Apple’s latest event introduced the new iPhone 17 lineup, the ultra-thin iPhone Air, major iOS 26 updates, and fresh AirPods. The launch gives Apple fans a look at what’s next for iPhone 17 models and other devices arriving this fall.

The iPhone Air: Apple’s thinnest phone yet

Apple introduced the iPhone Air, a device that’s 5.6mm thick and weighs 165 grammes. Tim Cook described it as offering “pro performance in a thin and light design.”

The Air features a 6.5-inch ProMotion display with a refresh rate that reaches 120Hz and up to 3,000 nits of peak brightness. Apple says the body is its “most durable” design to date, built with a ceramic shield and titanium frame.

Under the hood, the Air runs on Apple’s new A19 Pro chip, the fastest in the iPhone lineup so far. It also comes with the C1x modem, which the company claims doubles the speed of the previous C1, and the all-new N1 chip for Wi-Fi 7, Bluetooth 6, and Thread support.

Battery life is designed to last through the day, with up to 27 hours of video playback. There’s also a $99 MagSafe battery pack built exclusively for the Air that stretches that time to 40 hours. To make room for more battery capacity, Apple dropped physical SIMs – the Air supports eSIM only. iOS 26 will also bring a new adaptive power mode to help stretch battery performance.

The Air introduces a 48MP “dual fusion” rear camera system, paired with a 12MP telephoto lens. A new capture mode allows both the front and back cameras to record at the same time. The 18MP front camera supports Center Stage, a feature that frames everyone in view without requiring the phone to be rotated.

The iPhone Air will be available in black, white, beige, and light blue, starting at $999 for 256GB of storage. Preorders open September 12th, with sales beginning September 19th.

iPhone 17: A larger display and camera upgrades

The iPhone 17 no longer has a Plus version. Instead, it comes in a single size with a slightly larger 6.3-inch OLED display, slimmer bezels, and ProMotion support at up to 120Hz. The screen can reach 3,000 nits of peak brightness and has a new protective coating, Ceramic Shield 2, that Apple says is three times more resistant to scratches.

Camera improvements headline the update. The rear system includes a 48MP main camera that can act as a 2x telephoto lens by cropping, alongside a 48MP ultrawide lens with macro capabilities. The front camera has also been upgraded to 18MP with a larger, square sensor, allowing for high-quality landscape selfies without rotating the phone.

Internally, the iPhone 17 is powered by Apple’s new A19 chip with a six-core CPU and five-core GPU. Apple says this enables better performance for on-device AI tasks while still delivering all-day battery life – up to 30 hours of video playback.

The phone also introduces Apple’s new in-house N1 networking chip, which replaces Broadcom components. It supports Wi-Fi 7, Bluetooth 6, and Thread, improving the reliability of features like AirDrop and hotspot sharing. The faster C1x modem also ships with the device.

The iPhone 17 starts at $799 for 256GB of storage. Preorders begin September 12th, and it launches September 19th in black, lavender, blue, green, and white.

iPhone 17 Pro and Pro Max: New design and big battery

The iPhone 17 Pro lineup sees the biggest visual change in Apple’s new phones. The rear camera system now sits on what Apple calls a “full-width camera plateau,” a bar that spans the back of the phone. The design recalls the Pixel’s wide camera bar and is expected to appear on Samsung’s next S series as well.

For the first time, all three rear cameras feature 48MP sensors. The telephoto lens is the most improved, offering 56% more sensor space and up to 8x optical quality zoom. Like the other models, the front camera has been upgraded to 18MP with Centre Stage support.

Video tools get a boost too, including Dual Capture – which records from both front and rear cameras at once – and support for formats like ProRes RAW and Log 2.

The Pro models keep the same display sizes: 6.3 inches for the Pro and 6.9 inches for the Pro Max, with ProMotion at up to 120Hz and peak brightness of 3,000 nits. The body returns to aluminium, paired with second-generation Ceramic Shield on the front.

Performance comes from the A19 Pro chip, a 3nm processor with a six-core CPU and GPU. But the standout is battery capacity. Apple says the Pro Max offers up to 39 hours of video playback, the longest ever for an iPhone. Models sold in the US are eSIM-only, leaving space for larger batteries. Versions with physical SIMs may get slightly less runtime.

Apple’s iPhone 17 Pro line supports faster charging too – up to 25W through MagSafe wireless charging using the Qi2.2 standard. Colour options include silver, blue, and a bright orange.

Pricing starts at $1,099 for the Pro and $1,199 for the Pro Max, both at 256GB of storage. The Pro Max can be configured with up to 2TB, priced at $1,999.

Security upgrades in iOS 26

Beyond hardware, Apple is stressing new security changes in iOS 26. The company says it’s delivering “the most significant upgrade to memory safety in the history of consumer operating systems.”

The feature, called Memory Integrity Enforcement (MIE), targets spyware that exploits memory bugs, like those used in Pegasus. Built into the A19 and A19 Pro chips, MIE protects memory by default without slowing performance. Apple says this makes it more costly for attackers to build spyware.

The open-source GrapheneOS project praised the improvements while pointing out differences between Apple’s approach and Android’s Memory Tagging Extension, which is already active on Pixel phones.

iOS 26 launches September 15th, bringing the new “Liquid Glass” design language, which gives apps and system elements a glossy, transparent look. The update also includes new features like Live Translation, a refreshed Phone app, call screening, polls in Messages, and a new Games app.

MagSafe battery and accessories

Apple also revealed a new MagSafe battery pack, but it only works with the iPhone Air. The $99 add-on attaches to the slim phone, but its size doesn’t fit the camera layout of other models. Apple ended support for its previous MagSafe Battery Pack in 2023, though third-party options remain available.

Other accessories include a reinforced polycarbonate bumper case, a standard MagSafe case, and a crossbody strap option.

Apple Watch and new health features

Apple’s latest software update for its watches, watchOS 26, arrives September 15th. It brings new features to existing models, not just the upcoming Series 11.

Hypertension notifications are the highlight. Using the heart sensor, the watch can track vascular responses over 30 days and alert users if it detects signs of high blood pressure. Apple is seeking FDA approval for the feature, with plans to roll it out in more than 150 regions.

Other updates include Sleep Score, which combines heart rate, temperature, blood oxygen, and breathing data to grade sleep quality. The will be available on Series 6 and later, along with Watch Ultra and SE models.

AirPods Pro 3: Better health tracking

The AirPods Pro 3 are Apple’s first major update to the line in three years. They introduce a heart rate sensor, stronger noise cancellation, and live translation features.

Apple says the redesigned earbuds are smaller and shaped to fit better after analysing more than 10,000 ear scans. They come with five tip sizes and are rated IP57 for water and sweat resistance.

The new heart rate sensor uses infrared light to measure blood flow and, paired with iPhone sensors and AI, can track calories burned and activity. A new workout feature called Workout Buddy links this data with fitness history.

Noise cancellation has also been improved, with Apple claiming twice the performance of the previous model. Live Translation lowers outside volume and provides spoken or text translations through the earbuds or paired iPhone.

The AirPods Pro 3 will cost $249, with preorders starting today and shipping September 19th.

iPadOS 26: New windowing system

Apple confirmed iPadOS 26 will be released on September 15th. The update adds the Liquid Glass design seen in iOS 26 but also introduces a new way to manage apps.

Users will be able to resize, minimise, and move app windows – similar to the multitasking system on Macs. A new Files app and a tablet version of Preview also arrive, alongside support for AI-powered Live Translation in the Phone app.

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Microsoft has introduced its first in-house AI models, a move that could reshape its position in the AI race. The company rolled out MAI-Voice-1, a speech model, and MAI-1-preview, a text-based model it calls a glimpse of what’s coming next inside Copilot.

The MAI-Voice-1 model is built for speed. According to Microsoft, it can generate a full minute of audio in less than a second using just a single GPU. The model is already in use inside some of the company’s tools. For example, Copilot Daily uses it to deliver short news summaries through an AI voice host. It also helps produce podcast-style conversations that break down complex topics into easier explanations.

The second release, MAI-1-preview, is designed for text tasks. Microsoft trained the model on roughly 15,000 Nvidia H100 GPUs, giving it the scale to handle instruction-following and natural Q&A. Users can already try it on Copilot Labs, where they can test its ability to respond to everyday queries. Microsoft says the model will soon support text-based use cases inside its Copilot assistant.

Competition with OpenAI

These launches come while Microsoft is still heavily tied to OpenAI, the maker of ChatGPT. Microsoft has invested more than $13 billion into the startup, which now has a valuation of about $500 billion. OpenAI continues to rely on Microsoft’s cloud infrastructure to run its own models, while Microsoft uses OpenAI’s systems inside Bing, Windows, and other products.

At the same time, the two companies are drifting into competition. Last year, Microsoft added OpenAI to the list of rivals it names in its annual report, alongside Amazon, Apple, Google, and Meta. OpenAI has also been spreading its infrastructure needs across other providers such as CoreWeave, Google, and Oracle, as demand for ChatGPT climbs. The chatbot now draws about 700 million weekly users.

Early results and rankings

Performance comparisons show Microsoft’s work still trails some of its peers. On Thursday, the new MAI-1-preview ranked 13th for text workloads on LMArena, behind models from Anthropic, DeepSeek, Google, Mistral, OpenAI, and Elon Musk’s xAI. While not at the top, Microsoft has positioned MAI-1-preview as its first foundation model built entirely in-house.

“MAI-1-preview represents our first foundation model trained end to end in house,” Mustafa Suleyman, Microsoft AI chief, wrote on X.

A consumer focus

Suleyman has been clear about the group’s direction. In an interview last year, he explained that Microsoft’s AI models are aimed at consumer use rather than the enterprise market. “My logic is that we have to create something that works extremely well for the consumer and really optimise for our use case,” he said. He pointed to Microsoft’s access to large amounts of consumer data—such as ad performance and telemetry—as a strength in training models for everyday companions.

The company has also said that it does not plan to rely on one general-purpose model. Instead, it sees potential in offering multiple specialised models designed for different types of requests. “We believe that orchestrating a range of specialised models serving different user intents and use cases will unlock immense value,” Microsoft AI wrote in a blog post.

Building an AI division

MAI-1-preview builds on earlier small-scale models released under the Phi name. But this marks the first time Microsoft has trained a foundation model of this size from start to finish. The effort reflects how the company has been building out its AI group since hiring Suleyman and many of his former colleagues from the startup Inflection.

Suleyman previously co-founded DeepMind, the research lab Google bought in 2014. In the past year, Microsoft has brought on about two dozen former DeepMind researchers to expand its internal team. The hires show how the company is drawing on talent with long experience in AI development to accelerate its own projects.

For now, Microsoft is positioning its new models as additions to its Copilot ecosystem while it continues to rely on OpenAI for many core features. But the release of MAI-Voice-1 and MAI-1-preview signals a step toward more independence in model development. Analysts say it could also set up a new phase of competition between Microsoft and the company it helped make into an AI giant.

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 part of TechEx and is co-located with other leading technology events, click here for more information.

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Nvidia shares slipped on Wednesday as uncertainty grew around its business in China, caught in the middle of the trade fight between Washington and Beijing.

CEO Jensen Huang said he expects approval to restart sales of Nvidia chips in China after striking a deal with US President Donald Trump to pay commissions to the government. But with no formal rules yet, and doubts about whether Chinese regulators might discourage purchases, Nvidia left potential China sales out of its forecast for the current quarter.

That decision led to an outlook that looked steady but less than what investors have come to expect. Nvidia projected revenue of about US$54 billion for the third quarter, just above Wall Street estimates of US$53.14 billion, according to LSEG data. The forecast was enough to beat analyst targets but fell short of the “blowout” growth the market has grown used to, pushing the stock down 3.2 per cent in after-hours trading. That drop cut about US$110 billion from Nvidia’s US$4.4 trillion valuation.

As reported by Reuters, Huang downplayed concerns that the AI spending surge could be cooling, telling investors the opportunity could expand into a multi-trillion-dollar market over the next five years. “A new industrial revolution has started. The AI race is on,” he said, adding that Nvidia sees $3 trillion to $4 trillion in AI infrastructure spending by the end of the decade.

“Nvidia’s biggest bottleneck isn’t silicon, it’s diplomacy,” said Michael Ashley Schulman, chief investment officer at Running Point Capital. He added the company’s growth is “still impressive, but not as exponential.”

Second-quarter revenue reached US$46.74 billion, above the US$46.06 billion analysts expected. But the data centre segment, a key driver of Nvidia’s growth, missed some estimates. Analysts suggested that big cloud providers may be spending more carefully. Nvidia said around half of its US$41 billion in data centre revenue came from major cloud companies, slightly below Visible Alpha’s estimates of US$41.42 billion.

The company’s forecast also assumed no shipments of its H20 chips to China, even though some licenses to sell them have already been granted. Nvidia said that if geopolitical hurdles ease and orders come in, H20 sales to China could add between US$2 billion and US$5 billion in the third quarter.

“That is a big question mark to watch,” said Ben Bajarin, CEO of consulting firm Creative Strategies.

Analysts also pointed out that Nvidia’s share price, which has risen by about one-third this year, may have created lofty expectations that are hard to meet. “The mega caps are the ones propelling a lot of the capex that Nvidia is benefiting from. But obviously Nvidia still is growing, is able to sell,” said Matt Orton of Raymond James Investment Management, who argued the durability of the AI trade remains intact.

Even so, demand for Nvidia’s chips remains strong. Businesses racing to build generative AI systems continue to buy the company’s processors, which are designed to handle huge amounts of data quickly. CFO Colette Kress said Nvidia’s “sovereign AI” push — aimed at selling AI hardware and software to governments, including outside China — is on track to bring in US$20 billion this year. She added that cloud and enterprise customers could spend as much as US$600 billion on AI in 2025 alone, with total infrastructure spending tied to AI reaching US$3 trillion to US$4 trillion by the end of the decade.

Huang said much of this growth will come from hyperscalers like Microsoft and Amazon, which are expected to spend about US$600 billion on data centres this year. He added that for a US$60 billion data centre, Nvidia can capture roughly US$35 billion in revenue.

Big Tech firms including Meta and Microsoft are spending heavily on AI, much of it flowing toward Nvidia chips. For the current quarter, Nvidia forecast adjusted gross margins of 73.5 per cent, a touch above analyst estimates of 73.3 per cent.

“The data centre results, while massive, showed hints that hyperscaler spending could tighten at the margins if near-term returns from AI applications remain difficult to quantify,” said Jacob Bourne, an analyst at eMarketer.

Shares of rival Advanced Micro Devices, which is developing competing AI servers, also fell 1.4 per cent after Nvidia’s results.

AI enthusiasm, with Nvidia at the centre, has been one of the main drivers of the S&P 500’s rally over the past two years. But the company’s latest report drew a more muted response.

“This is the smallest reaction to an earnings report in Nvidia’s AI incarnation,” said Jake Behan, head of capital markets at Direxion in New York. “While it may not have been a blowout, it’s not a miss.”

Outside China, Nvidia is still seeing strong demand for its H20 chips. Kress said one customer alone bought US$650 million worth during the second quarter.

Huang also said the company’s high-end Blackwell chips are already largely booked through 2026, while its older Hopper processors remain in demand. “The buzz is: everything sold out,” Huang told analysts, describing the pace of orders.

The company also said its board had approved an additional US$60 billion in share buybacks.

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 part of TechEx and is co-located with other leading technology events, click here for more information.

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Apple is exploring a major change for Siri that could bring Google’s Gemini AI models into the iPhone. According to Bloomberg, people familiar with the talks say the two companies have held early discussions about building a custom system to run on Apple’s servers, though no deal is finalised.

The move would mark a shift for Apple, which has long built its digital assistant around its own software. Facing delays in its internal work on generative AI, Apple is considering whether to stick with its homegrown technology or partner with outside firms. The company has also spoken with Anthropic and OpenAI about potential integrations.

A push to catch up in AI

Apple came late to the generative AI race and has struggled to close the gap with rivals. A long-promised Siri update — one that could use personal data to fulfil complex commands and allow users to control devices entirely by voice — was supposed to launch last spring. Engineering problems forced Apple to postpone the rollout by a year.

[See also: Google Cloud expands AI security tools at 2025 Summit]

That failure reshaped how the company manages the project. Siri development was taken away from AI chief John Giannandrea and placed under Craig Federighi, who oversees software, and Mike Rockwell, known for his work on the Vision Pro headset. Together with Adrian Perica, who runs Apple’s corporate development team, they began weighing outside help.

At the same time, Apple is running a “bake-off.” One version of the new Siri, code-named Linwood, uses Apple’s own models. Another, Glenwood, relies on third-party systems.

Apple weighs Google’s Gemini for Siri

While Apple considers multiple options, Google’s Gemini stands out. The model is already being trained to work with Apple’s servers, according to people with knowledge of the talks.

The two companies are rivals in smartphones and operating systems, but they already cooperate in search. Google pays billions each year to be the default search engine on Apple devices — a deal now under antitrust scrutiny. A Siri partnership would extend that uneasy alliance.

Shares of both companies climbed after news of the discussions surfaced. Google rose nearly 3% in New York trading, while Apple gained more than 1%.

A broader AI strategy

Even if Apple brings in Gemini, the company isn’t walking away from its own AI research. Its Foundation Models team is developing new systems, including its first trillion-parameter model. For now, that work is limited to research rather than consumer use.

Apple has also begun folding third-party tools into its devices. ChatGPT is available in iOS 26 for image generation, and the company has scrapped a project to build its own AI coding assistant in favour of using ChatGPT and Anthropic’s Claude.

Still, Apple has tried to keep core AI features — such as Apple Intelligence tools for summarising text or creating custom emoji — under its own control to protect user privacy. If a Siri deal goes forward, any third-party models would run on Apple’s Private Cloud Compute servers, not directly on devices.

Pressure inside Apple

Inside Apple, the uncertainty has created strain. Several members of the Foundation Models team left this summer after chief architect Ruoming Pang departed for Meta, lured by a lucrative offer to join its Superintelligence Labs. Others have started looking for jobs elsewhere.

[See also: iOS 26 vs Android 16: Apple and Google take smartphones in different directions]

Some Apple managers have even floated replacing AI models used beyond Siri, though that idea is not currently in development.

Meanwhile, Apple’s leadership is signalling urgency. At an internal meeting, CEO Tim Cook told employees the company must win in AI and is increasing its investment. On a recent earnings call, he declined to say whether Apple would use third-party models, but his refusal to rule it out suggested the company is seriously considering the option.

What’s next for Apple and Siri

The talks with Google remain preliminary, with no commercial terms in place. But Apple’s willingness to consider outside help shows how far it has fallen behind in AI — and how determined it is to catch up.

For now, Apple is testing whether its own models or those from partners like Google, Anthropic, or OpenAI can finally deliver the smarter Siri it has long promised.

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Google Cloud used its Security Summit 2025 to highlight a wave of new tools aimed at protecting artificial intelligence projects while also using AI to strengthen cybersecurity operations.

The company pointed to the dual challenge facing organisations: securing their AI systems and applying AI to defend against threats. The announcements covered updates in Google’s security portfolio, including Security Command Center, Google Security Operations, Chrome Enterprise, and Trusted Cloud.

Safeguarding AI agents

As AI agents become more common in enterprise environments, Google Cloud introduced new capabilities in its Security Command Centre to monitor and protect them. A preview feature will give teams automated discovery of AI agents and Model Context Protocol servers, flagging vulnerabilities and risky interactions.

Google is also expanding its Model Armor tool to cover prompts and responses in Agentspace, offering real-time defences against threats like prompt injection or jailbreaking. New posture controls for Agentspace and Agent Builder are also on the way, designed to enforce organisational security policies.

To help with ongoing protection, new detections have been added to identify suspicious behaviour in AI agents, drawing on intelligence from both Mandiant and Google.

AI in security operations

The company also shared its vision for an “agentic” security operations centre, where AI-driven agents can coordinate tasks to support human analysts. An Alert Investigation agent, now in preview, can automatically enrich events, analyse command-line inputs, and build process trees, with recommendations for next steps. Google said this could ease manual workloads and reduce response times.

Mandiant Consulting, part of Google Cloud, is expanding its services to address security concerns raised by the rapid use of generative and agentic AI. The firm is offering support in AI governance, environment hardening, and threat modelling. It has also emphasised the role of adversarial testing to identify risks before deployment.

Updates in Google Unified Security

The company’s broader platform, Google Unified Security, also received several upgrades. A new SecOps Labs feature in Google Security Operations will give customers early access to AI-powered experiments for detection and response. New dashboards, now generally available, integrate SOAR data for improved visibility.

Chrome Enterprise added new mobile protections, including URL filtering on iOS and enhanced reporting to track browser activity. The features are intended to help organisations manage employee browsing risks, including use of unapproved generative AI tools.

Cloud security enhancements

On the cloud side, Google announced previews of Compliance Manager and Data Security Posture Management in Security Command Center. The tools aim to simplify compliance monitoring and sensitive data governance, including AI-specific workloads. Risk Reports, also in preview, will summarise potential weaknesses based on simulated attacker techniques.

Identity and Access Management is adding “agentic IAM” later this year, which will provision agent identities in environments. Other updates include a role picker that uses Gemini to suggest least-privilege roles, and re-authentication requirements for sensitive actions.

Data security updates include expanded scanning of AI-related assets and image data, while network security improvements extend Cloud Armour and Cloud NGFW features for broader protection.

Google security focus on responsible AI adoption

The company framed these updates as part of its effort to make AI adoption more secure while using AI itself to enhance defence. By embedding controls into data protection, compliance, and identity systems, Google Cloud said it aims to give organisations a stronger foundation for managing both risks and opportunities in AI.

Want to learn more about cybersecurity and the cloud from industry leaders? Check out Cyber Security & Cloud Expo taking place in Amsterdam, California, and London.

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The Huawei Cloud AI Ecosystem Summit APAC 2025 brought together government leaders, industry experts, and technology partners to discuss how artificial intelligence is already changing the way people work, learn, and live in Malaysia and ASEAN. The gathering highlighted not only new technologies but also the partnerships and governance needed to make AI effective and trustworthy.

The summit is part of the Huawei Cloud APAC AI Ecosystem Initiative, a programme aimed at building an inclusive AI community by developing local skills, encouraging cooperation between sectors, and ensuring AI benefits are shared widely.

Government support for AI development

At the ASEAN AI Summit’s opening day, Huawei Technologies (Malaysia) CEO Simon Sun announced new AI initiatives. Malaysia’s Prime Minister, YAB Dato’ Seri Anwar Ibrahim, was present to witness the launch, underscoring the government’s view that AI is central to the country’s economic growth. The commitment is reflected in strategies that link public and private sectors and aim to prepare the country for a future where AI shapes every major industry.

Huawei Cloud’s three core capabilities

Huawei Cloud has built its AI approach around three capabilities. First, a global network of 34 regions and 101 availability zones (AZs) – including five regions and 17 AZs in ASEAN – provides the infrastructure for low-latency access. Second, an AI cloud service that supports more than 160 open-source models, allowing flexibility for development in different industries. Third, the Pangu multimodal models form the backbone of the company’s “AI for Industries” strategy; tailored solutions for manufacturing, healthcare, transport, among others.

On day two, the AI Ecosystem Summit drew about 300 delegates from the region. Li Yin, CTO of Huawei Cloud Enterprise Intelligence, led a session titled Leap to Cloud, Heading to AI, in which she shared examples of how Huawei Cloud has worked with customers in more than 30 industries and applied AI to over 500 scenarios worldwide.

See also: Huawei to unveil tech to cut China’s reliance on foreign AI memory chips

Li explained that with the Pangu foundational large model, ModelArts AI toolchain, and proven engineering methods, organisations can use own data to develop and refine models quickly. She pointed to three areas where Huawei Cloud will continue to invest: strengthening secure AI computing infrastructure, building industry-focused solutions like enterprise AI assistants and AI video applications, and expanding the partner ecosystem to speed adoption.

Malaysia’s focus on ethical and sustainable AI

Minister of Digital, YB Gobind Singh Deo, used his keynote to make clear that Malaysia’s AI journey is about more than just technology. Ethical use, sustainability, and shared benefit are all priorities.

“Our National AI Office (NAIO) has been speeding up the completion of the AI Technology Action Plan 2026 – 2030 and relevant regulatory frameworks to ensure the adoption of AI technology in key sectors in the country are ethical, sustainable and of high value,” he said.

He linked the goals to the Malaysia Digital Economy Blueprint and the Malaysia Digital (MD) initiative, saying both are strengthened through close cooperation with technology partners. Every step we take is action-driven, grounded in strong public-private collaborations, to shape Malaysia’s digital economy,” he said.

Building Malaysia’s AI talent pipeline

Simon Sun highlighted Huawei’s investment in local expertise through the Huawei Malaysia AI Talent Programme.

“We have set the goal of nurturing 30,000 Malaysian AI talents, comprising students, government officials, industry leaders, think tanks, associations, and others under this initiative in the coming three years,” he said.

He said AI is already making an impact in areas like fraud detection in banking, predictive maintenance in factories, supply chain management, and personalised learning in schools. Huawei’s localised partnerships, he said, ensure global expertise is applied in ways that suit ASEAN’s needs.

Real-world applications from Huawei partners

The summit also gave the stage to Huawei customers, who shared how they use AI in their own sectors.

William Zhou, Vice President of IFLYTEK Open Platform, said that while computing power and platforms form the base of AI systems, the real value comes from the application layer – where solutions are integrated into daily work. He said that Knowledge Q&A systems are among the most requested features from customers in government, telecom, and finance, but said successful deployment depends on close collaboration.

“The key is not the technology alone, but working closely with the customer to fine-tune the model and increase efficiency,” Zhou said, pointing to a Middle Eastern project that improved performance significantly in just two months.

He also described how subtitling and translation tools are vital in multilingual regions, with IFLYTEK solutions optimised for English, Malay, and Cantonese, which enable fast turnaround for media companies in Southeast Asia. In sectors where data must stay on-site, he said the ‘Spark’ all-in-one on-premise AI solution allows organisations to train and run models securely.

Dato Fadzli Shah, Co-Founder of Zetrix, discussed the link between AI, blockchain, and self-sovereign identity. He said these technologies could allow data from separate systems to be referenced securely without forcing organisations to adopt a single standard. Blockchain-backed digital identities, he added, could be used in education, finance, and trade to help ensure credentials remain verifiable.

He said Malaysia should develop specialist AI models trained on local data to ensure accurate interpretation of laws, policies, and cultural contexts. “We believe no single AI will dominate globally; instead, there will be natural product-market fit for specific stacks serving specific solutions.”

Henry Li Nan, Managing Director of TrustDecision Malaysia, shared how AI-powered decision intelligence is helping the finance industry tackle fraud. His company processes more than 130 million interception events a year, protects over seven billion devices, and prevents an estimated USD$10 billion in potential losses annually.

Working with Huawei, TrustDecision uses cloud-native infrastructure to deliver real-time detection, compliance, and risk management services.

“The result is faster detection, smarter prevention, and greater confidence for financial institutions to stay ahead of threats,” Li said.

National AI Office: Matching the speed of change

Shamsul Izhan Abdul Majid, Head of the NAIO, warned that the speed of AI development is unlike anything seen before, with new versions emerging every few weeks. This, he said, means that plans and standards must be developed quickly and in cooperation with industry.

He called data “the most important asset” and said that in sensitive fields like healthcare or defence, Malaysia’s approach is to bring AI to the data rather than move the data to the AI.

See also: Huawei tries to push AI chips abroad as US pressure grows

Since its formation in December last year, the NAIO has worked with six sectors and identified 55 AI potential use cases, with more expected as engagement expands to state and local levels. The office is also promoting the creation of locally-trained models with strong cybersecurity safeguards and a focus on making AI understandable for everyone, not just technical experts.

“Doing AI for everyone requires collaboration,” he said. “The AI Office brings together experts and companies to plan Malaysia’s AI journey for the next five years… We must stay ready, responsible, and innovative.”

Closing call to action

In closing, Simon Sun encouraged all participants to take the ideas shared at the summit and turn them into practical projects. He described the event as “the starting point for more actions and ideas to shape a smarter and stronger ASEAN, powered by AI and driving digital economies.”

The summit’s discussions made one thing clear: AI’s future in Malaysia and ASEAN will depend not only on powerful technology, but on how well it is adapted to real-world needs, governed responsibly, and supported by a skilled and informed community.

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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Instagram’s new location-sharing feature is sparking alarm among some users, who say it could put people at risk by revealing where they are without their knowledge.

The Meta-owned platform quietly added the option on August 6, introducing a map that lets people share their location with friends – a tool similar to one Snapchat has offered since 2017.

It didn’t take long for worried posts to appear online. As reported by AFP, in one widely shared exchange, Instagram user Lindsey Bell said she was shocked to learn her location was visible to her followers.

“Mine was turned on and my home address was showing for all of my followers to see,” she wrote in response to a TikTok warning from reality TV personality Kelley Flanagan. “Turned it off immediately once I knew but had me feeling absolutely sick about it.”

In a TikTok video, Flanagan called the feature “dangerous” and walked viewers through how to disable it.

Instagram chief Adam Mosseri addressed the concerns in a post on Threads, saying the feature is off by default. “Quick Friend Map clarification, your location will only be shared if you decide to share it, and if you do, it can only be shared with a limited group of people you choose,” he wrote. “To start, location sharing is completely off.”

According to Instagram, the map is meant to help people share places they’ve visited and connect with friends. The company says users can choose who sees their location and can turn the feature off at any time.

A privacy concern on the heels of a legal case

The unease over Instagram’s map comes just a week after Meta faced scrutiny in court. A federal jury in San Francisco sided with women who said the company misused health data collected by Flo, a third-party app that tracks menstrual cycles and fertility.

The jury found that Meta knowingly received sensitive health information from the app and used it to target ads. Evidence presented in court included internal communications suggesting that some employees made light of the nature of the data.

“The case was about more than just data – it was about dignity, trust, and accountability,” said Carol Villegas, lead attorney for the plaintiffs.

How the new map works

Instagram’s map sits at the top of the messages inbox. It lets people share their live location while they’re using the app and see the locations of others who have chosen to share.

The company says no one can see a user’s location unless the person opts in. People can also limit the visibility to certain followers or turn it off entirely.

Meta describes the tool as “a new, lightweight way to connect with each other.” Similar functions exist on other platforms – Snapchat offers a personalised map, Apple’s iOS allows users to share locations with contacts, and Meta’s other apps like Facebook and WhatsApp have live location features.

A rocky reception

Despite these reassurances, the rollout has been met with scepticism. Many users, including professional creators, have raised safety concerns, warning that the feature could be misused for stalking or harassment.

The backlash has reached US lawmakers. According to NBC News, Senators Marsha Blackburn and Richard Blumenthal have reportedly written to Meta CEO Mark Zuckerberg, urging him to drop the feature.

Some confusion stems from how the map displays past posts. Users have reported seeing their older posts – ones with location tags – appear on the new map, even live location sharing enabled.

Mosseri explained that this is because the map includes both real-time locations and past posts with location tags. Those tags were already public to followers but weren’t previously collected in one place.

When location tags become personal

Allie Taylor, an educator who shares disability-related content on Instagram, said they learned about the map when followers messaged to say their location was visible. Taylor had posted a video tagged with the city of Cincinnati while at work. The map appeared to pinpoint the street they were on.

“It was terrifying,” Taylor said. “Why was this even a feature?”

Turning it off

There are several ways to disable location sharing. In Instagram, users can go to the messages inbox, open the map, tap the settings icon, and select “no one” for location sharing.

On a phone, location services for Instagram can be turned off entirely in the device’s settings.

Instagram promises changes

Mosseri has acknowledged the confusion and said the company will make the feature clearer. “We’re never going to share your location without someone actually actively asking to do so,” he said in a post last Friday.

In a statement, Meta said: “Instagram Map is off by default, and your live location is never shared unless you choose to turn it on. If you do, only people you follow back – or a private, custom list you select – can see your location.”

Mosseri also admitted that Instagram could “do a better job” explaining what appears on the map. “We can, and will, make it easier to understand exactly what’s happening,” he wrote, adding that improvements are planned for early next week.

Balancing connection and safety

The feature’s intent – to make it easier for friends to meet up and share experiences – is not new in social media. Apps have long offered ways to share location, from Snapchat’s Snap Map to Apple’s “Find My” function. The tools have drawn both praise for making coordination easier and criticism for the risks they pose when misused.

For Instagram, the challenge lies in ensuring that users understand exactly what they are sharing, with whom, and how it appears on the map. The backlash suggests that many people either missed or misunderstood the opt-in nature of the feature, especially when older posts appeared without warning.

Privacy advocates often caution that location data is especially sensitive. While a post tagged at a restaurant may seem harmless, patterns over time can reveal personal routines, places of work, or home addresses. The makes clear controls – and clear explanations – vital.

Instagram says it will continue to refine the map and its settings. Whether that will be enough to restore user confidence remains to be seen. In the meantime, those concerned about privacy have the option to disable location sharing entirely, either in the app or through phone settings.

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Huawei is expected to unveil a technology that could lessen China’s dependence on high-bandwidth memory (HBM) chips for running artificial intelligence reasoning models, according to the state-run Securities Times.

As reported by the South China Morning Post, the announcement will be made at the 2025 Financial AI Reasoning Application Landing and Development Forum in Shanghai today. The event focuses on AI in the financial sector.

Huawei did not respond to a request for comment on Monday. If confirmed, the development would mark another step by the US-sanctioned company in strengthening China’s AI hardware capabilities and reducing reliance on foreign technology.

HBM chips are a key component in advanced AI systems, particularly for running reasoning models. The models take an already-trained AI system and apply it to real-world data, making decisions based on patterns the AI has learned. HBM is important for these workloads because it can move large amounts of data quickly between the processor and memory.

The current market for HBM is dominated by US companies Micron and AMD, as well as South Korean firms Samsung Electronics and SK Hynix. The chips are often integrated directly into AI processors used in data centres.

China’s two main memory chip producers, Yangtze Memory Technologies and Changxin Memory Technologies, have expanded their capabilities, but analysts say they are still behind their US and Korean competitors in technical performance. That gap has left China dependent on imports for the most advanced HBM products, an issue made more pressing by US export controls on advanced chipmaking tools and technologies.

While China works to strengthen its domestic supply chain, demand for HBM worldwide is rising sharply. Orders have surged as major tech companies build more AI data centres.

Micron, one of the top HBM producers, raised its forecast for fourth-quarter revenue and profit on Monday, citing strong demand for AI infrastructure. The company now predicts $11.2 billion revenue, plus or minus $100 million, up on its earlier estimate of $10.7 billion. Adjusted earnings per share are forecast at $2.85, plus or minus 7 cents, up from a prior estimate of $2.50.

Micron also increased its adjusted gross margin outlook to 44.5%, from 42%, plus or minus 1%, pointing to stronger pricing notably in DRAM product lines.

“We look at all of our different end markets around the world, the pricing trends have been robust, and we have had great success in being able to push that pricing up,” said Sumit Sadana, Micron’s chief business officer, during an industry event on Monday.

Analysts say the combination of limited HBM supply and surging AI demand has allowed producers to raise prices – a reversal from past years when memory chipmakers faced shrinking margins.

SK Hynix, another leading HBM supplier, expects the market for AI-focused memory chips to grow by about 30% per year until 2030.

Trade measures could still affect the sector. The US recently imposed 100% tariffs on certain imported chips, although the duties will not apply to companies that manufacture in the US or have committed to doing so.

In June, Micron said it would increase its planned US investment by $30 billion, bringing its total commitment to $200 billion in the country.

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OpenAI’s newest model, GPT-5, is now available to all users – including those on the free tier. The company says GPT-5 works faster, answers better, and is more useful for tasks like writing, coding, and helping in areas like health care.

OpenAI CEO Sam Altman said he didn’t enjoy switching back to GPT-4 after using the latest model. “I tried going back to GPT-4, and it was quite miserable,” he told reporters during a recent briefing.

ChatGPT, OpenAI’s chatbot powered by its language models, is now used by around 700 million people weekly. The company is also in early talks with investors about a possible stock sale that could value it at $500 billion, according to CNBC.

One of the key changes in GPT-5 is how often it “hallucinates” – a term used when AI makes up information. OpenAI says this happens less often with the new model. The company also ran more than 5,000 hours of safety tests while building it.

GPT-5 also takes a different approach when faced with risky or sensitive questions. Rather than refusing to respond entirely, the model offers a general response that avoids giving harmful details. “GPT-5 has been trained to recognise when a task can’t be finished, avoid speculation and can explain limitations more clearly,” said Michelle Pokrass, who works on post-training at OpenAI.

During the demo, the company showed how GPT-5 could turn simple prompts into working software. They asked it to create a language learning app to help English speakers study French. The prompt called for features like flashcards, quizzes, a fun theme, and progress tracking. Two separate GPT-5 sessions produced different versions of the app in seconds.

The apps needed a bit of cleanup, an OpenAI staffer said, but users can make changes easily – like adjusting the layout or adding new tabs.

The release marks the first time free ChatGPT users will get access to a model with reasoning capabilities – meaning it runs an internal thought process before replying. If they hit their use limit, they’ll be shifted to GPT-5 mini, a smaller version of the same model.

Subscribers to the Plus plan get more use room, and Pro users can access GPT-5 without limits, as well as GPT-5 Pro, a higher-tier version. Enterprise and education customers will start getting access about a week after the public rollout.

Microsoft, OpenAI’s close partner and investor, is bringing GPT-5 into its own products. A company blog post said GPT-5 will power Microsoft 365 Copilot and Azure’s AI tools. On social media, Microsoft CEO Satya Nadella reflected on how far AI has come since Altman visited Microsoft’s headquarters in 2023 to present GPT-4.

Other companies are already testing the new model. Box, which makes file management software for businesses, tried GPT-5 on large sets of data. CEO Aaron Levie said older models had trouble understanding long documents that involved complex math or logic, but GPT-5 handled them better. “The model is able to retain way more of the information that it’s looking at, and then use a much higher level of reasoning and logic capabilities to be able to make decisions,” he said in an interview with CNBC.

OpenAI is also giving developers three different versions of GPT-5 through its API: the standard model, GPT-5 mini, and GPT-5 nano. The are designed to support different needs when it comes to speed and cost.

Earlier in the week, the company also released two open-source language models, the first time OpenAI has released models like this since GPT-2 launched in 2019. The new models are meant to be easier and cheaper to use, especially for developers and researchers.

Altman called the two open-source models – GPT-OSS-120b and GPT-OSS-20b – “a big deal,” saying on social media that they’re “the best and most usable open models in the world.”

The release into the open came as China’s AI firms continue to release more open-source models. Companies like Alibaba Cloud have built popular model families, like Qwen, that are gaining international attention. According to Bloomberg, OpenAI’s recent moves – including GPT-5 and the open models – are part of a broader strategy as it considers a new stock sale.

OpenAI said its two open models perform about as well as o4-mini and o3-mini, which are among its smaller reasoning models. The release of open models suggests the company is returning to its original goal of making AI more accessible to the public – an effort many saw as slowing down in recent years. However, China appears to have the upper hand in terms of the number of competitive open models available.

“In the open-source space overall, China still has an edge over the US in the number of highly competitive models available,” said Ray Wang, a research director at consultancy Futurum Group. He added that OpenAI’s move might put pressure on its Chinese competitors.

The open-source trend picked up speed after Hangzhou-based DeepSeek introduced two low-cost, high-performance models in late 2023 and early 2024. That moment reportedly led Altman to question whether OpenAI had made the right call by not pursuing open-source releases as much as its competitors.

In the weeks since, more Chinese AI companies have entered the spotlight. Alibaba upgraded its Wan video generation tool and released Qwen-Image, a model that improves on previous iterations’ ablities at reading and editing text inside images. Zhipu AI, based in Beijing, launched GLM-4.5, which it says ranked third globally and first in China in a series of benchmarks. Another Beijing firm, Moonshot AI, released the Kimi 2 model last month, which has 1 trillion parameters – far more than OpenAI’s open-source offerings.

Altogether, China now has 1,509 AI models, both open and proprietary, according to data from the 2025 World Artificial Intelligence Conference in Shanghai.

OpenAI’s open-source models are getting attention in China too. A discussion thread about the models on Zhihu, a Chinese Q&A site, received over 250,000 views. Some local companies are paying close attention. Zhipu referred to the new models as “game changers.”

While GPT-5 and the open-source models are getting most of the attention, Altman says there’s more to come. He believes GPT-5 represents a step forward not just in speed and quality, but in how natural it feels to talk to.

“I think having something like GPT-5 would be pretty much unimaginable at any previous time in human history,” he said.

Rival companies are also claiming breakthroughs. Last month, Elon Musk said the latest version of Grok was “better than PhD level in everything” and described it as the “smartest AI” to date.

OpenAI is also promoting GPT-5 as a helpful coding assistant – part of a wider trend among US firms aiming at software developers. Anthropic’s Claude Code is one example of a model focused on similar tasks.

Altman said one major shift is how AI is changing what people can do with simple ideas. “People are limited by ideas, but not really the ability to execute, in many new ways,” he said.

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Apple’s latest results showed a rebound in iPhone sales and a recovery in China, giving a lift to two areas that had been under pressure over the past year.

The better-than-expected quarter helped calm investor concerns about the company’s core business, even as it works to catch up with rivals in artificial intelligence and prepares for potential tariffs under President Donald Trump. As reported by CNN, CEO Tim Cook told analysts that tariffs could cost Apple $1.1 billion in the September quarter, up from $800 million in the last quarter.

For the three months ending in June, iPhone sales brought in $44.5 billion, topping analyst estimates of $40 billion and last year’s $39.3 billion for the same period. Overall revenue reached $94 billion, up 10%. In China, sales grew from $14.7 billion in the third quarter of 2024 to $15.3 billion.

Apple’s stock gained just over 2% in after-hours trading. That’s far less than Microsoft and Meta, which saw jumps of nearly 7% and over 9% on Wednesday after their financial announcements. Apple’s stock is down almost 15% this year, missing out on much of the broader tech rally.

A decade ago, a jump in iPhone sales might have been enough to spark excitement on Wall Street. Now, analysts are pressing Cook on how Apple plans to keep the iPhone relevant as AI changes how people interact with devices.

“It’s difficult to see a world where iPhone’s not living in it,” Cook said when asked about a future where people might rely more on voice assistants than screens. He said that Apple sees devices as working alongside each other, not replacing each other.

iPhone still at the centre

The iPhone remains Apple’s biggest source of revenue and a key focus for investors. Cook said the company set a record for June quarter iPhone sales, growing 13% from last year.

Shifting trade policies have forced Apple and other electronics makers to rethink manufacturing. To avoid new tariffs, Apple moved most production of US-bound iPhones from China to India earlier this year. Smartphones were previously exempt from a planned 145% tariff rate, but Donald Trump has warned that Apple and Samsung could face a 25% tariff unless they produce hardware in the US. A temporary deal has kept tariffs at 30% until August 12, though Trump recently suggested tariffs on India could also reach 25%.

Cook said Apple’s production approach hasn’t changed since last quarter, with “the vast majority” of iPhones sold in the US now coming from India. He also pointed out that around 19 billion chips are currently made in the US.

Pushing forward on AI

While tariffs are a near-term issue, Apple is also dealing with concerns over its AI strategy. The company has faced criticism for trailing behind rivals like Google, Microsoft, and Meta, who have moved faster in developing AI products.

A planned major upgrade to Siri has been delayed indefinitely, keeping the voice assistant behind newer AI systems like ChatGPT and Gemini. Cook told analysts that Apple is making “good progress” and plans to roll out the updated Siri next year. Current AI features are spread in Apple’s products, with tools like custom emoji creation, text summarisation, and image generation – features that add convenience but are far from the impact felt by users of the top AI platforms.

“We are also significantly growing our investments,” Cook said. “Apple has always been about taking the most advanced technologies and making them easy to use and accessible for everyone. And that’s at the heart of our AI strategy with Apple Intelligence.”

Bloomberg reported recently that Apple has lost several AI researchers to Meta, which has been expanding its AI team. Cook said the company has reassigned “a fair number of people to focus on AI” and has acquired seven companies this year, though not all are AI specialists.

Recently, analysts at Lightshed Partners questioned whether Apple should consider replacing Cook with a CEO more focused on product development.

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For years, smartphones from Apple and Google have followed a similar formula. Whether you picked an iOS or an Android device, the basic setup didn’t change much: a grid of apps, swipe-able screens, and occasional visual updates. But with the arrival of Apple’s iOS 26 and Google’s Android 16 this year, the two companies are starting to go in separate directions – not just in how their software looks, but in what it does.

Apple’s new operating system, coming this autumn, introduces a fresh look called “Liquid Glass.” The interface now blends into the background with translucent menus and soft visuals that make icons and buttons seem to float on the screen. It’s meant to feel clean and elegant and to offer a consistent experience on iPhones, iPads, and Macs. For Apple, the focus is on refining design – a move that plays to its reputation for polished aesthetics.

Google’s Android 16 update is going in a different direction. It brings in “Material 3 Expressive,” a brighter, louder design language that puts bold colours front and centre. Users can customise their phones with vivid themes – pink windows, violet buttons, and colourful highlights that reflect a more playful approach. Google says it wants Android to feel emotional and dynamic, with a user interface that feels more personalised.

But design changes only scratch the surface of what’s shifting. Under the hood, Android 16 is taking a big step into artificial intelligence. Google has integrated its Gemini AI assistant into the operating system whether asked for or not, acting as users write emails, edit images, generate lists, or providing suggestions drawing from and integrated into separate apps. Gemini is present in Google’s core apps and continues working in the background, offering its input before users ask for it.

A new “AI Mode” uses personal data – like calendar events, recent searches, or photos – to make suggestions. Google says it handles data “responsibly,” but some users may not be comfortable with a system that watches so closely. There’s a balance between useful and intrusive, and it remains to be seen how Android users will respond.

Meanwhile, Apple’s AI approach is more cautious. The company has introduced a few new features through its Apple Intelligence system, like real-time language translation during FaceTime calls or text conversations, and the ability to scan a screenshot and suggest next steps. For instance, take a screenshot of a concert flyer and your phone might prompt you to add the date to your calendar. Or snap a handbag you’re eyeing and get a link to shop for similar items.

These may be helpful additions, but they’re not new to Android users. Google rolled out real-time translation tools in 2021 and has long-offered visual search through features like Circle to Search, where users can draw around an object to find related images online. Some have called that feature more of a novelty than a necessity, but it’s an example of how Android tends to experiment early.

One feature that’s notably absent from iOS 26 is an updated version of Siri. Apple had been working on a new AI-powered Siri meant to compete with Gemini, but internal testing showed it got nearly one in three responses wrong. Google’s Gemini has suffered from its own issues, but the company remains fully committed to AI.

Apple has postponed the relaunch of Siri, and in the latest version of iOS will remain mostly unchanged. Apple users can send some questions to ChatGPT, but the integration is still basic.

All of this points to a wider shift in direction, and Apple seems more focused on design, consistency, and privacy. The company wants its devices to feel intuitive and stable, with AI features that stay in the background. Google is more willing to take risks, putting AI at the centre of the experience in an attempt to turn smartphones into what it frames as active assistants.

The divide means your choice of phone could shape how you use technology in the coming years. If you prefer a system that purports to be able to automate tasks and can make suggestions based on large language models, Android may offer more right out of the box. If you want a clean, visually polished interface with tighter control over how your data is used, with less AI input, iPhones may be a better fit.

What’s clear is that the days of Apple and Google moving in lockstep are over. With iOS 26 and Android 16, the two mobile giants are no longer trying to match each other feature for feature. They’re building different futures – and users will have to decide which one fits them best.

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