Tag: AI

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Corporate

DeepSeek Huawei team up on AI chip software

Chinese artificial intelligence company DeepSeek has partnered with Huawei Technologies to develop programming tools for Huawei’s Ascend AI chips, marking a fresh step in China’s push to build a stronger domestic AI technology ecosystem.

The partnership focuses on the software needed to make AI chips easier and more efficient to use. DeepSeek has released open-source programming infrastructure for Huawei’s Ascend platform, covering tools designed to support computation and communication between chips.

The move is significant because advanced AI hardware needs a strong software ecosystem to reach its full potential. Nvidia has built a major advantage through its CUDA software platform, which developers widely use to program and optimise AI workloads on Nvidia GPUs. DeepSeek and Huawei are now working on alternatives designed specifically for Chinese AI processors.

A key part of the collaboration is TileLang, an open-source programming language developed to simplify the process of programming AI chips. DeepSeek says the language allows developers to work at a higher level while still accessing the performance of the underlying hardware.

The goal is to make it easier to develop and optimise AI applications without relying heavily on Nvidia’s software ecosystem. DeepSeek has described the development of such programming infrastructure as an important step towards creating a more independent AI computing ecosystem.

The companies have also worked together on a computing system built around 128 Huawei Ascend 950 chips. Known as a “supernode”, the system is designed to allow a large number of AI processors to work together, improving computing and communication between the chips.

Huawei provided support for the programming infrastructure used by the system, according to DeepSeek. The development comes shortly after Huawei unveiled its next-generation AI processors and supernode systems, highlighting the company’s growing focus on large-scale AI computing.

The partnership also builds on earlier cooperation between the two companies. DeepSeek has been working to adapt its AI models to Huawei hardware, including its V4 model, which supports Huawei’s Ascend platform.

That shift is important because AI models require much more than powerful chips. Developers also need programming languages, compilers, libraries and communication systems that allow processors to work together efficiently. A strong software layer can reduce the amount of time developers spend rewriting and optimising applications for different hardware platforms.

TileLang is aimed at addressing part of that challenge. By providing a common programming framework, DeepSeek hopes developers can more easily build applications for Huawei’s AI chips while maintaining greater control over how the hardware is used.

The development comes against the backdrop of growing competition between China and the United States over advanced semiconductor and AI technology. Restrictions on the export of some advanced US chips and technology to China have pushed Chinese companies to accelerate the development of domestic alternatives.

Huawei has emerged as one of the key players in that effort, particularly through its Ascend AI chip range. DeepSeek’s involvement adds the expertise of one of China’s most closely watched AI companies to the software side of Huawei’s semiconductor strategy.

Open-source development could also help the new ecosystem attract more developers. Giving programmers access to the underlying tools allows them to experiment, adapt the software and contribute improvements. A larger developer community could eventually help expand the number of applications that can run efficiently on Huawei hardware.

Still, building a credible alternative to Nvidia’s established ecosystem will take more than releasing new software. Developers will look at performance, reliability, compatibility, documentation and hardware availability before moving large AI workloads to a new platform.

The 128-chip Ascend 950 supernode is an important technical development, but its chip count alone does not establish how it compares with Nvidia-based systems. Meaningful comparisons would require independent testing under similar workloads, hardware configurations and software conditions.

The DeepSeek-Huawei partnership therefore represents a broader shift in China’s AI strategy. The focus is moving beyond simply producing domestic AI chips towards building the software and infrastructure needed to make those chips competitive and practical at scale.

DeepSeek brings experience in developing and optimising large AI models, while Huawei brings its Ascend processors and computing infrastructure. Their collaboration aims to connect those two strengths through a stronger software layer.

The bigger challenge is reducing dependence on established foreign technologies while giving developers a practical alternative. Success will depend on how quickly the tools mature and how widely they are adopted by China’s growing AI industry.

China’s AI chip race is consequently becoming a race over software as much as hardware. Powerful processors need efficient programming tools, and DeepSeek and Huawei are betting that an open-source ecosystem can help close that gap.

The latest partnership could give Chinese developers another route to build and run AI systems using domestic technology, while adding momentum to Huawei’s wider effort to develop an alternative AI computing ecosystem.

 

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Beyond

AI giants face lawsuit over alleged slowdown pact

Four of the biggest names in artificial intelligence, Anthropic, OpenAI, SpaceXAI and Google,  are facing an antitrust lawsuit in the United States over allegations that they agreed to slow the pace of AI development.

The lawsuit, filed in the US District Court for the Northern District of California, was brought by four people who pay for ChatGPT, Claude, Grok or Gemini. They are seeking to represent a wider group of paid subscribers across the country.

The case is a growing debate inside the AI industry: how quickly should increasingly powerful AI systems be developed, and can rival companies work together to make that process safer without breaking competition laws?

The plaintiffs allege that the four companies crossed an antitrust line by coordinating efforts to slow their AI development. They argue that if competing companies collectively agree to reduce the pace at which their products improve, consumers could receive less value from the AI services they pay for.

The lawsuit does not challenge the companies’ right to slow their own development independently because of safety concerns. Instead, the plaintiffs argue that competing firms should not agree among themselves to restrain development.

The immediate trigger for the case was a statement by Anthropic CEO Dario Amodei on September 12. Amodei called for cooperation among leading AI companies to slow advances in AI capabilities and give safety measures more time to catch up.

The proposal quickly received public support from OpenAI CEO Sam Altman, SpaceXAI CEO Elon Musk and Google DeepMind co-founder and chair Demis Hassabis. The lawsuit points to those responses as evidence of coordination among major AI rivals.

The plaintiffs also allege that discussions about slowing AI development started earlier. Their complaint points to a statement from July signed by senior employees from several leading AI laboratories. That statement acknowledged the intense competitive pressure companies face when considering whether to slow development on their own.

According to the lawsuit, this creates a difficult competition problem. If one company slows its AI development alone while its rivals continue moving ahead, it could lose customers and market share. The plaintiffs argue that an agreement among several competitors removes that competitive pressure.

The companies, however, have been discussing the issue primarily from a AI safety perspective. The argument from industry leaders is that the technology is advancing rapidly and that safety testing, evaluation and safeguards need to keep pace.

Amodei has warned about the possibility of increasingly capable AI systems being used in cyberattacks, biological threats and other harmful activities. He has argued that leading AI developers should have more time to evaluate increasingly powerful models before pushing them further.

The Anthropic chief also acknowledged that cooperation between competing companies could raise antitrust concerns. He suggested that the US government could help facilitate discussions or provide a limited legal framework for certain safety-related cooperation.

Altman has separately supported the idea of a federal framework establishing consistent AI safety requirements. OpenAI has said such a framework could provide greater confidence around safety work, while arguing that companies should not necessarily have to wait for new legislation before working on safety measures.

That tension is now at the centre of the lawsuit. US antitrust law is designed to protect competition and prevent businesses from making agreements that improperly restrict the market. The legal question will include whether safety-related cooperation between competing AI companies can be treated differently from an agreement that limits competition.

The case also raises questions about the future of AI regulation. The technology industry is under pressure to address concerns about powerful AI models while continuing to invest heavily in new systems. Companies face a difficult balance between moving quickly, keeping up with rivals and introducing stronger safety measures.

The lawsuit could therefore become important beyond the four companies named in the case. A court decision could help clarify how US antitrust rules apply when competing AI companies cooperate on safety standards, testing or development limits.

The plaintiffs are seeking to represent a nationwide class of paying subscribers. Their argument is that customers could be affected if competition between major AI platforms is reduced and improvements in services become slower than they otherwise would have been.

The companies have not immediately responded publicly to the lawsuit in detail, according to reports. The case is at an early stage, and the allegations have not been established in court.

The dispute comes at a time when ChatGPT, Claude, Grok and Gemini are competing for users, businesses and developers. Their rivalry has helped drive rapid advances in generative AI, but it has also increased concerns over safety, regulation and the risks of developing increasingly capable systems.

The lawsuit now puts that wider debate before a US court: whether AI companies can cooperate to address genuine safety concerns while still maintaining the competition that drives innovation.

 

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Technology

Google tests paying publishers for AI answers

Google is testing a new way to pay publishers whose content helps power its artificial intelligence responses, marking a significant shift in how the search giant may value online content in the AI era.

The programme, called the AI Contribution Pilot, is being offered to a limited group of publishers through Google Search Console. Participating websites receive a new earnings section showing how much they have earned from their content contributing to responses across Google AI Overviews, AI Mode and the Gemini app.

The pilot is still in its early stages and Google has not opened it to publishers generally. Industry reports indicate that dozens of publishers have been approached, with the programme appearing to attract particular interest from small and mid-sized publishers. The participating websites are not limited to news organisations, suggesting that Google is testing a broader model for compensating websites whose information is used by its AI systems.

The basic idea is simple: when a publisher’s material makes a meaningful contribution to an AI-generated answer, Google can assign value to that contribution and make a payment. This is different from the traditional search model, where publishers generally depend on users clicking a Google result and visiting their websites to generate advertising or subscription revenue.

Google has described the initiative as an early-stage learning pilot designed to explore how it can reward high-quality content while continuing to provide publishers with traffic and tools. The company has also said it wants to work with websites whose material helps keep its generative AI answers fresh and accurate.

There is, however, an important catch. Publishers can see a monthly earnings figure in Search Console, but Google currently provides little information about how that amount is calculated. The absence of a clear payment formula has already raised questions among publishers about transparency and whether the amounts being offered properly reflect the value of their content.

The system is therefore closer to a pay-per-value or usage-based AI licensing model than a conventional licensing agreement with a fixed annual fee. Publishers do not appear to receive a large upfront payment. Instead, earnings are linked to how Google assesses the contribution of their content to AI responses. Participants can also opt out of the programme.

That distinction matters because Google’s AI products are changing how people consume information online. A user who once searched for a question, opened several websites and read their articles may now receive a complete answer directly on Google through an AI Overview or AI Mode. The change can save users time, but it also creates a difficult business problem for publishers.

Publishers spend money on reporters, editors, researchers, photographers and technology to create the information that AI systems rely on. If users receive the substance of that work without visiting the original website, publishers can lose valuable search traffic, advertising opportunities and potential subscribers.

Recent research has added weight to those concerns. A field experiment published in August found that removing Google’s AI Overviews and AI Mode increased click-through rates to publishers, while an AI Mode-only experience reduced referrals. The findings underline the growing tension between convenient AI search and the economics of the websites that supply the information behind it.

Google has been expanding its measurement tools at the same time. Its Search Console now includes reporting around visibility on generative AI surfaces, giving websites more information about how their content appears in Google’s AI experiences. The new payment pilot takes that relationship a step further by attaching a financial value to some of that AI exposure.

The development also comes as Google faces growing regulatory and legal pressure over the use of publisher content in artificial intelligence. European regulators have been seeking views from publishers on Google’s AI search opt-out system, which allows websites to prevent their content from being used for AI-generated summaries without affecting their traditional search rankings.

The payment experiment could therefore serve several purposes at once. It gives Google a way to test how a future AI content licensing market might work, while giving publishers an opportunity to receive some compensation for material that contributes to AI answers.

Some publishers see that as an important first step. Even if the current payments are small, the fact that Google is testing direct compensation could establish a new precedent: content used by AI systems can have measurable economic value.

Others remain sceptical. Without greater transparency around the calculation of payments, publishers may find it difficult to determine whether the programme offers a fair return. Some industry executives have reportedly described early payouts as too small compared with the advertising revenue their content generates.

 

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Beyond

China spy chief warns AI poses national security risks

China’s top intelligence official has issued a strong warning about the national security risks posed by artificial intelligence, saying the rapidly developing technology could become a powerful tool for cyberattacks, disinformation and what he described as “cognitive warfare”.

Chen Yixin, China’s Minister of State Security, outlined the concerns in an article published in China Cyberspace, a journal linked to the country’s internet regulator. His comments represent one of Beijing’s clearest warnings yet about the dangers posed by advanced AI.

Chen said artificial intelligence has become a new arena for strategic competition between major powers. He warned that hostile groups could exploit generative AI to create and spread political rumours, manipulate public opinion and encourage social divisions on a much larger scale.

The concern goes beyond ordinary misinformation. Chen specifically pointed to AI-generated images, videos and audio, along with automated online accounts that can flood social media with misleading content.

Such tools could make it easier to create convincing deepfakes of political leaders or public figures. A fabricated speech or video, if widely circulated before it can be disproved, could create confusion and potentially trigger a political or social crisis.

Chen described these activities as a form of public opinion and cognitive warfare. He said they could directly affect China’s political, institutional and ideological security.

The warning comes as artificial intelligence becomes increasingly central to the global competition between China and the United States.

China has made AI a strategic priority and is investing heavily in advanced models, chips and computing infrastructure. At the same time, Beijing is trying to reduce its dependence on foreign technology, particularly advanced semiconductors needed to train powerful AI systems.

Chen said China must strengthen its ability to control key technologies and protect its technological independence.

Cybersecurity is another major concern highlighted by the intelligence chief.

Chen warned that advances in AI could lower the technical expertise and financial resources needed to launch sophisticated cyberattacks. Powerful AI systems could potentially help attackers identify weaknesses, write malicious code and target computer networks much faster.

That could put critical infrastructure at greater risk. Energy systems, financial networks, communications infrastructure and government databases could all become potential targets.

Chen specifically referred to advanced AI models developed by US companies, including systems from Anthropic and OpenAI. He warned that increasingly capable models could create serious risks for China’s critical information infrastructure.

The Chinese security ministry is also worried about sensitive information being collected and analysed with the help of AI.

Chen said foreign intelligence agencies could use automated web crawlers, data-mining systems and AI-powered profiling tools to gather information on national databases, business secrets and citizens’ personal information.

The concern reflects a broader issue surrounding the rapid growth of AI: the same technology that can improve productivity and research can also make surveillance, intelligence gathering and cyber operations more powerful.

AI is also changing the nature of modern warfare, according to Chen.

He warned that countries able to use AI for faster sensing, analysis and targeting could gain a major advantage on the battlefield. This has made AI warfare and military AI increasingly important parts of the competition between major powers.

The warning comes at a sensitive moment in US-China relations.

Washington and Beijing are expected to discuss AI governance and other issues as the two countries attempt to manage growing technological competition. US technology leaders have also been debating whether the development of increasingly powerful AI systems should be slowed or subjected to tighter safeguards.

Anthropic CEO Dario Amodei has recently called for a slower pace of development for advanced AI models. OpenAI CEO Sam Altman and other technology figures have also raised concerns about the risks associated with increasingly powerful systems.

Amodei has argued that maintaining a technological lead over China is important for US security. China, however, has rejected what it sees as attempts to use concerns about AI safety to restrict its technological development.

Chinese Foreign Ministry spokesperson Guo Jiakun said that “fearmongering, confrontation and vicious competition” would harm efforts to establish global AI governance.

Beijing has instead called for greater international cooperation on AI rules. Chen urged stronger safeguards and a more robust system of global AI governance while arguing that China must protect its own technological and security interests.

The contrast highlights the complicated position China occupies in the global AI debate. Beijing wants to become a leader in artificial intelligence while also warning about the technology’s potential dangers.

China’s leadership has increasingly linked AI with national development, economic competitiveness and military strength. At the same time, officials are becoming more vocal about the risks created by advanced AI systems.

The latest warning therefore reflects more than concern about deepfakes or online misinformation. It shows that Beijing increasingly sees artificial intelligence as both an economic opportunity and a national security challenge.

The biggest fear is that AI could make existing threats faster, cheaper and harder to detect. A single sophisticated system could potentially generate large volumes of false information, analyse huge amounts of sensitive data or assist cyberattacks at a scale that would have been difficult to achieve manually.

As China and the US compete for leadership in artificial intelligence, the technology is moving beyond the world of chatbots and productivity tools.

It is becoming part of the wider contest over cybersecurity, military power, information control and technological independence.

 

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Beyond

BRICS declaration focuses on terror, AI and trade

BRICS leaders have adopted the New Delhi Declaration 2026, bringing the expanded grouping together on issues ranging from terrorism and global trade to artificial intelligence, West Asia and reform of international institutions.

The declaration was adopted unanimously at the 18th BRICS Summit in New Delhi, despite differences among member countries over several geopolitical issues. India, which held the BRICS chair this year, pushed for a broader focus on practical cooperation and a stronger voice for developing countries.

The 45-page declaration does not create a common BRICS currency, one of the most closely watched possibilities surrounding the grouping. Instead, members agreed to deepen the use of local currencies for trade and investment and work towards making their payment systems more compatible.

Strong condemnation of Pahalgam terror attack

Terrorism was one of the clearest areas of agreement at the summit. BRICS leaders strongly condemned the April 22, 2025 terror attack in Jammu and Kashmir’s Pahalgam, in which 26 people were killed.

The declaration called for zero tolerance towards terrorism and rejected double standards in dealing with terrorist groups. It also highlighted the need to tackle cross-border movement of terrorists, terrorist financing and safe havens.

The grouping called for all those involved in terrorist activities and their support networks to be held accountable. It also backed faster progress towards the long-pending Comprehensive Convention on International Terrorism at the United Nations.

The reference to Pahalgam is significant for India, which has repeatedly sought stronger international action against cross-border terrorism.

BRICS takes aim at tariffs

Trade emerged as another major issue. BRICS expressed serious concern over the growing use of unilateral tariffs and non-tariff barriers, saying such measures can distort global trade and are inconsistent with World Trade Organization rules.

The declaration called for a stronger and more responsive WTO, particularly one that takes into account the interests of emerging markets and developing economies.

The grouping also opposed unilateral economic sanctions that are not authorised by the UN Security Council. Such measures, it said, can have wider effects on food security, healthcare, development and vulnerable populations.

The declaration did not directly name the United States or President Donald Trump. Its criticism of unilateral tariffs, however, comes against the backdrop of growing global trade tensions and the US use of tariffs as an economic policy tool.

No common BRICS currency

Talk of a common BRICS currency has gained attention in recent years, particularly as members explore ways to reduce their dependence on the US dollar.

The New Delhi summit stopped short of such a move. Instead, members agreed to promote local-currency settlements, improve cross-border payment systems and continue work through the BRICS Payment Task Force.

The New Development Bank was encouraged to increase financing in local currencies and diversify its funding sources. A phased and consensus-based New Investment Platform will also be developed.

India’s proposal to establish a BRICS Risk Lab at GIFT City in Gujarat received support, adding another element to the bloc’s financial cooperation agenda.

AI gets bigger role

Artificial intelligence has also become a major part of the BRICS agenda.

Leaders recognised AI as an important driver of economic growth and sustainable development but stressed that its benefits should be accessible to developing countries. The declaration called for AI systems that are safe, secure, inclusive and reliable.

The grouping also highlighted the need for international cooperation on AI research, innovation, energy efficiency and responsible use.

India’s AI Impact Summit, held in February 2026, was recognised as an important contribution to discussions on global AI governance.

China also proposed deeper cooperation in the field, including an AI Open Source Zone. The growing focus on AI reflects how technology is becoming closely linked with economic competitiveness, development and national security.

West Asia remains a concern

The continuing conflict and instability in West Asia also featured prominently in the declaration.

BRICS called for dialogue and diplomacy to resolve international disputes and stressed the importance of preventing further escalation. The grouping backed a two-state solution for Palestine, based on the 1967 borders with East Jerusalem as the capital of a Palestinian state.

The declaration also supported Palestine’s full membership of the United Nations and called for greater humanitarian assistance.

The wording was significant because BRICS now includes countries with very different positions and interests in the region. Iran and the UAE, for example, are both members but have had differing positions on regional issues.

India’s ability to secure a common declaration despite these differences was an important diplomatic outcome of the summit.

Push for UN reforms

The BRICS leaders also renewed their call for reform of the United Nations and other global institutions.

India has long argued that developing countries need greater representation in bodies such as the UN Security Council. The declaration backed a more representative and inclusive global governance system.

The summit also highlighted the need to give the Global South a stronger role in international decision-making.

India’s BRICS presidency focused heavily on development issues, including digital public infrastructure, healthcare, food security, skills, industrial cooperation and sustainable development.

Focus on practical cooperation

Several India-led initiatives received support during the summit. These included a BRICS digital public infrastructure repository, a Training Hub Network and greater cooperation in Industry 4.0.

The grouping also backed the creation of a BRICS-NDB Knowledge Portal and a Task Force on Growth and Development.

Health and human development were also part of India’s wider agenda. An early warning system for infectious diseases was among the initiatives highlighted during the summit.

The expanded BRICS now brings together 11 member countries, giving the grouping a much larger geographical and economic footprint across Asia, Africa, the Middle East and Latin America.

The New Delhi summit therefore produced fewer dramatic institutional changes than some had expected but delivered consensus on several important issues.

 

 

Categories
Leaders

John Ternus takes Apple helm as AI challenges grow

John Ternus will take charge as Apple’s chief executive on September 1, marking the end of Tim Cook’s 15-year tenure and opening a new chapter for the technology giant.

Ternus, Apple’s senior vice-president of Hardware Engineering, will become the company’s eighth CEO. Cook will move to the role of executive chairman, allowing Apple to retain his experience while handing day-to-day leadership to a new generation.

The leadership transition comes at an important moment for Apple. The company remains one of the world’s most valuable businesses, with a huge global customer base and strong positions in smartphones, computers, wearables and digital services. But the technology industry is changing rapidly, with artificial intelligence emerging as a major force shaping the future of consumer technology.

Ternus will inherit a financially powerful company, but also one facing questions over its AI strategy, growth prospects, China business and global supply chain.

An Apple veteran takes charge

Ternus has spent nearly 25 years at Apple after joining the company in 2001. He became senior vice-president of Hardware Engineering in 2021 and has played an important role in the development of several of Apple’s major products.

His work has included the iPhone, iPad, Mac and Apple Watch, as well as other hardware. He has also been closely involved in Apple’s transition to its own chips, which has given the company greater control over the performance and design of its devices.

His appointment signals a preference for continuity. Instead of bringing in an outsider, Apple has chosen an executive who understands its products, engineering teams and culture from within.

That experience could be valuable as Apple attempts to connect artificial intelligence more closely with its hardware.

Ternus, however, will now have responsibilities far beyond product development. As CEO, he will have to oversee Apple’s global operations, manage relations with governments, respond to regulatory challenges and guide the company’s long-term business strategy.

AI becomes the biggest challenge

Artificial intelligence is likely to be the most closely watched area of Ternus’ leadership.

Apple has already introduced Apple Intelligence, bringing AI-powered features to the iPhone, iPad and Mac. However, the company has moved more cautiously than several technology rivals in the generative AI race.

Companies such as Google, Microsoft, Meta and OpenAI have invested heavily in AI systems, infrastructure and consumer products. Apple, meanwhile, has faced questions over delays in delivering more advanced AI capabilities for Siri.

For Ternus, strengthening Apple’s AI position will be a key priority.

The company does not necessarily need to compete by creating another standalone chatbot. Its biggest advantage is its ecosystem of devices and services. The challenge will be to make AI useful across that ecosystem, from smartphones and computers to wearables and other connected products.

Apple will also want to maintain its focus on privacy and ease of use. The company has long promoted privacy as an important part of its products, and its AI strategy will need to balance powerful new features with those commitments.

Ternus’ hardware background could prove useful. AI increasingly depends on specialised chips and efficient computing, areas where Apple has invested heavily in recent years.

China remains a difficult equation

China will present another major challenge for the new CEO.

The country remains important to Apple as both a manufacturing centre and a consumer market. Although Apple has expanded production in countries including India and Vietnam, China continues to play a significant role in its global supply chain.

Apple must also deal with rising geopolitical and trade tensions. US policies have encouraged companies to reduce dependence on Chinese manufacturing, while relations between Washington and Beijing remain uncertain.

The Chinese smartphone market has become increasingly competitive for Apple as domestic manufacturers have strengthened their products and gained consumer attention.

Ternus will therefore have to balance manufacturing diversification with the realities of running a complex global supply chain. Any major shift away from China will take time because Apple depends on an enormous network of suppliers and manufacturing partners.

Cook’s move to executive chairman could provide some continuity in this area. His experience in dealing with governments, suppliers and international business partners will remain useful as Ternus takes over.

Cook leaves behind a transformed Apple

Ternus is taking charge of an Apple that is much larger than the company Cook inherited in 2011.

During Cook’s leadership, Apple expanded beyond the iPhone with products such as the Apple Watch and AirPods. It also built a major services business covering areas such as the App Store, Apple Music and iCloud.

Apple also developed its own silicon for Macs and other devices, giving the company greater control over its hardware and software.

The company’s market value rose dramatically during Cook’s tenure, reaching about $4 trillion. Apple now has more than 2.5 billion active devices worldwide, creating a vast ecosystem for new products and services.

Services have become an important source of recurring revenue, helping Apple reduce its dependence on hardware sales alone.

Cook’s tenure therefore left Ternus with a strong foundation. But maintaining that growth will be harder as smartphone markets mature and competition increases.

First major test arrives quickly

Ternus will have little time to settle into his new role before facing his first major product test.

Apple is scheduled to hold its next major iPhone event on September 9, only days after Ternus becomes CEO. The company is expected to introduce its latest iPhone lineup, with particular attention on the possibility of a foldable iPhone.

A foldable device would represent one of the biggest changes to the iPhone’s design in years. It could also open a new premium segment and give Apple another opportunity to drive hardware growth.

The launch will be closely watched because it will be the first major iPhone event under Ternus’ leadership. Investors and consumers will be looking for signs of how the new CEO intends to shape Apple’s product strategy.

Defining the next Apple era

Ternus takes over at a time when Apple’s traditional strengths are being tested by rapid changes in technology.

The company must continue growing the iPhone business, strengthen its artificial intelligence capabilities, develop new products and manage increasingly complicated supply chains. At the same time, it faces intense competition and growing regulatory scrutiny across major markets.

His engineering background gives Ternus a deep understanding of Apple’s products. His bigger challenge will be proving that he can translate that expertise into a broader vision for the company.

Cook leaves behind a business that has grown enormously in size, value and global reach. Ternus must now build on that success while ensuring Apple does not fall behind in the next major technology shift.

The leadership change is therefore more than a change of CEO. It comes as the industry moves from the smartphone era towards an AI-driven future.

Ternus’ task will be to preserve what has made Apple successful while giving the company a clear path into that future. His ability to close the AI gap, manage China-related challenges and deliver the next wave of products will determine whether Apple can maintain its position at the top of the technology industry.

 

Categories
Leaders

Bill Gates warns AI could reshape jobs and society

Microsoft co-founder Bill Gates has warned that the world is entering a turbulent phase of the artificial intelligence revolution, with AI potentially reshaping jobs, economies, education and human relationships much faster than governments and societies are prepared to handle.

In a new essay, Gates said he remains convinced that artificial intelligence could deliver enormous benefits in healthcare, science and education. But he is increasingly concerned that the technology is advancing so quickly that the negative consequences could arrive before adequate safeguards are in place.

Gates’ biggest concern is the effect of AI on employment. He expects the technology to move beyond assisting workers and increasingly perform entire tasks on its own. Areas such as law, customer service, medicine, software development and manufacturing could see significant changes over the next decade.

The shift could be especially difficult for entry-level and mid-level workers. Young people entering the workforce may find fewer opportunities to gain experience, while employees whose jobs disappear may struggle to move into completely different careers.

Gates also believes the disruption will eventually reach beyond traditional office jobs. As robotics improves, machines could become capable of performing more physical tasks. He has pointed to construction and hospitality as sectors where increasingly capable robots could begin competing with human workers before the end of the decade.

That possibility has led Gates to suggest an unusual policy idea: creating a category of “Human Reserved” jobs.

Under this approach, governments or societies could decide that certain occupations or tasks should remain primarily with people even when AI or robots are technically capable of doing them. The idea would be similar to protecting a nature reserve from development.

Gates believes healthcare and caregiving could be among the areas where human involvement should remain particularly important. A machine may be able to deliver information or perform a task efficiently, he argues, but there are situations where compassion, trust and emotional understanding matter just as much as technical ability.

The concept could also be temporary. Some jobs might be protected for a period of years or decades to give workers time to adapt rather than allowing sudden automation to eliminate entire categories of employment.

Gates has also proposed changing the tax system to deal with the economic impact of automation. He has suggested taxes on AI use, including AI “tokens”, as well as taxes on robots.

His reasoning is that the current system can make replacing employees with machines financially attractive. Businesses pay payroll-related taxes when they employ people, while investment in machines can receive different tax treatment. A tax on automation could slow the pace of replacement while generating money for worker retraining and stronger social safety nets.

Gates accepts that such measures would represent a major change in economic policy. But he believes governments should act before large-scale job losses become a reality rather than trying to respond after workers have already been displaced.

His concerns extend beyond employment. Gates has warned that increasingly powerful AI systems could be misused for cyberattacks and other harmful activities. The technology could allow malicious individuals to carry out sophisticated operations more quickly and at a lower cost.

He has also raised concerns about AI and biotechnology, particularly the possibility that advanced systems could make dangerous biological activity easier for bad actors.

Another area of concern is the effect of AI on children and human relationships. AI companions and increasingly personalised digital systems could become attractive substitutes for real-world interaction. Gates worries that excessive dependence on such technology could affect emotional development, social skills and the ability to think independently.

Education presents a similar dilemma. AI tutors could make learning more accessible and provide students with instant explanations. At the same time, relying on AI to solve every difficult problem could weaken critical thinking if students stop working through problems themselves.

Despite his warnings, Gates is not calling for an end to artificial intelligence. He continues to see the technology as potentially transformative in positive ways.

AI could help doctors identify diseases, accelerate scientific research, improve public services and expand access to education. In developing countries, it could also provide farmers and communities with useful information and services that are currently difficult to access.

The challenge, Gates argues, is ensuring that those benefits are widely shared while limiting the damage caused by rapid automation.

He believes governments need new institutions and policies specifically designed for the AI era. Existing rules were largely created before systems capable of performing complex cognitive tasks became widely available, leaving important gaps in areas such as employment, safety, education and accountability.

 

 

Categories
Leaders

Infraeo names Rakesh Sambaraju as CEO

Infraeo has appointed Rakesh Sambaraju as its President and Chief Executive Officer, placing an experienced optical communications executive at the helm as demand for high-speed connectivity continues to grow across artificial intelligence infrastructure and data centres.

The appointment comes at a crucial time for the AI infrastructure industry. As companies build increasingly powerful AI systems, data centres need faster connections, higher bandwidth and lower latency to move enormous volumes of data between servers, processors and storage systems. Infraeo is positioning its networking technology to address these requirements.

Sambaraju brings more than 20 years of experience in optical communications and high-speed interconnects. Before taking over as CEO, he served as Executive Vice President at Infraeo, giving him direct knowledge of the company’s technology, customers and markets.

Over his career, Sambaraju has held technology and business development leadership positions at companies including Sterlite Technologies, Nexans and Corning. His experience spans optical networking, photonics and the development of technologies designed for high-speed data transmission.

He holds a PhD, master’s degree and bachelor’s degree in Optical Communications from the Universitat Politècnica de València. His academic and industry background has focused on technologies that enable faster and more efficient communications networks.

Sambaraju takes charge as the artificial intelligence industry moves towards increasingly demanding workloads. AI training requires large clusters of computing systems to exchange data at extremely high speeds, while AI inference is increasingly being distributed closer to users and applications.

That shift is creating demand for networking technologies that can deliver high bandwidth without significantly increasing power consumption or latency. Infraeo says its strategy will focus on supporting both large-scale AI training environments and distributed AI inference.

Under Sambaraju, the company plans to continue developing its portfolio of 800G and 1.6T optical and copper interconnect products. These technologies are designed to provide the high-speed connectivity required by modern data centres and AI computing systems.

The company is also working on technologies for AI inference at the edge, where computing takes place closer to where data is generated or consumed. Such applications can require low-latency and long-reach connectivity, particularly as AI workloads become more distributed.

One area of focus will be near-package optics, or NPO. The technology places optical connectivity closer to high-performance computing components, potentially helping data-centre operators manage the growing bandwidth requirements of AI systems while addressing power and performance challenges.

Infraeo has already been demonstrating its high-speed connectivity technologies. At OFC 2026, the company showcased 800G and 1.6T interconnect solutions in collaboration with VIAVI. The demonstrations focused on line-rate performance, power efficiency and interoperability for next-generation AI fabrics and data-centre architectures.

The company has also highlighted a 400G QSFP112 LPO SR4 optical transceiver designed to provide high-performance connectivity while reducing power consumption in data-centre networks. Low-power optical technologies are becoming increasingly important as AI data centres consume more electricity and require larger numbers of high-speed connections.

Sambaraju’s appointment therefore reflects a broader trend in executive leadership and CEO appointments across growing companies, where new leaders are being brought in to guide the next phase of expansion. In Infraeo’s case, the change comes as the market for AI infrastructure is expanding rapidly, with hyperscalers, cloud providers and AI companies investing heavily in computing capacity.

The rapid development of AI models has increased pressure on data-centre operators to upgrade their networking infrastructure. Faster processors alone are not enough to improve overall system performance if data cannot move between computing resources quickly and efficiently.

This makes optical interconnects an increasingly important part of the AI infrastructure ecosystem. Optical technologies can support high-speed data movement over longer distances and are becoming increasingly relevant as data centres scale.

Infraeo says it intends to invest further in advanced optical technologies as AI workloads evolve. The company’s roadmap includes optical solutions designed for both centralised training clusters and distributed inference applications.

Sambaraju said his focus would be on taking the company to its next stage of growth while investing in technologies such as NPO, co-packaged optics and coherent optics. These technologies are being developed to address the networking challenges created by increasingly demanding AI workloads.

The leadership change also comes as the broader technology industry moves towards higher-speed Ethernet and optical connectivity. The transition from 800G towards 1.6T networking is expected to become increasingly important as AI clusters expand and computing requirements rise.

For Infraeo, the challenge will be turning this growing market opportunity into sustained commercial growth. The company will need to scale production, strengthen its technology portfolio and work closely with data-centre operators, system companies and other partners.

Sambaraju’s combination of technical expertise and experience within Infraeo could help the company navigate that transition. His previous leadership role means he already has familiarity with its products and strategic direction.

The appointment places Infraeo firmly within the race to build the connectivity layer required by next-generation AI infrastructure. As AI adoption expands across industries, the demand for faster, more efficient and lower-latency data-centre networks is expected to remain a key driver of the optical interconnect market.

With Sambaraju now leading the company, Infraeo is looking to use that opportunity to expand its presence in high-speed AI connectivity while developing technologies capable of supporting the next generation of data-centre architectures.

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AMD invests $5 bn in Anthropic AI partnership

Advanced Micro Devices (AMD) has announced a landmark partnership with artificial intelligence startup Anthropic, committing to invest up to $5 billion in the company as both firms strengthen their position in the rapidly expanding artificial intelligence (AI) industry. The deal combines a major financial investment with a long-term technology collaboration aimed at accelerating the development and deployment of next-generation AI systems.

The partnership marks one of AMD’s biggest strategic moves in the AI sector and reflects the growing competition among technology companies to build the computing infrastructure needed for increasingly powerful AI models. As businesses worldwide adopt generative AI at an unprecedented pace, demand for advanced AI chips and high-performance computing continues to surge.

As part of the agreement, AMD will make a strategic investment of up to $5 billion in Anthropic over several years. The AI startup, known for developing the Claude family of AI models, will also use AMD’s latest AI accelerators to train and run future generations of its artificial intelligence systems.

The collaboration gives Anthropic another major hardware partner beyond Nvidia and broadens AMD’s role in the fast-growing AI chip market. For AMD, the agreement represents an opportunity to showcase the performance of its AI processors while expanding its presence among leading AI developers.

The announcement comes at a time when technology companies are investing billions of dollars to secure access to advanced computing resources. Training large language models requires enormous computing power, making specialised AI chips one of the most valuable assets in the global technology industry.

AMD Chief Executive Officer Lisa Su said the partnership reflects the company’s commitment to building an open AI ecosystem and providing customers with greater choice in AI infrastructure. She noted that developers increasingly want alternatives that can deliver high performance while avoiding dependence on a single hardware supplier.

Anthropic has rapidly emerged as one of the world’s leading AI companies through its Claude chatbot and enterprise AI solutions. The company focuses on developing reliable and responsible artificial intelligence systems for businesses, researchers and consumers. As demand for its AI services grows, expanding computing capacity has become a critical priority.

For Anthropic, partnering with AMD offers access to advanced AI hardware that can support the growing computational demands of developing increasingly capable AI models. Diversifying its hardware suppliers may also improve resilience and flexibility as competition for AI chips intensifies worldwide.

The partnership extends beyond investment alone. The two companies plan to optimise Anthropic’s AI models for AMD’s latest AI accelerators, improving performance, efficiency and scalability. Engineers from both organisations are expected to work closely to fine-tune software and hardware for large-scale AI training and inference.

Industry analysts view the agreement as another sign that the AI hardware market is becoming increasingly competitive. Nvidia continues to dominate the sector with its graphics processing units (GPUs), but rivals such as AMD are investing aggressively to capture a larger share of the rapidly expanding market.

The deal also highlights the enormous capital flowing into artificial intelligence. Over the past two years, leading AI companies have attracted billions of dollars in funding from technology giants and institutional investors as competition intensifies to develop the most advanced generative AI models.

For enterprises, increased competition among AI chip providers could eventually reduce costs, improve hardware availability and accelerate innovation. Businesses deploying AI applications are seeking powerful yet flexible computing platforms capable of supporting everything from chatbot services to scientific research and enterprise automation.

AMD has significantly expanded its AI strategy in recent years through new product launches, software investments and partnerships with cloud providers and AI developers. The collaboration with Anthropic further strengthens its position in the evolving AI infrastructure ecosystem and demonstrates its ambition to become a leading supplier of AI chips for generative AI workloads.

Meanwhile, Anthropic continues to grow its global presence as demand rises for enterprise-grade artificial intelligence solutions. The company has increasingly focused on building secure and trustworthy AI systems that can be deployed across industries including finance, healthcare, education and software development.

The AMD-Anthropic partnership underscores how artificial intelligence has become one of the world’s most competitive technology sectors. As companies race to develop faster AI models and more powerful computing infrastructure, collaborations between semiconductor manufacturers and AI developers are expected to play a central role in shaping the future of generative AI, AI chips, cloud computing and advanced AI infrastructure. With billions of dollars now committed to the partnership, both companies are positioning themselves for the next phase of the global AI revolution.

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Corporate

HCLTech secures $1.14 bn AI transformation deal

HCLTech has signed a $1.14 billion (around ₹9,500 crore) artificial intelligence-led digital transformation deal with a Europe-based Fortune Global 50 company, marking one of the largest contracts in the company’s history and reinforcing its growing presence in the global AI services market.

The multi-year agreement will see HCLTech deliver advanced AI-powered solutions and digital transformation services to its client. While the company has not disclosed the customer’s identity because of confidentiality agreements, it said the partnership highlights increasing demand for large-scale AI adoption among global enterprises.

The announcement was well received by investors, sending HCLTech shares up nearly 6% in Friday’s trade. The stock emerged as one of the top gainers on the Sensex as market participants welcomed the deal, viewing it as a strong endorsement of the company’s artificial intelligence capabilities and long-term growth prospects.

The contract is expected to strengthen HCLTech’s revenue pipeline at a time when global technology companies are witnessing rising demand for AI-driven automation, cloud computing and data modernisation services. Businesses worldwide are increasingly investing in artificial intelligence to improve efficiency, reduce operational costs and enhance customer experience.

The announcement comes as Indian IT firms continue to adapt to changing market conditions. Although discretionary spending has remained under pressure in some sectors, demand for AI solutions has opened fresh opportunities for technology companies with strong digital capabilities.

HCLTech has been steadily expanding its AI portfolio through investments in generative AI, automation platforms and strategic partnerships. The latest contract further strengthens its position in the competitive global IT services industry, where companies are racing to secure large AI-focused transformation projects.

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