deploy agents directly within existing security experiences. Generally available March 31.  
  • Sentinel custom graphs powered by Microsoft Fabric enable views unique to your organization of relationships across your environment. Now available in preview.  
  • The Sentinel Model Context Protocol (MCP) Entity Analyzer helps automate faster with natural language and harnesses the flexibility of code to accelerate responses generally available in April.  

Strengthen with Experts 

Even the most experienced security teams sometimes need extra support, especially during complex attacks or investigations. The Microsoft Defender Experts suite offers expert-led services, including technical advice, managed external detection and response, MXDR, and full incident response. These services help you defend against advanced threats, build sustained resilience, and modernize your security operations with confidence.  

Apply Zero Trust for AI 

Zero Trust centers on three ideas: verify consistently, use the least privilege, and assume breaches as AI permeates the environment from models to agents. These principles are critical. At RSAC 2026, we are broadening our Zero Trust architecture to cover the full AI lifecycle. Our updated reference architecture workshop, assessment tools, and new articles make this practical for you. 

Source: Secure agentic AI end-to-end