Apple is preparing to make a significant change to its in-car technology ecosystem. According to recent reports, the company plans to allow external, voice-controlled AI chatbots to operate within Apple CarPlay. This move marks a notable shift in Apple’s traditionally closed approach and signals a broader acceptance of third-party AI tools within its platforms.

Until now, Siri has been the only voice assistant available in CarPlay. Drivers could use Siri to make calls, send messages, get directions, or control music. However, with the rapid rise of advanced AI chatbots, Apple appears ready to expand what CarPlay can do.

What Exactly Is Changing in CarPlay

Apple’s upcoming update will allow third-party AI chatbot apps to work inside CarPlay. This means users could interact with AI assistants such as ChatGPT, Google Gemini, or other AI-powered apps using voice commands while driving.

However, Apple is not replacing Siri. Instead, Siri will remain the default assistant. Users will not be able to change the wake word or system button to activate a third-party chatbot. Instead, drivers will need to open the AI app within CarPlay to begin interacting with it.

This approach allows Apple to maintain control over the core experience while still giving users access to more advanced AI capabilities.

Why This Move Matters

Apple’s decision is important for several reasons. First, it reflects a growing recognition that AI assistants have evolved beyond traditional voice commands. Many modern AI chatbots offer more natural conversations, better contextual understanding, and more flexible responses than legacy assistants.

Second, this change suggests Apple is responding to competitive pressure. Automakers and tech companies are rapidly integrating AI into vehicles. Google, for example, already offers deeper AI integrations through Android Automotive. By opening CarPlay to external AI chatbots, Apple ensures it remains relevant in the evolving in-car technology landscape.

Finally, this update could significantly improve the driving experience. Drivers may soon be able to ask more complex questions, summarize messages, get contextual recommendations, or even draft responses more naturally, all without taking their hands off the wheel.

How Drivers Could Use AI Chatbots in CarPlay

Once supported, external AI chatbots could enable a wide range of use cases inside the car. For example, drivers might ask an AI assistant to summarize news, explain unfamiliar topics, or help plan a trip more intelligently.

In addition, AI chatbots could assist with productivity. A driver could dictate notes, get help drafting messages, or ask follow-up questions during navigation. Because these tools are designed for conversation, interactions may feel more human and less command-based.

That said, Apple is expected to enforce strict safety and interface guidelines. This ensures that interactions remain voice-first and do not distract drivers with unnecessary visuals or complex inputs.

Siri Still Remains Central

Despite opening the door to third-party AI, Apple is not sidelining Siri. Siri will continue to handle core system tasks such as calls, navigation, and system-level controls.

This design choice allows Apple to preserve privacy, security, and consistency, which are central to its brand. External AI chatbots will likely be sandboxed within their own apps and limited to specific use cases.

In effect, Apple is offering choice without relinquishing control. Users gain access to advanced AI features, while Apple retains oversight of the overall CarPlay experience.

Privacy and Security Considerations

Apple’s ecosystem is built around strong privacy standards, and this update will likely follow the same philosophy. Third-party AI apps in CarPlay will need to comply with Apple’s data protection rules and usage policies.

This is especially important because AI chatbots often rely on cloud processing. Apple will need to ensure that user data, voice recordings, and interactions are handled transparently and securely.

By controlling how these apps operate within CarPlay, Apple can limit potential risks while still enabling innovation.

What This Means for Developers and Automakers

For developers, this update opens new opportunities. AI companies can now design car-friendly AI experiences, optimized for voice interaction and real-time assistance.

Automakers also benefit. CarPlay is already widely adopted, and adding AI chatbot support enhances its appeal without requiring manufacturers to build their own AI systems from scratch.

As cars increasingly become software-driven platforms, these integrations could influence purchasing decisions, especially among tech-savvy consumers.

Part of Apple’s Broader AI Strategy

This move aligns with Apple’s broader AI roadmap. While Apple has traditionally taken a cautious approach to generative AI, recent updates suggest a shift toward selective openness.

Rather than competing directly with every AI provider, Apple appears willing to integrate best-in-class AI tools while maintaining its ecosystem’s core values. Allowing external AI chatbots in CarPlay fits neatly into this strategy.

It also hints at possible future integrations across other Apple platforms, such as iOS or macOS, where third-party AI tools could coexist alongside Apple’s own solutions.

When Will This Feature Launch

Apple has not officially announced a release date yet. However, reports suggest the feature may arrive in a future CarPlay update, possibly alongside upcoming iOS releases.

As with most Apple features, availability may depend on region, vehicle compatibility, and app developer readiness. More details are expected once Apple formally introduces the update.

Final Thoughts

Apple’s plan to allow external voice-controlled AI chatbots in CarPlay represents a meaningful evolution in its in-car experience. While Siri remains central, users will soon gain access to more powerful conversational AI tools that can enhance navigation, productivity, and everyday driving tasks.

By striking a balance between openness and control, Apple is adapting to the fast-changing AI landscape without compromising its core principles. For drivers, developers, and automakers alike, this update signals a smarter, more flexible future for in-car technology.

As AI continues to redefine how people interact with devices, Apple’s CarPlay update shows that even tightly controlled ecosystems can evolve, thoughtfully and strategically.

The post Apple CarPlay AI Chatbots Expand Voice AI appeared first on TechnologyXpertise.

NVIDIA named the platform after Vera Florence Cooper Rubin, a famous American astronomer. NVIDIA continues its tradition of honoring influential scientists. The Vera Rubin platform also shows the company’s vision for the future of AI computing infrastructure. Performance, efficiency, and integration are key to this vision.

NVIDIA’s Vision for the Next Phase of AI Computing

Artificial intelligence has moved beyond experimentation and into real-world deployment across industries. From generative AI and autonomous systems to scientific research and enterprise applications, the demand for faster and more efficient AI computing has grown exponentially. NVIDIA’s announcement at CES 2026 directly addresses this shift.

The Vera Rubin platform is not just another chip release. Instead, it represents a tightly integrated AI computing architecture designed to support massive AI workloads that traditional systems struggle to handle. NVIDIA is positioning Rubin as the successor to its Blackwell architecture, pushing boundaries in performance, scalability, and energy efficiency.

By focusing on an end-to-end approach, combining GPUs, CPUs, memory, and networking into a unified system, NVIDIA aims to simplify AI infrastructure while delivering unprecedented computing power.

What Is the Vera Rubin AI Computing Platform?

The Vera Rubin platform is NVIDIA’s next-generation AI computing architecture built specifically for large-scale artificial intelligence workloads. Unlike traditional standalone processors, NVIDIA designed Rubin as a co-designed system. All its components work together seamlessly.

At its core, the platform integrates:

• High-performance Rubin GPUs
• A custom Vera CPU
• Advanced memory technologies
• High-speed networking and interconnects

This design allows data to move more efficiently between components, reducing bottlenecks that often slow down AI training and inference. The result is faster model development, improved efficiency, and better scalability for enterprises and cloud providers.

NVIDIA emphasized that Rubin can handle the growing complexity of modern AI models, including those with trillions of parameters. This makes it particularly suitable for generative AI, large language models, and scientific simulations.

Product Details: A New Architecture Built for Scale

One of the most notable aspects of the Vera Rubin platform is its rack-scale design philosophy. Instead of focusing on individual chips, NVIDIA has designed Rubin to operate as part of large AI systems deployed in data centers.

NVIDIA expects the Rubin GPUs to deliver significant performance improvements over previous generations. They offer higher throughput while using less power per computation. This balance between power and efficiency is critical as AI workloads become more resource-intensive.

Additionally, the platform introduces next-generation memory technologies that allow AI models to access and process massive datasets more quickly. Faster memory access means reduced training times and more responsive AI applications, which is especially important for real-time and enterprise use cases.

Another key feature is the platform’s ability to support large-scale parallel processing. By allowing multiple GPUs and CPUs to work together as a unified system, Rubin enables AI developers to scale their workloads without redesigning their infrastructure.

Product Details: Integrated Design for Smarter AI Systems

Beyond raw performance, the Vera Rubin platform focuses heavily on integration and efficiency. NVIDIA has designed the system so that computing, memory, and networking components communicate with minimal latency. This tight integration improves overall system responsiveness and reduces energy waste.

The inclusion of the custom Vera CPU alongside Rubin GPUs allows for better workload management. While GPUs handle intensive AI computations, the CPU manages data orchestration and system tasks, ensuring smoother operation across the entire platform.

NVIDIA has also optimized the platform for advanced AI workloads such as training, inference, and simulation. This makes Rubin versatile enough to support industries ranging from healthcare and finance to climate research and autonomous vehicles.

By treating AI computing as a complete ecosystem rather than isolated components, NVIDIA is redefining how future AI infrastructure will be designed and deployed.

Why This Matters for the AI Industry

NVIDIA’s announcement comes at a time when AI adoption is accelerating across the globe. Enterprises are moving from pilot projects to full-scale deployments, and they need infrastructure that can keep up with growing demands.

The Vera Rubin platform addresses several critical challenges:

• Scalability – Designed for large data centers and AI supercomputers
• Efficiency – Improved performance per watt to reduce operational costs
• Flexibility – Suitable for training and inference across industries
• Future readiness – Built to support increasingly complex AI models

For cloud service providers and enterprises, this means faster innovation cycles and lower barriers to deploying advanced AI solutions. For researchers, it opens the door to tackling more complex problems in fields like physics, medicine, and climate science.

NVIDIA’s CES 2026 Moment

CES has long been a stage for transformative technology announcements, and NVIDIA’s unveiling of Vera Rubin was one of the most significant highlights of CES 2026. Jensen Huang’s keynote emphasized the company’s belief that AI computing will be foundational to nearly every industry in the coming years.

By introducing Rubin at CES, NVIDIA reinforced its leadership role in shaping the AI landscape. The announcement also sent a clear message to competitors: the future of AI computing lies in integrated, scalable platforms rather than standalone components.

The naming of the platform after Vera Rubin also reflects NVIDIA’s broader philosophy, combining scientific inspiration with technological innovation to drive progress.

Expected Launch Timeline and Availability

While the Vera Rubin platform has been officially announced, NVIDIA has clarified that production is nearing completion, with a broader rollout expected in the second half of 2026.

This timeline aligns with NVIDIA’s strategy of allowing developers, partners, and cloud providers time to prepare for deployment. Once launched, Rubin is expected to power next-generation AI data centers and supercomputing systems worldwide.

Early adoption is likely to come from hyperscale cloud providers, research institutions, and large enterprises that require cutting-edge AI computing infrastructure.

Conclusion:

NVIDIA’s announcement of the Vera Rubin platform at CES 2026 marks a defining moment in the evolution of AI computing. By moving beyond traditional chip design and focusing on a fully integrated AI computing platform, NVIDIA is addressing the real-world challenges of scale, efficiency, and performance. The platform is expected to launch in the second half of 2026 and is set to play a crucial role in powering the next wave of AI innovation.

The post NVIDIA’s Leap in AI Computing at CES 2026 appeared first on TechnologyXpertise.

A New Era for Foldables: What the TriFold Brings

The standout feature of Samsung’s new device is its innovative dual-hinge mechanism that allows the phone to unfold into a large, 10-inch display. When fully opened, it becomes substantially larger than any of Samsung’s previous foldable phones, offering a near-tablet experience without carrying a separate device.

When folded twice, it fits comfortably in the hand like a traditional smartphone. A single fold reveals a midsized panel suitable for typical tasks, while the complete unfolding provides full screen estate for multitasking, entertainment, productivity, and creative work. The design also ensures that the main flexible display is protected on the inside when the phone is fully folded, enhancing durability and portability.

Samsung has spent nearly a decade refining its foldable technology, and the TriFold is being positioned as the culmination of that engineering evolution.

Key Features and Enhancements

1. Larger, Versatile Display

The TriFold’s 10-inch folding display is its biggest draw. It supports multiple window layouts, drag-and-drop functionality, and more space for apps to run side-by-side, catering to users who need a flexible work-consumption setup.

2. Powerful Battery Setup

Samsung has incorporated its largest foldable battery to date. The battery is split across the three panels to maintain device balance and improve thermal efficiency. Fast-charging support ensures the phone reaches about half its capacity in roughly half an hour.

3. Premium Performance

The device is powered by a flagship-grade chipset, high-speed RAM, and enhanced cooling systems optimized for the expanded screen. Samsung has also improved the hinge materials and internal architecture to withstand repeated folding.

4. Refined Dual-Hinge Design

The new hinge system is designed to be slimmer, stronger, and more fluid. It allows the phone to fold in a “Z” shape and reduces the overall thickness when folded. Samsung claims the hinge is engineered to provide long-term reliability even with frequent folding.

Release Timeline and Market Rollout

Samsung plans to launch the Galaxy Z TriFold first in South Korea, with preorders beginning shortly, followed by the official sale on December 12, 2025.

After the domestic launch, the device will roll out to additional markets:

• China
• Singapore
• Taiwan
• United Arab Emirates

A U.S. release is expected in early 2026, marking Samsung’s global expansion strategy for this new category.

Why This Launch Matters

1. Samsung Raises the Innovation Bar

For years, foldables have largely been limited to two formats: book-style folds and clamshell-style flippers. The TriFold expands possibilities by introducing a triple-panel concept, turning one device into three functional modes. It demonstrates how mobile devices could evolve from simple smartphones into more adaptable, multi-purpose gadgets.

This marks the first time a major global smartphone manufacturer is putting a multi-folding experience into commercial production, a move that may push competitors to release their own multi-panel devices.

2. The Competitive Landscape Is Heating Up

The foldable market has grown quickly, with Chinese brands experimenting aggressively with new form factors. Some have already showcased tri-fold prototypes, signaling that Samsung’s entry arrives at a strategically important time. Meanwhile, Apple is widely rumored to be exploring foldable concepts, suggesting that competition will intensify in the next 12–24 months.

Samsung’s TriFold serves as both a product and a message: the company intends to remain the leader of the foldable segment even as rivals close in.

Challenges the TriFold Must Overcome

1. High Pricing

The TriFold’s price, equivalent to well over $2,000, targets a niche audience rather than mass users. While early adopters and tech enthusiasts may embrace it, the cost could limit widespread acceptance in the short term.

2. Durability Questions

Any first-generation product faces scrutiny, and a dual-hinge mechanism introduces more complexity. Despite Samsung’s confidence in its refined engineering, consumers and analysts will be watching closely to see how the device performs after months of use.

3. Limited Mass-Market Appeal

Foldables, despite growing buzz, still represent a small portion of global smartphone sales. Until prices drop and the technology matures further, devices like the TriFold may remain specialized flagship showcases instead of mainstream drivers.

4. Production and Supply Constraints

Manufacturing a tri-fold device at scale poses challenges, especially regarding yield, hinge precision, and flexible display quality. Experts suggest Samsung may initially keep production volumes conservative to monitor performance and demand.

User Experience: Who Will Benefit the Most?

1. Productivity-Focused Users

Professionals who work heavily on mobile devices, multitaskers, and users who rely on split-screen workflows may appreciate the larger display and versatility. The TriFold’s ability to transform into a mini-tablet makes it appealing for presentations, content creation, and on-the-go productivity.

2. Entertainment & Creative Consumers

The larger screen is ideal for:

• watching movies
• reading
• gaming
• sketching or digital drawing
• editing media

It essentially becomes a compact entertainment device without carrying a full-size tablet.

3. Tech Enthusiasts and Trendsetters

As with any flagship innovation, early adopters and fans of cutting-edge tech will be drawn to the TriFold’s unique design and engineering.

Impact on the Smartphone Industry

The Galaxy Z TriFold could influence the direction of future mobile devices in several ways:

• Encourage brands to invest more in multi-fold formats.
• Push tablet-smartphone hybrids into the mainstream.
• Trigger price competition once other manufacturers follow suit.
• Accelerate user interest in flexible display technology.

If successful, the TriFold may help establish new device categories and change expectations about what a smartphone should be.

Even if it remains niche, its arrival marks a significant moment: Samsung has demonstrated that multi-fold technology is no longer just a concept, it is ready for real-world use.

Conclusion

Samsung’s Galaxy Z TriFold marks a bold step forward in foldable innovation. With its triple-panel design, expanded display, enhanced battery, and refined hinges, the device pushes foldable technology into new territory. Though priced for a selective market and still facing durability and scaling challenges, the TriFold stands as a major milestone for Samsung and the broader industry.

It may not become the everyday device for most users just yet, but it undeniably sets the stage for the next evolution of mobile devices, where phones, tablets, and future hybrid gadgets merge into transformative, shape-shifting designs.

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Which of the following commands would your current system fail to execute smoothly?

A. “Hey Google, turn on the living room light.”

B. “Hey Google, play my ‘Focus’ playlist on Spotify.”

C. “Hey Google, turn off all the lights except the office, and lock the front door.”

D. “Hey Google, based on the ingredients in my fridge, suggest a vegetarian 3-course meal and add what I’m missing to my shopping list.”

If you selected C or D (which, for most systems, is the correct answer), you’ve just highlighted the exact chasm Google’s Gemini for Home is designed to eliminate.

The Era of Transactional Commands is Over.

For years, the smart home has been defined by rigid, transactional commands. But with the launch of Gemini for Home, Google is not just updating an assistant; they are deploying their most capable, contextual, and conversational AI as the new foundation for the entire ecosystem.

This is more than a software upgrade. It is a foundational reset.

This shift fundamentally changes user expectations, demanding that your devices and services move from reacting to simple commands to participating in a natural, ongoing, and context-aware collaboration. From creating complex, exception-based automations with a single sentence to summarizing a day of camera activity with generative AI, the new smart home is an intelligent partner, not just a controlled device.

Ready to find out exactly how this seismic shift impacts your B2B strategy, from product development and API integration to retail shelf space and subscription models? Let’s dive into the four pillars of the Gemini for Home transformation and the concrete steps your business must take to thrive in the new era of ambient intelligence.

The Fundamental Leap: From Command-Based to Conversational AI

The single most important distinction between the departing Google Assistant and the incoming Gemini for Home is the fundamental model of interaction. The Google Assistant was, at its core, a command processor. It required specific syntax and often lost context with follow-up questions. Gemini, however, is built on Google’s most advanced Large Language Models (LLMs), enabling a truly conversational experience.

This shift delivers several crucial capabilities:

1. Contextual Persistence and Complex Reasoning

Instead of rigid commands, users can now engage in natural, flowing dialogue. For example, a user can say, “Hey Google, turn off the lights in the kitchen and dim the living room to 25%.” Gemini executes both tasks while simultaneously remembering the context. If the user then follows up with, “Now, what’s a quick recipe using the ingredients I have?” it can intelligently connect to a previously mentioned shopping list or even interpret ingredients mentioned earlier in the conversation. This multi-step, contextual reasoning dramatically lowers the friction of smart home interaction, encouraging increased daily usage.

2. Multimodal Intelligence Beyond Voice

Gemini for Home transcends simple voice commands by deeply integrating visual and sensor data. The AI isn’t limited to what you say; it interprets what the connected devices see and sense.

• Smarter Security: New Nest Cams and Doorbells, powered by Gemini, move beyond generic “person detected” alerts. They can now generate detailed notifications, such as, “Delivery driver dropped a package at 2:05 PM,” or “The dog jumped the fence.” This intelligent summarisation transforms raw video data into actionable, language-based insights, significantly enhancing the value proposition for security device manufacturers and monitoring services.
• Home Brief: This new feature provides users with an AI-generated daily summary, turning hours of security footage and thousands of sensor events into a quick, digestible recap of key household activities. This is invaluable for busy professionals and property managers.

The B2B Pivot: Platform Opportunity and Monetisation

For B2B players, the introduction of Gemini for Home is a platform expansion, not just a product launch. Google is solidifying its ecosystem to drive revenue, creating a clear framework for third-party integration and development.

A. The Google Home Premium Subscription Model

Google is strategically bundling many of Gemini’s most advanced features, such as “Gemini Live” (for expert, continuous troubleshooting and personalised advice) and the superior AI-powered camera features, behind the new Google Home Premium subscription. This move is pivotal:

This subscription-led model de-risks hardware sales by shifting the long-term value to a service-based relationship. Device manufacturers and retailers should view the hardware as an on-ramp to the high-value subscription, rather than the final product.

B. The Developer Ecosystem and Matter Standard

Google’s long-term strategy involves making Gemini for Home the unifying intelligence layer across the entire smart home landscape. By leveraging the Matter interoperability standard, Google actively encourages third-party manufacturers, from lighting to HVAC systems, to integrate their products seamlessly.

• New API Access: Google has promised expanded Home APIs that allow developers to build the “next generation of AI cameras and devices” around Gemini’s capabilities. This is a direct call to action for hardware manufacturers to move their R&D focus toward Gemini integration.
• Simplified Automations: The “Ask Home” feature allows users to create complex automations using natural language (“Later tonight, when everyone leaves, set the alarm and turn off the basement lights”). Device makers who ensure their products flawlessly support these nuanced commands will gain a significant competitive edge and see higher adoption rates.

Strategic Considerations for Indian and Foreign Clients

The launch of Gemini for Home presents distinct opportunities for businesses targeting the dynamic Indian and global markets.

1. For Smart Device Manufacturers & Integrators

The key to success is moving beyond simple connectivity to AI-driven functionality. Your new marketing narrative shouldn’t be about “Wi-Fi enabled lights,” but about “Gemini-ready lighting systems that respond conversationally.”

• Focus on Differentiation: Prioritise features that directly leverage Gemini’s conversational memory. Think sophisticated energy management routines or multi-lingual household support, a crucial factor for diverse Indian households.
• Testing and Reliability: Google is explicitly pushing its developer ecosystem to robustly test existing Works with Google Home integrations. Any business that fails to ensure a seamless experience with the new Gemini environment risks high churn and negative reviews. Reliability under the new conversational paradigm is paramount.

2. For Real Estate and Hospitality Tech

The complexity of managing multiple devices in commercial or rental properties is simplified by a central, intelligent brain.

• Property Management: Gemini for Home can become the central operational hub in short-term rentals or serviced apartments. Imagine tenants asking, “Can you generate a summary of all door activity while I was out?” or “Start the evening routine for the whole apartment.” This provides both convenience for the tenant and valuable data/security for the owner.
• IoT for Enterprise: This AI-powered home hub is a precursor to a smarter office. B2B software companies should immediately investigate how to integrate their existing platforms (CRM, scheduling, inventory) with the emerging Gemini ecosystem to enable conversational, hands-free management in a commercial setting.

Conclusion

The replacement of Google Assistant with Gemini for Home is Google’s clear message: the future of ambient computing is conversational, contextual, and deeply embedded in our daily lives.

For B2B decision-makers, this is more than just a consumer tech update; it’s a structural realignment of a trillion-dollar ecosystem. Businesses that act decisively now to invest in Gemini integration, align their hardware R&D with AI-centric features, and strategically position themselves within Google’s new subscription economy will capture the next wave of smart technology market share. The opportunity is clear: shift your focus from simply connecting devices to infusing them with superior intelligence. The time for the passive smart home is over; the age of Gemini for Home, the conversational, contextual, and intelligent home, is here.

The post Decoding Google’s Strategic Shift to “Gemini for Home” appeared first on TechnologyXpertise.

In a recent episode of the Google for Developers podcast, Hassabis explained that even the most advanced AI systems can still fail at surprisingly basic tasks. Models like Google’s Gemini can win gold medals at the International Mathematical Olympiad, yet still make mistakes in high school-level math problems.

“It shouldn’t be that easy for the average person to find a trivial flaw in the system,” he said.

Uneven or “Jagged” Intelligence

Hassabis described today’s AI models as “uneven” or “jagged” intelligences. In some areas, they outperform humans. In others, their weaknesses show quickly. For example, a model might excel at complex problem-solving in mathematics but fail to apply similar reasoning to a simpler puzzle.

This view matches what Google CEO Sundar Pichai has called artificial jagged intelligence (AJI). Speaking on Lex Fridman’s podcast earlier this year, Pichai used the term to describe AI that is strong in some capabilities but lacking in others.

Why It Matters for Business Leaders

For companies investing in AI, inconsistency can create risk. If a model gives an incorrect answer in a business-critical context, it could lead to bad decisions, compliance issues, or reputational damage.

B2B organizations often use AI for customer support, data analysis, market forecasting, and content generation. Inconsistent reasoning could affect each of these. A chatbot might answer 90 percent of queries correctly, but the 10 percent it mishandles could damage trust. A forecasting tool might produce accurate predictions most of the time, but an occasional flawed output could cost millions.

For business leaders, the takeaway is clear: AI can be powerful, but its limitations must be factored into strategy, governance, and risk management.

Beyond More Data and Bigger Models

Hassabis stressed that solving inconsistency will require more than scaling up data sets and computing power. The missing capabilities lie in reasoning, planning, and memory. These are core cognitive skills that humans use to connect ideas, anticipate outcomes, and recall relevant information.

In his view, AI research needs to focus on improving these capabilities. That includes developing new training methods and architectures, not just larger models.

Another area Hassabis highlighted is testing. He called for “new, harder benchmarks” to measure what AI is truly good at and where it fails. Current tests often highlight strengths but don’t always reveal weaknesses.

OpenAI’s Perspective

Google DeepMind isn’t alone in seeing these gaps. Ahead of the GPT-5 launch last week, OpenAI CEO Sam Altman made a similar point. While describing GPT-5 as a major improvement, he said it still falls short of AGI.

“One big one is this is not a model that continuously learns as it’s deployed from the new things it finds,” Altman said. For him, the ability to learn independently and adapt in real time is a defining feature of AGI.

Altman’s comments underline the fact that even leading AI labs are facing the same core challenge: building systems that are not just intelligent, but consistently intelligent across all contexts.

The Road to AGI

The race to achieve artificial general intelligence is far from over. Hassabis has said he expects AGI could arrive within five to ten years, but only if researchers can address inconsistencies and other missing capabilities.

For now, B2B leaders should approach AI with a balanced mindset. These systems can offer significant efficiency gains and open new opportunities, but they need oversight. Testing, validation, and clear guardrails are essential when integrating AI into critical operations.

As the technology evolves, the winners will be organizations that can leverage AI’s strengths while managing its weaknesses. That means not only investing in tools but also in processes, training, and governance.

The post Artificial General Intelligence – The Key Weakness Holding It Back appeared first on TechnologyXpertise.

Microsoft Signals Likely Compliance

Microsoft President Brad Smith recently indicated that the company is leaning toward signing the EU’s new AI Code of Practice. “I think it’s likely we will sign. We need to read the documents,” Smith told Reuters.

The code, developed by 13 independent experts, is part of a broader EU initiative to enforce transparency and copyright compliance among developers of general-purpose AI models. Signatories must publish summaries of the datasets used to train their AI systems and adopt policies that align with EU copyright law.

Smith emphasized Microsoft’s interest in engaging constructively with the EU’s newly established AI Office, which is tasked with ensuring industry compliance with the AI Act, the world’s first comprehensive AI law that came into effect in June 2024.

Meta Rejects the Guidelines

In contrast, Meta Platforms has chosen not to sign the voluntary code. According to Joel Kaplan, Meta’s Chief Global Affairs Officer, the code introduces legal ambiguities and imposes obligations that extend beyond the AI Act’s original scope.

“Meta won’t be signing it,” Kaplan wrote in a recent LinkedIn post. “This code introduces a number of legal uncertainties for model developers, as well as measures which go far beyond the scope of the AI Act.”

Kaplan also highlighted concerns shared by 45 European companies, warning that the additional requirements could hamper the growth of frontier AI models and limit innovation among European startups and developers.

What Is the EU AI Code of Practice?

The EU AI Code of Practice is a voluntary framework that supports the enforcement of the AI Act by encouraging companies to:

• Disclose training data summaries
• Ensure AI models comply with copyright regulations
• Implement transparent governance practices
• Collaborate with the EU AI Office for ongoing oversight

While not legally binding, the code provides legal clarity and a cooperative path for companies that want to operate within the European Union’s digital economy.

Mixed Reactions from the Industry

While Meta has rejected the code, other major players including OpenAI and Mistral have already signed on. The code applies to key developers and deployers of general-purpose AI systems, including Alphabet (Google), Anthropic, and thousands of smaller companies operating in the EU.

Microsoft’s expected participation would signal strong support for regulatory collaboration, especially at a time when AI governance remains a global challenge.

What’s Next for AI Regulation in Europe?

The divergence between Microsoft and Meta reflects a broader debate about the balance between innovation and regulation in AI. While the EU aims to establish global leadership in ethical AI development, tech firms remain cautious about the impact of overlapping guidelines and complex compliance frameworks.

As the AI Act transitions into full enforcement, companies operating in Europe will need to weigh the benefits of voluntary alignment with codes like this one against the operational and legal risks of non-participation.

Conclusion

The contrasting stances of Microsoft and Meta toward the EU AI Code of Practice spotlight the ongoing tension between AI innovation and regulatory oversight. As Europe leads the charge in AI governance, the choices made by these tech giants will set the tone for global industry practices in the years ahead.

The post Microsoft Likely to Join EU AI Code of Practice While Meta Declines Participation appeared first on TechnologyXpertise.

This strategic move underscores Zoom’s growing interest in virtual reality (VR), augmented reality (AR), and artificial intelligence (AI), aiming to redefine how people engage in remote communication.

A New Dimension of Virtual Meetings

According to Meta’s official blog, the newly released Zoom app is a seamless extension of the Zoom Workplace platform, traditionally used on smartphones and desktops. This VR version allows users to enter virtual meetings as avatars in either Immersion Mode or Passthrough Mode.

• Immersion Mode: Creates a full virtual environment around the user, helping eliminate distractions and keeping the focus on conversations.
• Passthrough Mode: Enables augmented reality by blending the user’s real surroundings with virtual elements, enhancing the sense of presence.

Regardless of how users join—from desktop, mobile, or VR headsets—participants will see a consistent animated avatar for those using Meta Quest devices.

Broad Compatibility and Familiar Interface

The Zoom Meetings app for VR is compatible with:

• Meta Quest 3
• Meta Quest 3S
• Meta Quest Pro
• Meta Quest 2

The app mirrors Zoom’s desktop UI but optimizes navigation for VR. A vertical sidebar now houses key sections like Home, Team Chat, Meetings, and Contacts, making it easy to move between functions in the 3D interface.

AI and VR Take Center Stage at Zoom

Zoom’s partnership with Meta comes amid the video conferencing giant’s wider push into AI and immersive technologies. CEO Eric Yuan recently stated in an interview that his vision includes AI-generated digital twins to represent users in meetings, effectively allowing people to be present without being physically involved.

Back in March 2024, Zoom introduced a series of upgrades to its AI Companion, including customizable avatars for Zoom Clips, enabling AI to automatically generate professional video content on behalf of users.

Earlier this year, Zoom also announced its app for Apple’s Vision Pro headset, further signaling its commitment to leading in AR/VR meeting experiences. While Apple’s approach involves photorealistic avatars, Meta’s Zoom integration offers more playful, animated representations.

Conclusion

The Zoom Meta Quest app marks a significant step in transforming virtual communication through immersive technologies. By blending AI avatars, AR/VR environments, and cross-device compatibility, Zoom and Meta are making it easier—and more engaging—for users to connect, collaborate, and communicate in the virtual world.

As hybrid and remote work models evolve, tools like these will continue to shape the future of digital collaboration. With Zoom’s focus on avatar technology and Meta’s VR expertise, this partnership is poised to bring the next generation of workplace meetings to life.

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What Is Perplexity AI and Why It’s Gaining Attention

Founded in 2022, Perplexity AI has built a reputation for offering a conversational, AI-driven search engine experience. Unlike traditional search engines, Perplexity responds to user queries with verified sources and supports multimodal input, including text, voice, and images. Its growing popularity—reaching 15 million users by mid-2024—positions it as a serious challenger to Google’s search dominance.

While initial skepticism labeled Perplexity a simple “AI wrapper,” it has evolved significantly with its large language model (LLM), Sonar, and user-centric design. This success has caught the attention of companies looking for the next big leap in AI innovation.

Apple’s Motivation: Filling the AI Gap

Apple, long praised for its hardware and ecosystem, has lagged in the AI space, particularly with Siri. Despite recent updates under “Apple Intelligence,” the company’s WWDC 2025 event left many unimpressed with its AI capabilities.

To accelerate its progress, Apple has partnered with OpenAI, but owning a platform like Perplexity would offer more control. The startup’s modular architecture could help Apple build a standalone AI search engine, possibly reducing reliance on Google, which currently pays billions to be the default search provider on iPhones.

Perplexity also aligns with Apple’s privacy-first philosophy. With a clean UI and transparent sourcing, Perplexity fits the aesthetic and ethical standards Apple values. However, acquiring a growing player like Perplexity could raise regulatory concerns, especially given the ongoing scrutiny of Apple’s App Store practices.

Meta’s Push: Fast-Tracking AI Development

Unlike Apple, Meta has taken a more aggressive approach to building its AI ecosystem. Despite releasing Llama 4, the reception has been lukewarm, and Meta is eager to close the gap with rivals like OpenAI and Google.

Perplexity offers Meta an instant upgrade—its real-time search, natural conversation interface, and strong engineering team could bolster Meta’s existing AI assistant, which already reaches over a billion users through apps like WhatsApp and Instagram.

Meta’s urgency is reflected in recent moves: it invested $14.3 billion in Scale AI and is reportedly offering huge bonuses to lure top AI talent from OpenAI. For a company that has bought its way into market leadership before—think Instagram and WhatsApp—acquiring Perplexity is consistent with its bold strategy.

What’s at Stake

The race to acquire Perplexity underscores a broader trend: Big Tech is betting on AI-powered search as the next frontier. With consumer trust in traditional search engines declining, platforms like Perplexity represent a new way forward—conversational, source-based, and privacy-aware.

Whether Apple seeks tighter AI integration and independence from Google or Meta needs a faster route to AI relevance, Perplexity AI is emerging as a valuable strategic asset.

In the fast-evolving world of artificial intelligence, Perplexity’s innovation and momentum make it a startup to watch—and potentially, the next billion-dollar acquisition that reshapes how we search online.

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The focus on multilingual capability, cultural nuance, and voice interfaces reflects India’s need for AI systems attuned to its diverse languages and contexts.

India’s reliance on international LLMs often falls short in understanding local idioms, accents, and sector-specific demands. To bridge this gap, the government invited bids for over 18,000 GPUs—far exceeding initial estimates—to power high-parameter models tailored for Indian use cases. 

This compute surge underlines a national strategy to democratize AI infrastructure and foster domestic talent rather than depend solely on foreign technologies.

Sarvam in Bengaluru leads the charge with three versions of its model: Sarvam-Large for deep reasoning and text generation, Sarvam-Small for real-time AI applications, and Sarvam-Edge for on-device, low-latency tools. 

Founders Vivek Raghavan and Pratyush Kumar aim to address a spectrum of use cases, from conversational agents to embedded systems, emphasizing efficient models optimized for Indian languages and contexts. 

With government-provided GPUs and a six-month commitment announced by Ashwini Vaishnaw, Sarvam’s models are expected to be globally competitive while serving vernacular needs.

Soket AI plans to develop an open-source foundation model for India’s linguistic diversity, targeting sectors like defence, education, and healthcare. Founder Abhishek Upperwal envisions iterative development, starting small, testing rigorously, and expanding to foster community contributions and transparency.

Gnani.ai is developing real-time, voice-first LLMs with emotional intelligence, starting with a 14-billion-parameter model and expanding to 70 billion parameters within a year, aiming to improve customer service, smart assistants, and accessibility tools in India.

Stanford alumni Suvrat Bhooshan and Parth Sarthi are leading India’s push in voice AI, Gan.ai, with a 70-billion-parameter multilingual foundation model. The startup aims to outperform global benchmarks and leverage domestic talent and infrastructure to create globally competitive solutions.

IndiaAI Mission aims to create AI tools that cater to India’s diverse needs, languages, and sectors. The initiative involves startups and government investment in compute capacity, talent development, and safety standards. The next six to twelve months will determine the performance of indigenous Language Learning Machines (LLMs) in shaping India’s AI trajectory.

As these models mature, businesses and developers can expect more accurate language understanding, localized applications, and voice-driven interfaces tailored for the Indian user. If successful, India’s homegrown LLMs could not only reduce dependence on foreign solutions but also export culturally aware AI globally.

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Meta’s New AI Technology for Small Businesses

Meta recently unveiled its latest innovation for businesses: AI-powered customer service agents designed to automate interactions on popular social media platforms. These AI agents will be able to respond to voice commands, handle purchases, and even provide personalized product recommendations, all while engaging with customers in a natural and conversational manner.

According to Clara Shih, the VP of Business AI at Meta, this marks an “amazing and historic moment” in the evolution of AI. Meta’s new Llama AI model is set to make business automation accessible for everyone, from small startups to large enterprises. The goal is to provide small business owners with a cost-effective solution for customer service that can operate around the clock, without the need for hiring additional staff.

The Rise of Business AI: Making Customer Support More Accessible

Over 600 million conversations between businesses and consumers happen daily across Meta’s social platforms. With this staggering number, Meta’s new AI agents are designed to simplify customer service by automating routine tasks. These tasks include handling customer inquiries, providing returns and exchanges support, assisting with purchases, and even offering tailored product recommendations.

AI agents, powered by advanced machine learning models, are integrated into the Meta ecosystem, including Facebook, Instagram, and WhatsApp. They can interact with customers in real-time, using data from past interactions and business posts to provide contextually relevant responses, ensuring personalized communication with businesses.

How Meta’s AI Agent Works for Small Businesses

One of the key features of Meta’s AI agents is their ability to be seamlessly integrated into business operations. Business owners can set up their AI agents easily, without the need for extensive technical expertise. Whether through advertisements, DMs, or Messenger, these AI agents can instantly assist customers with a variety of inquiries.

Meta is offering this service at no cost during its pilot phase, allowing businesses to experiment with the technology and see how it can improve their operations. In the future, Meta plans to introduce pricing for the service, but the pilot allows small businesses to try the system and determine its value before committing to any costs.

The AI agents are highly customizable, enabling business owners to decide which tasks the AI will handle and which tasks should be directed to a human representative. This flexibility ensures that businesses can maintain a balance between automation and personalized customer service.

Democratizing AI: Empowering Small Businesses

Meta’s AI agents enable businesses of all sizes to access advanced AI technology, enabling them to enhance customer service without the need for a large budget or technical expertise. This initiative is significant as it makes AI solutions accessible to all types of businesses.

Shih explains that Fortune 500 companies can fine-tune AI models and create personalized solutions, while small businesses can benefit from intuitive and simple AI designed for ease of use.

Meta’s focus on small business owners is also evident in its plans. CEO Mark Zuckerberg has previously stated that he expects 2025 to be a pivotal year for AI, with Meta’s AI becoming the leading personalized assistant for over one billion users globally.

Looking Ahead: A New Era for Customer Support

As Meta rolls out its AI agents, small business owners are already benefiting from the ability to offer 24/7 customer support with minimal effort. With AI automating tasks like answering customer queries and handling purchases, business owners can focus more on growing their business and less on managing day-to-day customer service operations.

Meta’s commitment to making AI accessible is transforming the landscape of business automation, allowing small businesses to scale faster and more efficiently. As the program expands, more businesses will be able to implement AI in their operations, further changing the way companies interact with their customers.

With the potential for significantly improving customer engagement and operational efficiency, Meta’s AI agents are poised to transform how small businesses handle customer support. Entrepreneurs and small business owners can now access the same AI tools that larger corporations use—democratizing customer service and leveling the playing field for all businesses, big and small.

Conclusion

Meta’s new AI-powered customer support agents offer an exciting opportunity for small businesses to automate their customer service operations and engage with customers in a more efficient and personalized manner. By leveraging the power of AI, small business owners can improve customer satisfaction, reduce costs, and free up valuable time to focus on growing their businesses. With the full rollout of this technology on the horizon, Meta is set to empower businesses of all sizes to harness the power of AI.

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