Google has introduced Ironwood, its seventh-generation Tensor Processing Unit (TPU) at Google Cloud Next 2025. The processor unit is specifically designed to support large-scale inference workloads.

The chip marks a shift in focus from training to inference, reflecting broader changes in how AI models are used in production environments. TPUs have been a core part of Google’s infrastructure for several years, powering internal services and customer applications. Ironwood continues with enhancements for the next wave of AI applications – including large language models (LLMs), Mixture of Experts (MoEs), and other compute-intensive tools that require real-time responsiveness and scalability.

Inference takes centre stage

Ironwood is designed to support what Google calls the “age of inference,” in which AI systems interpret and generate insights actively, rather than just responding to inputs. The shift is reshaping how AI models are deployed, particularly in business use, where continuous, low-latency performance is important.

Ironwood represents a number of architectural upgrades: Each chip provides 4,614 teraflops at peak performance, supported by 192GB of high bandwidth memory and up to 7.2 terabytes per second of memory bandwidth – significantly more than in previous TPUs.

The expanded memory and throughput are to support models requiring rapid access to large datasets, like those used in search, recommendation systems, and scientific computing.

Ironwood also features an improved version of SparseCore, a component aimed at accelerating ultra-large embedding models that are often used in ranking and personalisation tasks.

Scale and connectivity

Ironwood’s scalability means it can be deployed in configurations from 256 to 9,216 chips in a single pod. At full scale, a pod delivers 42.5 exaflops of compute, making it more than 24 times more powerful than the El Capitan supercomputer, which tops out at 1.7 exaflops.

To support this level of distributed computing, Ironwood includes a new version of Google’s Inter-Chip Interconnect, which can communicate bidirectionally at 1.2 terabits per second. This helps reduce bottlenecks so data can move more efficiently across thousands of chips during training or inference. Ironwood is integrated with Pathways, Google’s distributed machine learning runtime developed by DeepMind. Pathways allows workloads to run on multiple pods, letting developers orchestrate tens or hundreds of thousands of chips for a single model or application.

Efficiency and sustainability

Power efficiency metrics show that Ironwood has twice the performance per watt as its predecessor, Trillium, able to sustain high output under sustained workloads. The TPU has a liquid-based cooling system, and according to Google, is nearly 30 times more power-efficient than the first Cloud TPU introduced in 2018. The emphasis on energy efficiency reflects growing concerns about the environmental impact of large-scale AI infrastructure, particularly as demand continues to grow.

Supporting real-world applications

Ironwood’s architecture supports “thinking models,” which are used increasingly in real-time applications like chat interfaces and autonomous systems. The TPU’s capabilities also offer the potential for use in finance, logistics, and bio-informatics workloads, which require fast, large-scale computations. Google has integrated Ironwood into its Cloud AI Hypercomputer strategy, which combines custom hardware and tools like Vertex AI.

What comes next

Google plans to make Ironwood publicly-available later this year to support workloads like Gemini 2.5 and AlphaFold, and the unit is expected to be used in research and production environments that demand large-scale distributed inference.

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A growing number of North Korean IT workers are posing as remote freelancers from other countries in an effort to gain access to companies in Europe, raising concerns about potential espionage, data theft, and operational disruption.

According to Google’s Threat Intelligence Group (GTIG), these workers—who refer to themselves as “warriors”—are securing remote roles with foreign organisations to generate revenue for the Democratic People’s Republic of Korea (DPRK). The activity, previously concentrated in the United States, is now increasingly being observed in European countries such as Germany, the United Kingdom, and Portugal.

Since GTIG’s last report on DPRK IT worker activity, recent crackdowns in the US have made it more difficult for these individuals to secure and maintain employment there. According to a blog post by Jamie Collier, lead adviser for Europe at Google’s Threat Intelligence Group, GTIG has observed a rise in operations globally, with particular growth in Europe over the past few months. Countries targeted include Germany, the UK, and Portugal.

The workers often misrepresent their nationalities, claiming to be from countries such as Italy, Japan, Malaysia, Singapore, Ukraine, the United States, and Vietnam. They find jobs through freelance platforms like Upwork and Freelancer, as well as communication channels such as Telegram. Payments are typically made in cryptocurrency or through digital payment platforms including Wise and Payoneer.

Upwork provided a statement following publication, clarifying it did not receive the initial request for comment. The company said:

“Fraud prevention and compliance with US and international sanctions are critical priorities for Upwork. The tactics outlined in this report represent a challenge that affects the entire online work industry, and Upwork is at the forefront of combating these threats. Any attempt to use a false identity, misrepresent location, or take advantage of Upwork customers is a strict violation of our terms of use, and we take aggressive action to detect, block, and remove bad actors from our platform.

Upwork has long invested in industry-leading security and identity verification measures, deploying advanced technology alongside a dedicated team of global professionals across legal, investigations, intelligence, identity risk management, compliance, anti-money laundering, and machine learning detection. These experts work relentlessly to prevent fraudulent activity before it reaches our customers, and quickly respond to new methodologies and trends.

As fraud tactics evolve, Upwork continuously enhances its proactive screening for attempts to bypass geographic restrictions, monitoring for signs of misrepresentation both before and after contracts begin. Our sophisticated detection tools, paired with strong partnerships with law enforcement and regulatory bodies, enable us to take swift and decisive action when fraudulent behaviour is identified.

While no online platform is immune to fraud, Upwork is setting the standard for trust and safety in the industry. We will continue to invest in cutting-edge fraud prevention measures and vendor solutions, collaborate with industry stakeholders, and innovate to protect our customers and uphold the integrity of our marketplace.”

Freelancer, Telegram, Wise, and Payoneer did not respond to requests for comment.

GTIG reports that since October, there has been an uptick in cases where previously terminated workers attempt to extort their former employers by threatening to leak sensitive company information to competitors. Collier suggested that mounting pressure on these workers may be pushing them toward more aggressive tactics to maintain income.

One case in late 2024 involved a North Korean individual operating under at least 12 separate identities while applying to organisations in the defence and public sectors, reportedly using false references. In the UK, North Korean IT workers have been linked to work ranging from standard web development to more advanced projects in blockchain and artificial intelligence.

Google’s research points to risks associated with bring-your-own-device (BYOD) policies, where employees use personal devices to access internal systems. These setups often lack proper security oversight, making it more difficult to detect unauthorised access.

Authorities in the US and UK have issued multiple warnings about these activities. The FBI has advised firms to improve identity verification practices, while the US Treasury in January sanctioned two individuals and four entities accused of generating revenue for the North Korean government. Officials allege the regime withholds up to 90% of wages earned by these workers.

In a separate legal action, a US federal court in Missouri indicted 14 North Korean nationals in December for allegedly participating in an employment scheme that generated US$88 million over six years. Some of these individuals were reportedly employed by US firms for extended periods, earning hundreds of thousands of dollars without detection.

The UK’s Office of Financial Sanctions Implementation has also responded. In September, it recommended employers implement stricter identity checks, including video interviews, and advised against using cryptocurrency for payments.

Collier noted that North Korea has a long history of engaging in cyber operations to fund its regime. “A decade of diverse cyberattacks (encompassing SWIFT targeting, ransomware, cryptocurrency theft, and supply chain compromise), precedes North Korea’s latest surge,” he wrote.

“This relentless innovation demonstrates a longstanding commitment to fund the regime through cyber operations. Given DPRK IT workers’ operational success, North Korea will likely broaden its global reach. With APAC already impacted by these operations, this problem is set to escalate. These campaigns thrive on ignorance and will likely enjoy particular success in areas of APAC with less awareness of the threat.”

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Google plans to acquire cybersecurity company Wiz for $32 billion in its largest-ever acquisition, strengthening the US giant’s position in the highly-competitive cloud computing market. If the deal is approved, Wiz will be integrated into Google Cloud, which generated $43.2 billion in revenue last year, up 64% from 2022.

The deal comes as Google faces antitrust inquiry in the United States, and lawsuits targeting its advertising practices and search engine dominance. Google’s acquisition of Wiz reflects a broader industry trend in which organisations seek to expand their cloud security capabilities in response to growing demand for data-intensive services.

Google’s push into cybersecurity

Google’s proposed acquisition of Wiz aims to strengthen its position in cloud, where it trails in third place behind Amazon and Microsoft.

Wiz, founded in 2020, has quickly become a major player in cloud security, obtaining contracts with large organisations to monitor and manage cloud vulnerabilities.

Wiz CEO Assaf Rappaport said the company shares Google’s goal of making cloud security more accessible and effective. “Wiz and Google Cloud are both fueled by the belief that cloud security needs to be easier, more accessible, more intelligent, and democratised, so more organisations can adopt and use cloud and AI securely,” they said in a blog post. Google CEO Sundar Pichai stated that the acquisition would let the company provide stronger security at a lower cost.

Wedbush analysts have described the deal as a strategic move to compete with Microsoft and Amazon, which have already invested heavily in cybersecurity. Google’s acquisition of Mandiant for $5.4 billion in 2022 helped boost its cloud division’s operating profit to $6.1 billion last year, and Wiz is expected to expand its portfolio of offerings.

High price and market impact

The $32 billion price tag exceeds Google’s previous largest deal – a $12.5 billion acquisition of Motorola Mobility in 2012. According to Mergermarket, the Wiz deal ranks among the 20 most expensive software company acquisitions to date. Investors have responded cautiously, with Alphabet’s shares dropping 2% following the announcement.

Google has been in discussions with Wiz for several months, reportedly increasing its offer from a previous $23 billion bid that was rejected in July. Wiz initially planned to pursue an IPO but decided against it owing to market volatility.

Industry-wide impact and antitrust concerns

The acquisition comes as the cybersecurity market continues to grow. Mark Smith, a director at Houlihan Lokey’s Technology Group, said the global cybersecurity market exceeds $50 billion, growing over 10% annually. Cloud security, in particular, is expanding even faster due to increasing threats and regulatory demands. “Strategic acquirers are competing to secure emerging technologies, driving up valuations,” he said. He highlighted AI’s role in shaping security measures and creating more resilient defences.

The Google-Wiz deal raises antitrust concerns. The US Justice Department has already filed cases against Google’s search and advertising businesses, threatening to force the company to divest itself of Chrome and/or Android. It’s thought, therefore, that regulators are expected to scrutinise the Wiz acquisition closely. The Justice Department is also exploring the impact made by Google’s deals to make its search engine the default for Apple and other platforms.

Despite these challenges, Google and Wiz anticipate the deal will close in 2026, pending regulatory approval and completion of other conditions. Analysts at Mergermarket believe the companies would not have agreed to the deal without seeing a clear path to approval under the Trump administration.

Business watchdog group, the Demand Progress Education Fund, has urged regulators to block the deal, arguing it would consolidate too much power in Google’s hands. Emily Peterson-Cassin, the group’s director of corporate power, said the acquisition would undermine competition in the cybersecurity market.

Future of cloud and cybersecurity

The Wiz deal reflects the trend of consolidation in the cybersecurity space. Google, Microsoft, and Amazon are investing heavily in cloud security to address rising threats and meet customer expectations for compliance and protection. According to Wedbush analysts, more deals will likely follow as organisations seek to boost their AI and security capabilities under a receptive US administration.

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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OpenAI and Google are pushing the US government to allow AI models to train on copyrighted material, arguing that ‘fair use’ is critical for maintaining the country’s competitive edge in artificial intelligence.

Both companies outlined their positions in proposals submitted this week in response to a request from the White House for input on President Donald Trump’s “AI Action Plan.”

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A research team at the University of Science and Technology of China (USTC) has introduced Zuchongzhi-3, a 105-qubit superconducting quantum computer capable of performing calculations at speeds 10¹⁵ times faster than the most powerful supercomputer and one million times faster than Google’s latest quantum results.

Zuchongzhi-3 represents a significant step forward in quantum computing. The research team announcing the breakthrough was led by Jianwei Pan, with Xiaobo Zhu, Chengzhi Peng, and others, publishing their findings in Physical Review Letters.
Quantum supremacy refers to the point where a quantum computer can calculate faster than even the most powerful classical computers. In 2019, Google’s 53-qubit Sycamore processor completed a specific sampling action in 200 seconds, which is anticipated to take 10,000 years on a classical supercomputer, for example.

However, in 2023, USTC researchers revealed that an improved classical algorithm could solve the same task in 14 seconds using over 1,400 A100 GPUs. Using the Frontier supercomputer’s enhanced memory, the task can now be completed in 1.6 seconds, putting Google’s past claim of quantum supremacy into question.

Technical specifications and performance

Zuchongzhi-3, which builds on the 66-qubit Zuchongzhi-2, outperforms previous models in key areas. The system has a coherence time of 72 microseconds, with single-qubit gate fidelity at 99.90%, two-qubit gate fidelity at 99.62%, and readout fidelity at 99.13%. The improvements allow for more accurate and complex quantum operations.

The research team performed an 83-qubit, 32-layer random circuit sampling task at processing speeds 15 orders of magnitude faster than the most powerful classical supercomputer. Zuchongzhi-3 also outperformed Google’s latest quantum computing results by six orders of magnitude, setting a new benchmark for superconducting quantum systems.

What is quantum supremacy?

Quantum supremacy has broad implications across industries.

• In cryptography, quantum computing could run Shor’s algorithm, which threatens current encryption methods by efficiently factoring large numbers.
• In drug development, quantum simulations could accelerate the discovery of new treatments by modelling molecular interactions with high precision.
• Quantum-powered weather forecasting could improve the climate model accuracy, and quicker market analysis and algorithmic trading could improve stock trading efficiency.
• Quantum computers could help material scientists identify new materials with unique properties by performing precise atomic-level modelling.

Challenges and progress

Despite the promise of quantum computing, there are significant challenges to achieving consistent quantum supremacy. Qubit stability and error rates remain key concerns. Quantum operations are particularly sensitive to external noise, which raises the likelihood of computation errors.

The number of functional qubits is another limiting factor. Building scalable quantum systems requires increasing the number of qubits while keeping error rates low. Current developments in error correction, like surface code integration, try to address these concerns.

USTC researchers are working on improving error correction by starting with a distance-7 surface code and planning to extend this to distances 9 and 11 to improve fault tolerance and system stability.

Global race in quantum computing

Investment in quantum computing has grown rapidly, with major players like Google, Microsoft, and IBM driving research and development. Google remains focused on fault-tolerant quantum computing, while Microsoft is looking at topological qubits for scalable quantum systems.

IBM has made progress in superconducting quantum processors, whereas Alibaba has focused on quantum cryptography and simulation. China and the United States continue to lead the way in quantum research, with government and private sector funding driving advances in hardware, algorithms, and applications.

Collaborative effort

The research involved multiple institutions, including the Shanghai Research Centre for Quantum Sciences, Henan Key Laboratory of Quantum Information and Cryptography, China National Institute of Metrology, Jinan Institute of Quantum Technology, the School of Microelectronics at Xidian University, and the Institute of Theoretical Physics under the Chinese Academy of Sciences.

The next step for USTC researchers will be to scale the system while improving accuracy and reducing error rates – important steps toward achieving reliable quantum supremacy.

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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Google’s Pixel lineup has evolved to include a number of models, starting with the base Pixel, the Pro variations, and, most recently, the Pro Fold model.

The Pixel 9 is the latest addition to Google’s flagship series, offering some enhancements and retaining core strengths. Released alongside Android 15, the device combines refined hardware and software to deliver a compelling user experience. However, while the Pixel 9 stands out in many ways, it faces strong competition from the rest of its own lineup, particularly the Pixel 9 Pro and Pro XL.

Tech Wire Asia had the opportunity to review the Pixel 9. Here’s a closer look at the strengths and limitations of this year’s base model.

Design and build: Sleek but imperfect

The Pixel 9 introduces subtle yet impactful design refinements to the lineup. Its flatter profile and grippable frame make it comfortable to hold, with improved ergonomics compared to its predecessor. The return to uniform bezels around the display adds to its sleek, symmetrical appearance, appealing to users who value minimalist aesthetics.

However, the glossy backplate detracts from the overall premium feel, especially when compared to the polished matte finishes found on competing smartphones. The addition of more premium case options from third-party manufacturers would enhance protection without sacrificing style — a demand we hope Google addresses in the future.

Display and audio: Bright and balanced

As expected, the Pixel 9 continues Google’s tradition of delivering excellent displays. The screen’s better brightness ensures usability in a variety of lighting conditions, including direct sunlight. While the overall quality is not a significant leap from the Pixel 8, the display remains one of the device’s best qualities.

The audio experience has also improved, with speakers delivering richer sound. However, the maximum volume could benefit from a further boost to match the immersive quality of other flagship devices. The multimedia experience, when combined with the responsive haptics, is one of the phone’s highlight.

Performance: Reliable but not groundbreaking

The Pixel 9 is powered by Google’s Tensor G4 processor, which brings minor but effective improvements in performance and thermal management. With an additional four gigabytes of RAM compared to the Pixel 8, the device feels noticeably more responsive during daily use, easily handling multitasking and routine tasks.

That said, the use of UFS 3.1 storage creates a bottleneck, particularly when switching between apps or transferring data. Faster storage technology could have significantly boosted the device’s overall responsiveness. While the Pixel 9 is not designed for heavy gaming or benchmarking, it performs adequately for everyday tasks, showcasing Google’s focus on optimisation rather than raw processing power.

Camera: Reliable but limited

The Pixel 9 continues to excel in photography, capturing sharp, vibrant, and detailed images thanks to its dual-camera configuration. Edge detection in portrait mode has improved with updates, while the Magic Editor feature allows users to make meaningful post-capture adjustments, such as removing unwanted elements from photos. The Google Camera app continues to be a market leader.

However, the absence of a telephoto lens limits the camera’s versatility, especially for users accustomed to optical zoom. While Google’s computational photography algorithms compensate to some extent, a specialised telephoto lens would have added value to the camera system.

Furthermore, the difference between what is shown in the viewfinder and the final processed image remains a concern, particularly in modes such as portrait photography.

Battery life: A reliable companion

The Pixel 9’s battery life has improved following the Android 15 update. Previously, users could deplete the battery in a day, but power management improvements have extended its endurance to keep up with other smartphones in its class. While these changes are not groundbreaking, they make the Pixel 9 a more dependable choice for daily use.

Charging speed, however, remains an area for improvement. Faster charging would significantly enhance the overall user experience. Users who require greater storage, especially for tasks like 4K video recording, will benefit from the 256-gigabyte model, which provides more flexibility without frequent file management.

AI features: Promising but region-locked

One of the Pixel 9’s standout features is its integration of AI tools, such as Gemini and Pixel Screenshots. Pixel Screenshots, in particular, allows users to efficiently search and organise screenshots, saving time and improving productivity. Magic Editor and other AI-powered features add creative flexibility for editing photos and videos.

However, many of these features are region-locked, which diminishes their universal appeal. Tools like Call Notes remain unavailable in certain regions, limiting the Pixel 9’s ability to fully leverage its AI-driven potential. Google needs to address these regional limitations to make the device’s AI capabilities universally attractive.

Pricing and competition: A tough sell

At its recommended retail price of $790, the Pixel 9 positions itself as a premium mid-range device. It provides a well-rounded package but other phones provide more value when it comes to performance and features. Discounts, trade-ins, and rebates make the Pixel 9 more attractive, but it is still outperformed by the Pixel 9 Pro and Pro XL, which deliver enhanced capabilities with fewer compromises.

The Pixel lineup spans a diverse price range, from about $800 to $1,800, with the goal of catering to a variety of users’ budgets. However, there is a noticeable gap between the $1,200 and $1,800 price points, which could be filled by a Pixel Pro Flip in the future.

Additionally, Google plans to introduce the Pixel 9a in mid-2025, a budget-friendly option that is expected to scale back features to achieve a lower price point and broaden the lineup’s appeal.

Verdict: A solid base model with caveats

The Pixel 9 exemplifies Google’s commitment to refining its flagship lineup. With a strong display, dependable battery life, and reliable cameras, it delivers a well-rounded experience. However, it falls short of its Pro siblings in terms of regional AI availability, storage technology, and overall versatility.

For those looking for a sleek and capable phone, the Pixel 9 delivers. But those willing to spend a little more may find better value in the Pro models.

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Two major initiatives were announced at the launch of Malaysia’s National AI Office (NAIO), marking a significant step forward in integrating generative AI into public services.

The initiatives are part of Google’s broader partnership with the Malaysian government, which includes a US$2 billion investment in a new Google data centre and Cloud region in Selangor’s Elmina Business Park. Construction on the facilities has been underway since October 2024.

Introducing ‘AI at Work’: A productivity boost for public officers

The first initiative, ‘AI at Work,’ is a collaboration between the Ministry of Digital and Google Cloud. The programme will integrate Gemini for Google Workspace into public officers’ daily routines, beginning with a pilot program at the Ministry of Digital. The goal is to enhance productivity by leveraging AI for tasks like report writing and meeting summaries, allowing officers to focus on strategic projects.

Gemini for Google Workspace is designed to be an “always-on” AI collaborator that streamlines workflows, creates visualisations, and improves communication in teams. Built with enterprise-grade protections, it ensures that sensitive data stays inside trusted boundaries.

Public officers using Gemini will gain access to a suite of productivity apps, like Gmail, Drive, Docs, Sheets, Slides, Meet, and Chat. Furthermore, NotebookLM, a personalised AI research assistant included as an add-on, enhances how public officers interact with legislative and policy documents.

NotebookLM: Transforming how public officers access information

NotebookLM stands out by allowing users to upload and query documents, extracting insights to support decision-making. For example, a public officer can upload files such as Google Docs, PDFs, or URLs and ask questions about their content. NotebookLM gives accurate answers with inline citations to ensure transparency. Aside from Q&A, the tool can generate summaries, briefing documents, timelines, and audio overviews, making it a useful assistant for public service personnel.

Google has also introduced new tools to enhance productivity and improve access to enterprise data. Google Agentspace, for instance, uses AI capabilities to help employees tackle tasks such as planning, research, and content creation. By combining Gemini’s reasoning abilities, search, and enterprise data, Agentspace enables employees to work more efficiently, regardless of where data is hosted.

NotebookLM is also being expanded for enterprises with a feature called NotebookLM Plus. Employees can use the tool to upload data, synthesise information, and extract insights, supporting more dynamic methods of engaging with content, such as Audio Overviews, which are similar to podcast-style summaries.

NotebookLM Plus prioritises security and privacy for organisational use, and an experimental version of Gemini 2.0 Flash is being integrated to improve the capabilities.

Serene Sia, Country Director for Malaysia and Singapore at Google Cloud, highlighted the importance of this initiative: “In alignment with NAIO’s goal of promoting AI innovation through collaboration, the AI at Work initiative by the Ministry of Digital and Google Cloud will empower public officers with secure and best-in-class AI tools to drive efficiency, innovation, and citizen-centric service delivery.”

Collaboration for responsible AI adoption

The second initiative focuses on policy and education. Google and NAIO are establishing an ‘AI Policy and Skilling Lab’ in Malaysia. The lab will serve as a hub for policymakers, industry experts, and other stakeholders to collaborate on AI-related challenges and opportunities. Through think tank discussions and workshops, the Lab aims to develop frameworks and best practices for the responsible use of AI.

Su Ann Lim, Head of Government Affairs and Public Policy for Google Cloud’s Southeast Asia Cluster, emphasised the Lab’s role: “The AI Policy and Skilling Lab aligns with the Malaysia government’s goals of operationalising safe and responsible AI. By fostering collaboration and knowledge sharing, this initiative will establish clear guidelines for AI adoption, ensuring its benefits are realised while mitigating potential risks. This will not only elevate Malaysia’s standing as a leader in the region for AI development and adoption but also attract investment and create new economic opportunities for Malaysians – especially ahead of the country’s ASEAN Chairmanship in 2025.”

Together, the initiatives highlight Malaysia’s ambitions to use AI for national development, demonstrating how technology and strategic partnerships can drive meaningful change in public service and beyond.

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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With Android 15, Google has introduced something exciting: wi-fi ranging—a technology designed to help us find our way indoors with far better accuracy than before. Think of all the times GPS couldn’t quite get it right inside a mall, airport, or conference centre because of those pesky walls and structures. Wi-fi ranging tackles this issue head-on, using the IEEE 802.11az protocol to give you location accuracy within less than a metre—essentially changing how Android users navigate indoor spaces.

Why is wi-fi ranging a big deal?

Most of us rely on GPS for navigation, but GPS has always had a major blind spot: it doesn’t work well indoors. GPS signals come from satellites orbiting Earth, which struggle to penetrate solid structures like walls, floors, and ceilings. So, once you’re indoors, GPS accuracy often becomes unreliable, making it hard to pinpoint locations inside large buildings. That’s where wi-fi ranging comes in. Instead of relying on satellites, it uses nearby Wi-Fi access points to calculate your indoor position with impressive accuracy. This might be a game-changer for navigating spaces like large malls, crowded airports, museums, and stadiums.

Wi-fi ranging builds on previous wi-fi positioning technologies, like Wi-Fi RTT (Round Trip Time) with FTM (Fine Timing Measurement). Wi-Fi RTT, introduced in Android 9, was already a solid improvement, bringing location accuracy down to about 1-2 meters. But the technology in Android 15 takes it further, promising sub-metre precision.

The way it works is actually pretty cool: it measures the time it takes for signals to travel between your device and multiple nearby Wi-Fi access points, doubling the bandwidth (160 MHz) and utilising the devices’ support for the 6GHz band. Those enhancements improve accuracy, but they also boost scalability and security, making wi-fi ranging an important upgrade for indoor positioning.

How does wi-fi ranging compare to GPS for indoor tracking?

Indoor environments have always been GPS’s Achilles’ heel. Using access points that are already installed in buildings overcomes GPS’s limitations and provides a reliable way to navigate large indoor spaces. So, whether you’re trying to find your gate at the airport or locate a specific store in a big shopping mall, wi-fi ranging makes accurate indoor directions much easier.

Wi-fi positioning technology has evolved quite a bit. The first methods used Received Signal Strength Indicator (RSSI), which was only accurate within 10-15 meters. Then came Wi-Fi RTT in Android 9, which measured the time-of-flight of RF packets between your device and nearby access points. Now, with wi-fi ranging using the 802.11az protocol, Android 15 achieves precision, refinied timing measurements and can into more bandwidth for accurate location discovery.

This leap means this innovative tech can pinpoint locations more precisely, making it a great fit for places where close accuracy matters, like retail spaces, airports, and offices.

Which devices support this technology?

Currently, Wi-Fi Ranging is available only on devices running Android 15 and equipped with Wi-Fi chips that support the 802.11az protocol. Many phones on the market lack the requisite, but Qualcomm’s FastConnect 7900 chip is paving the way for future compatibility. Over the next few years, as more manufacturers integrate this technology, we can expect to see wider adoption of Wi-Fi Ranging in Android devices.

For Wi-Fi Ranging to work, the Wi-Fi access points in a space must support the 802.11az standard. While some Wi-Fi 6 access points may be compatible with a firmware update, others might need to be upgraded or replaced. Until this support becomes more widespread, this tech will only be available in places with compatible access points. However, as the technology grows more mainstream, we’ll likely see more locations improving their infrastructure to enable this feature.

How does it stack up against UWB and Bluetooth?

While it has amazing range and scalability, other technologies such as UWB (Ultra-Wideband) and Bluetooth Channel Sounding offer slightly better accuracy in some cases. However, this tech has a few big advantages: it’s built on existing Wi-Fi infrastructure, supports a larger number of clients, and can adapt to traffic loads without compromising performance. According to Google engineer Dr. Roy Want, Wi-Fi Ranging is secure, scalable, and ideal for diverse environments where a balance of accuracy and convenience is key.

With this tech, the possibilities are exciting. Imagine being able to find the exact product you’re looking for when you go into a store. In smart homes, this feature could enable even more intelligent automation, like adjusting lights based on the room you’re in. And these examples are just the beginning. Developers and companies will probably find even more ways to use Wi-Fi Ranging to create convenient and immersive user experiences.

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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In recent months, interest in artificial intelligence (AI) has surged, with many business leaders eager to get started but often asking the same question: Where do we begin? This is where understanding AI’s potential for growth, efficiency, and future-proofing becomes essential.

AI tools are increasingly embedded in the apps we use daily, from social media to productivity software. “Most of the apps we use daily now feature generative AI, influencing consumer behaviour and how we interact with technology,” noted Caroline Yap, Managing Director of Global AI Business & Applied Engineering at Google, at the Google Cloud APAC Media Summit in Singapore.

This widespread adoption prompts questions about how companies can hire, retain, and reskill talent while determining which AI tools to leverage. Yap’s advice is straightforward: Start with a clear understanding of your business strategy and identify where AI can drive growth, efficiency, and innovation.

Starting with growth, not efficiencies

A recurring question from business leaders is: Why prioritise growth over efficiency? Yap believes that firms should focus on growth when adopting AI. “If you start by focusing solely on efficiency, you risk limiting innovation by simply addressing past issues,” she explained. By focusing on growth, companies can rethink how AI might shape their services and experiences to meet evolving consumer expectations.

“This approach enables companies to develop new experiences that align with changing consumer behaviours,” she said. Yap emphasised that focusing on growth first allows companies to design unique customer interactions, then implement AI solutions to make those experiences efficient.

To support this shift, Yap explained how Google Cloud’s Vertex AI platform enables enterprises to securely design and deploy custom models. Agent Builder and Model Garden are tools that assist businesses address specific business goals while retaining complete control over their data. “We prioritise security, trust, and privacy in our AI models to allow businesses to use them with confidence,” Yap added.

Rising pressures on today’s security organisations

When it comes to security, it’s always a major concern for organisations introducing new technologies. According to Mark Johnston, Director of the Office of the Chief Security Information Officer (CSIO) at Google Cloud APAC, security teams are increasingly strained as cybercrime grows in scale and complexity.

“Cyberattacks are happening at unprecedented rates, and we’re challenged to respond effectively,” he said. Adding AI poses new set of risks, but Johnston believes it might also be a valuable tool in defence.

However, Johnston recognised that AI integration must be handled with caution to prevent creating new risks. Companies require strong data governance to ensure that sensitive financial, personal, and proprietary information is not unintentionally disclosed. “AI must be applied responsibly,” he stated. “We provide not only products but also a methodology to help businesses assess and manage their software, data, and operational risks.”

The importance of data governance in AI

Johnston emphasised that proper data governance is essential for secure AI adoption. “Data management is critical, as it often limits our ability to understand AI-related risks,” he noted. When AI processes sensitive data like personally identifiable information (PII) and financial records, strong data governance is crucial to preventing privacy breaches and protecting intellectual property.

Organisations without robust data management risk violating privacy standards and exposing corporate data. “Handing over sensitive data to multiple models across various business functions without governance is risky,” Johnston explained.

Google’s Vertex AI platform supports data security by providing real-time data protection and data lineage visualisation, which traces data from origin to application. “Data governance maximises the value of AI while ensuring data security,” he added.

Protecting AI models and intellectual property

For startups and companies developing AI models, securing intellectual property is vital. “For many AI startups, it’s not just about the models—they’re existential to the business,” Johnston pointed out. Google’s security team has discovered vulnerabilities in large language models (LLMs), including the company’s own Gemini model, highlighting the potential of remote access and data theft. Recognising the broader implications, Google publicised these results to the industry to improve model security.

“Model theft is a significant concern, as it threatens the integrity and investment in AI,” Johnston stressed. To address this, Google has developed tools to prevent unauthorised access to model weights and data. For example, Google’s AI Notebook Scanner detects vulnerabilities within Jupyter notebooks, ensuring developers work in secure environments.

The Google Secure AI Framework (SAIF)

Google introduced the Secure AI Framework (SAIF) to further support secure AI integration by providing guidelines on safe data usage, risk management, and responsible AI practices. Johnston emphasised that SAIF allows organisations to use AI responsibly by providing a structure that supports security while increasing AI capabilities.

Google’s SAIF and Vertex AI ensure that organisations can utilise AI’s revolutionary potential while adhering to high security standards; so, ensuring a secure and sustainable path forward for AI-driven innovation.

Navigating AI compliance and industry standards with Google

In addition to SAIF, Google recently joined efforts to establish the Coalition for Secure Artificial Intelligence (CoSAI) and contributed to a universal AI risk management standard, ISO 42001. These initiatives aim to create a framework for safe AI applications across industries.

“Our goal is to make AI security consumable, understandable, and practical for any organisation looking to integrate AI into their operations,” Johnston emphasised.

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The Indonesian Ministry of Industry has said that Google’s Pixel phones can’t be bought by Indonesians from domestic retailers because the US company does not ensure 40% of their ‘content’ comes from Indonesia. Content can comprise firmware or some form of investment in the local population, as well as the physical components of a phone. Spokesperson Ministry Febri Hendri Antoni Arief said, “The local content rule and related policies are made for fairness for all investors that invest in Indonesia, and for creating added value and deepening the industry structure here.”

The most recent ban follows on from a similar limit on sales of Apple’s iPhone 16 placed in late October this year. Both bans also apply to phones used by tourists and visitors to the country.

Apple iPhone and Google Pixel ban

Apple had promised to invest $109 million in local infrastructure, including educational initiatives, but to date has only committed $95 million. According to Statista, $109 million is accrued in revenue by the Cupertino, California-based company roughly every ten hours, with the required shortfall of $14 million taking about an hour and a quarter’s global income.

Apple Academies – Apple’s choice of Indonesian investment – train students in the use of development tools and methods used to produce software for the company’s devices that run iOS, macOS, tvOS and iPadOS.

Companies wishing to sell their consumer tech devices have to seek certification from the Indonesian government, having proved that they are ploughing money into the local economy. How that investment is manifest is agreed between the Indonesian authorities and the company in question.

Korea’s Samsung and China’s Xiaomi have created manufacturing and assembly plants in Indonesia, and currently, Samsung holds 16.5% of the Indonesian handset market. Mi phones from Xiaomi comprise 18.4%, according to statistics from Counterpoint.

As part of the same survey, Counterpoint’s senior analyst, Febriman Abdillah, stated that there is particular demand in Indonesia for mid-range phones ($200-$399) at present, a bracket that excludes Google and Apple’s offerings other than as luxury items.

The Indonesian government implements its embargoes by means of withholding IMEI certifications for new handsets. That has the effect of making phones impossible to use with a domestic carrier for data, calls or texts. Phones could still operate as wi-fi-only devices – potentially an option for tourists entering Indonesia with a new device. Given the strictures in place at present, however, the government’s edicts have effectively stopped all sales to the domestic market.

Both Apple and Google can still qualify for the necessary certifications to re-open trade in the country, but at the time of writing, neither company had commented on the developing situation. Apple’s Tim Cook visited Indonesia in April 2024 as part of the negotiations over Apple’s inbound investment, but the company’s shortfall means that it, like Google, exists in a state of limbo with regards handset sales. Google’s ban comes just days after that affecting Apple, showing that the Indonesian government is sticking to the letter of its edicts, even if US technology companies are not.

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