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Category: Artificial Intelligence

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  • The math behind the OpenAI Jalapeño chip

    OpenAI’s financial trajectory hinges heavily on infrastructure costs, a reality that drove the development of the new custom OpenAI Jalapeño chip. Developed in collaboration with Broadcom, the application-specific integrated circuit (ASIC) represents a direct attempt to mitigate the heavy capital expenditure associated with third-party hardware. 

    While Nvidia currently commands an estimated 75% profit margin on its high-end processors, OpenAI operates on tighter margins, keeping roughly 33 cents of profit on each dollar generated after accounting for its massive operational expenses. The financial burden of running large language models at scale is severe. 

    Last year, keeping ChatGPT servers responsive had cost OpenAI a staggering US$8.4 billion. With the platform now attracting 900 million weekly users, that operational cost is projected to reach approximately US$14 billion this year. Over the next eight years, OpenAI has committed roughly US$1.4 trillion to computing power, a massive bet for a company currently generating US$25 billion in annual revenue.

    Designing Hardware for LLM Inference

    The OpenAI Jalapeño chip, dubbed as the company’s first “Intelligence Processor”, is built specifically for large language model (LLM) inference rather than general-purpose AI workloads. OpenAI provided the core architectural design based on its specific model roadmaps and serving systems, while Broadcom managed the silicon engineering and high-performance networking integration. 

    TSMC handles the physical manufacturing in Taiwan, and Celestica is tasked with building the board and rack systems. According to OpenAI, early lab samples are already running frontier workloads, including an unreleased GPT-5.3-Codex-Spark model, at target production frequency and power. 

    Richard Ho, head of OpenAI’s hardware program, noted that the architecture minimizes data movement to push realized utilization closer to its theoretical peak performance. Unlike general-purpose accelerators adapted from legacy AI workloads, this architecture specifically balances compute, memory, and networking resources to solve the data-movement bottlenecks native to interactive LLM serving.

    To achieve this at scale, the platform integrates Broadcom’s Tomahawk networking silicon directly into the design, allowing the custom processors to communicate across massive, clustered data center environments.

    The vertical integration flywheel

    By moving into custom silicon, OpenAI shifts from being a mere software layer to a vertically integrated infrastructure company. This full-stack strategy spans the entire pipeline: chip architecture, software kernels, memory systems, network scheduling, and the final application layer. Much like Apple’s tight coupling of proprietary hardware and iOS, OpenAI can now optimize its infrastructure around its exact internal model roadmaps.

    This integration feeds a continuous operational flywheel. Enhanced infrastructure efficiency lowers the cost of both training and serving models. More affordable serving leads to better, more responsive products, which drives user volume and revenue to be reinvested back into the next generation of custom infrastructure.

    Overcoming the late-mover advantage

    By introducing its own silicon, OpenAI enters a landscape where its primary competitors have spent nearly a decade developing proprietary hardware. Google began deploying its Tensor Processing Units (TPUs) in 2015 and now controls roughly a quarter of global AI computing capacity outside of Nvidia’s supply chain. 

    Amazon has shipped over one million of its custom chips, while Meta and Microsoft continue to scale their own infrastructure.

    “Jalapeño is part of our long-term full-stack infrastructure strategy to make compute more abundant,” said Greg Brockman, president and co-founder of OpenAI. “By designing more of the stack ourselves, we can serve more intelligence with greater efficiency.”

    To close this timeline gap, OpenAI accelerated the development phase. The OpenAI Jalapeño chip transitioned from a blank-slate design to manufacturing tape-out—the final step before physical production—in just nine months. The engineering teams achieved this timeline by utilizing OpenAI’s own language models to automate and optimize portions of the hardware design process.

    This creates a unique feedback loop where the models served to users are actively being leveraged to build the physical infrastructure that will run future iterations. Initial deployment of the hardware into data centres is scheduled to begin by the end of 2026.

    Broadcom CEO Hock Tan confirmed that the rollout will scale alongside infrastructure partners, including Microsoft, to prepare for gigawatt-scale data centre integration.

    (Photo by OpenAI)

    See also: Omio scales travel product development using OpenAI models

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  • Samsung opens ChatGPT Enterprise and Codex access after AI restrictions

    Samsung Electronics is expanding employee access to ChatGPT Enterprise and Codex, giving staff wider use of AI tools for technical and non-technical work.

    According to OpenAI, the deployment covers all Samsung Electronics employees in Korea and all Device eXperience employees worldwide. The DX division includes smartphones, consumer electronics, and home appliances.

    Samsung plans to use the tools in software development, marketing, product development, manufacturing, and other business functions. The tools will support tasks such as information search, document drafting, idea development, data interpretation, and code-related work.

    Samsung revisits employee AI use

    The rollout comes three years after Samsung restricted employee use of generative AI tools over data-security concerns. In 2023, the company limited the use of ChatGPT and similar tools after concerns that sensitive internal information had been uploaded to an external AI platform.

    The new deployment gives employees access to ChatGPT Enterprise, which includes controls for data protection, user access, and security management. OpenAI said the enterprise version allows organisations to manage users, apply access controls, and use AI tools within internal security requirements.

    Samsung’s earlier restrictions applied to employee use of ChatGPT and similar generative AI tools. The new rollout gives employees access through an enterprise product with data protection and access controls.

    Samsung has not limited the deployment to a single business unit or technical group. OpenAI said the tools will be used across a broad range of functions, including technical and non-technical teams.

    OpenAI said ChatGPT can support knowledge-based tasks such as searching for information, analysing material, drafting documents, developing ideas, and interpreting data.

    Codex for technical and non-technical work

    Codex will be used for software-related tasks such as writing, reviewing, and debugging code. OpenAI said the tool is also being used for internal tools, websites, software prototypes, and automated workflows.

    OpenAI said Codex can also support non-technical teams in day-to-day work, including by helping employees create internal tools and automated workflows.

    OpenAI said Codex now has more than five million weekly users across technical and non-technical workflows. In Korea, weekly active users of Codex have grown nearly 800% since February 1, 2026, according to the company.

    Harrison Kim, general manager of OpenAI Korea, said the agreement is one of OpenAI’s largest enterprise deployments. He said Samsung is using AI across teams and functions rather than limiting it to specific departments.

    In October 2025, Samsung said it would work with OpenAI as a strategic memory partner for the Stargate AI infrastructure initiative, with OpenAI’s memory demand projected to reach up to 900,000 DRAM wafers per month.

    Samsung SDS also entered a potential partnership with OpenAI to jointly develop AI data centres and provide enterprise AI services. Samsung said the agreement would allow Samsung SDS to provide consulting, deployment, and management services for businesses integrating OpenAI models into internal systems.

    Samsung SDS also signed a reseller partnership to offer OpenAI services in Korea. Under that arrangement, Samsung SDS said it would support Korean companies adopting ChatGPT Enterprise and other OpenAI services.

    Reuters reported that Samsung Electronics and SK Hynix had signed letters of intent to supply memory chips for OpenAI’s Stargate project. The report said the two South Korean chipmakers together account for about 70% of the global DRAM market and nearly 80% of the high-bandwidth memory market.

    High-bandwidth memory supports fast data movement between memory and processors in AI systems. Reuters reported that OpenAI’s chip demand for Stargate may reach 900,000 wafers per month, citing South Korea’s presidential office.

    Samsung said its semiconductor businesses would support OpenAI’s demand with advanced memory solutions. The company also said its affiliates were exploring broader work with OpenAI in areas including data centres, enterprise services, and AI infrastructure.

    AI adoption and productivity

    Deloitte’s 2026 State of AI in the Enterprise report found that 66% of organisations reported productivity or efficiency gains from enterprise AI adoption. The same report found that 53% reported improved insights and decision-making.

    A Bpifrance survey reported by Reuters found that 77% of 534 French mid-sized company heads said their firms used generative AI, but only 17% of those using it reported time savings.

    Samsung has identified use cases across document work, information analysis, coding, product development, marketing, and manufacturing. The deployment gives employees access to ChatGPT Enterprise and Codex for those tasks under a company-wide agreement.

    OpenAI’s Korea partnerships

    OpenAI has also announced other partnerships in Korea. Seoul National University recently began providing ChatGPT Edu to 47,000 students, faculty, and staff.

    OpenAI has also worked with Kakao to bring ChatGPT responses into KakaoTalk group chats. The company said Korean organisations including LG Electronics, LG Uplus, LG CNS, GS E&C, Samsung SDS, TVING, Krafton, Toss, MUSINSA, Korea Zinc, Nexen Tire, and HanaTour are using ChatGPT Enterprise, OpenAI APIs, or Codex.

    (Photo by Zulfugar Karimov)

    See also: Omio scales travel product development using OpenAI models

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  • Anthropic drops ‘workplace AI agents’ directly inside Slack

    Anthropic launched a beta version of its Claude Tag feature for Enterprise and Team tiers, shifting its chat model into shared Slack channels. Moving away from traditional isolated chat boxes, users pull the artificial intelligence model into active group threads by typing @Claude. 

    The integration allows any team member in the channel to delegate a task, review the model’s outputs, and pick up the discussion thread from a previous point. This structural shift follows a US$65 billion Series H funding round that brought Anthropic’s post-money valuation to US$965 billion, positioned above rival OpenAI’s US$852 billion mark. 

    Following a confidential S-1 filing for an initial public offering, market competition for business software placement remains tight. Data from corporate expense platform Ramp’s May 2026 AI Index indicates Anthropic’s enterprise adoption rate reached 34.4%, passing OpenAI’s 32.3% footprint.

    Modifying the channel workstream

    Standard generative software requires enterprise employees to move data between team chats and separate browser instances. Anthropic aims to reduce this back-and-forth movement by restructuring workplace AI agents to work in multiplayer environments.

    “Instead of a private back-and-forth, Claude Tag shows up in the open,” stated Rob Seaman, general manager of Slack, regarding the operational mechanics of the application. This shared visibility alters how context is tracked inside an organisation. Because Claude Tag logs its task status directly inside the communication window, multiple employees can monitor the live execution steps. 

    The system tracks ongoing information from its active channels to build a contextual background. This automated history tracking limits the need for team members to continuously retype foundational company data or project scopes.

    Functional mechanics and asynchronous tasks

    The technical foundation for this channel integration relies on Anthropic’s Opus 4.8 engine. When assigned a request, the model divides the operation into sequential execution phases and utilises connected corporate databases, tools, and code repositories to complete the work.

    The primary operational difference for these workplace AI agents is their capability to function asynchronously without real-time human prompting. If a network administrator activates the tool’s “ambient” configuration, Claude Tag monitors threads and tracks tasks autonomously. The agent checks inactive text threads, signals priority notifications from integrated software extensions, and tracks unresolved assignments across multi-day intervals.

    Cat Wu, head of product for Claude Code, noted that the change centres on user configuration rather than completely new logic. “The form factor of being able to tag it the same way that you would a coworker is really powerful,” Wu told Reuters. Wu explained that connecting her personal Claude Tag agent to her email archive allows the system to analyse incoming communications, categorise urgent entries, and send immediate alerts inside Slack.

    Metrics and administrative controls

    Internal reporting from Anthropic shows that automated code generation has altered engineering activities, with the firm’sinternal product group creating 65% of its code through its private version of Claude Tag.

    Beyond software development, the vendor targets non-technical office workforces. Early customer implementations focus on querying database metrics, parsing analytics data, and processing internal IT support tickets.

    This expansion of background agent operations requires a distinct security infrastructure to protect proprietary information. To restrict data access to approved departments, system administrators must establish scoped Claude identities. All localised memories and tool integrations are confined strictly to specific channels authorised by the IT department. 

    Additionally, management portals offer full tracking logs of user queries alongside specific organisational caps to regulate monthly token costs. 

    The enterprise calculation: Autonomy vs. governance

    Frankly, moving generative tools from individual sandboxes into persistent corporate communication channels presents distinct operational trade-offs. The clear upside is the optimisation of routine knowledge work. By centralising information logs directly inside active threads, companies can lower task friction, capture context across changing project teams, and reduce the time spent on manual codebase tracking or database updates.

    However, delegating cross-app workflows to background agents introduces significant structural risks for IT departments. Permitting automated systems to read chat histories, connect to email accounts, and modify central code repositories expands an organisation’s internal data-exposure risks.

    If access boundaries are misconfigured, sensitive proprietary context could cross into unapproved channels. Furthermore, autonomous asynchronous execution removes direct human verification from intermediate workflow stages, leaving teams vulnerable to systemic errors if the underlying model misinterprets instructions mid-task. 

    Corporate decision-makers must ultimately evaluate whether the productivity gains of channel-based automation outweigh the rigorous auditing, compliance overhead, and channel-by-channel security configurations required to safely govern an always-on agent.

    See also: Anthropic releases Claude Opus 4.8

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  • Top spy agencies say AI cyber threats will impact you within months. Here’s why

    The global surge in AI cyber threats is no longer a distant problem for corporate data centres, according to an urgent public warning from the world’s most powerful intelligence alliance. On June 22, 2026, the cybersecurity chiefs of the Five Eyes nations—comprising the US, UK, Canada, Australia, and New Zealand—issued a rare joint intelligence briefing stating that upcoming artificial intelligence models will supercharge offensive hacking capabilities on a timeline measured in months, not years. 

    While the advisory specifically tells corporate executives to overhaul their network defences, the rapid evolution of these tools means everyday internet users are about to face a much shiftier digital landscape. 

    The massive shift in AI cyber threats

    The intelligence brief highlights an immediate danger: advanced, upcoming models like OpenAI’s “GPT-5.5-Cyber” and Anthropic’s “Mythos” are actively lowering the technical barriers for digital crime. Rogue actors no longer need elite coding skills to build complex, devastating software exploits.

    Instead, automated digital agents can scan internet-connected infrastructure around the clock to find software vulnerabilities before human engineers can patch them. This drastically shrinks the safety window that technology companies rely on to keep user applications secure.

    How does this hit home for regular users?

    When criminal networks use automated tools to breach large databases, the immediate consequence is the theft of regular consumer data. Your personal information, saved passwords, and cloud backups are the ultimate targets in these accelerated corporate intrusions. 

    Furthermore, bad actors are leveraging conversational models to generate hyper-personalised phishing scams at an industrial scale. This trend is hitting the Asia-Pacific (APAC) region particularly hard, with countries like India recording a staggering 165% spike in ransomware incidents in early 2026 due to AI-assisted targeting.

    Rather than relying on easily spotted, poorly written spam emails, automated systems can scan your public social media profiles to write flawless, highly convincing messages designed to steal your credentials. 

    Fighting back with the same tech

    The primary challenge facing cyber defenders is that machine-paced offence naturally moves faster than human-led detection. According to the World Economic Forum’s Global Cybersecurity Outlook, a massive 94% of corporate executives identify AI as their top threat vector, yet two out of three organisations report moderate to critical cybersecurity talent shortages.

    Network administrators are finding it impossible to review and deploy traditional security patches manually when rogue AI agents can discover and exploit a software vulnerability within minutes. 

    The Five Eyes alliance emphasises that the most effective way to withstand these accelerating AI cyber threats is to deploy automated defences. Security teams are actively integrating defensive artificial intelligence models to monitor unusual behaviour and isolate network breaches.

    For individual users, the basic rules of internet safety are becoming mandatory. Turning on multi-factor authentication and deleting old, unused online accounts remain the most effective ways to break the automated chain of an AI-driven attack.

    See also: AI web search risks: Mitigating business data accuracy threats

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    AI News is powered by TechForge Media. Explore other upcoming enterprise technology events and webinars here.

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  • L’Oréal brings Maybelline virtual try-on to ChatGPT

    L’Oréal has announced a collaboration with OpenAI that will bring Maybelline New York’s virtual makeup try-on feature into ChatGPT.

    The announcement was made at VivaTech 2026. The partnership covers consumer-facing shopping tools, product discovery, advertising pilots, research, and internal content production. The collaboration also covers L’Oréal’s internal use of AI in research, formulation, content production, and employee tools.

    OpenAI said in 2026 that ChatGPT had more than 900 million weekly active users and more than 50 million subscribers.

    Maybelline try-on comes to ChatGPT

    Maybelline’s Makeup Virtual Try-On will be available directly within ChatGPT. The feature will use L’Oréal’s ModiFace technology, which allows users to test makeup looks digitally through a conversational interface.

    ModiFace is L’Oréal’s augmented reality and AI beauty technology business. L’Oréal acquired the Canadian company in 2018 to expand its digital beauty services across areas such as virtual makeup try-on, hair colour try-on, and augmented reality shopping.

    L’Oréal’s 2025 Annual Report said its Beauty Tech services had more than 120 million uses across 66 countries and 31 brands by the end of 2025.

    Product discovery and advertising

    L’Oréal will also work with OpenAI to improve how its products are surfaced in ChatGPT in the United States. The company said the work will cover brands including Lancôme and Kérastase.

    L’Oréal said the ChatGPT work also includes product discovery. The company said e-commerce grew by double digits in 2025 and passed 30% of sales. Several L’Oréal brands are also involved in OpenAI’s global ChatGPT advertising pilot. They include SkinCeuticals, CeraVe, and Garnier. The programme focuses on ads within AI-assisted consumer interactions.

    L’Oréal described the pilot as focused on AI-native advertising at moments of consumer intent and commerce. The company has not provided further operational details on how the ad placements will appear inside ChatGPT.

    AI use in research and formulation

    The partnership also extends to L’Oréal’s research work. The company said it is using GPT-Rosalind, OpenAI’s life sciences reasoning model, to map the skin microbiome.

    OpenAI launched GPT-Rosalind as a model for life sciences research tasks, including evidence synthesis and experimental planning. L’Oréal said it is applying the model to skin microbiome research, starting with La Roche-Posay. The skin microbiome refers to the community of microbes that live on the skin. L’Oréal said the work is aimed at identifying beneficial bacteria that can support the development of new skincare products.

    L’Oréal’s 2025 Annual Report also cited AI work in formulation science. L’Oréal Research & Innovation and IBM are developing a Formulation Foundation Model for beauty formulation.

    L’Oréal has also worked with NVIDIA on AI development and deployment. The company has said the partnership covers areas including 3D product rendering and predictive formulation science.

    Internal AI tools

    OpenAI’s latest model will also be used in CreAItech, L’Oréal’s internal generative AI content platform. The platform is designed to create images and videos while reflecting the visual identity and history of L’Oréal’s brands.

    CreAItech is used by L’Oréal teams for beauty content creation. The OpenAI model support will apply to image and video generation.

    Asmita Dubey, L’Oréal’s chief digital and marketing officer, said the company wants to use AI to support consumers and employees. She also cited its use across marketing and research.

    Emmanuel Marill, OpenAI’s managing director for EMEA, said the work with L’Oréal covers research and employee tools, as well as consumer-facing services.

    The collaboration forms part of L’Oréal’s wider AI programme. The company said the programme covers consumer tools and internal work across marketing and research. L’Oréal said 73,000 employees have already been trained in generative AI. The company has also introduced internal tools including L’OréalGPT and personal AI companions.

    The announcement coincides with L’Oréal’s 10th year at VivaTech.

    (Photo by Helio E. López Vega)

    See also: Microsoft sells OpenAI models in China. OpenAI and Anthropic won’t.

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    AI News is powered by TechForge Media. Explore other upcoming enterprise technology events and webinars here.

    The post L’Oréal brings Maybelline virtual try-on to ChatGPT appeared first on AI News.

  • HSBC expands AI banking partnership with Google Cloud

    HSBC has entered a multi-year partnership with Google Cloud to develop and deploy artificial intelligence tools across its global operations.

    Announced at Google Cloud Summit London 2026, the agreement covers work in wealth management, financial crime risk management, and internal decision support. HSBC will work with Google Cloud and Google DeepMind engineering teams on AI tools and programmes using Gemini models and the Gemini Enterprise Agent Platform.

    AI rollout across HSBC

    HSBC expects the partnership to support more than 200 AI use cases over the next two years. Selected initiatives could each return more than US$100 million through direct revenue gains or efficiency improvements, according to the bank.

    HSBC had existing AI deployments before the Google Cloud agreement. In its 2025 Strategic Report, the bank said it had more than 100 active generative AI use cases and was increasing AI partnerships.

    HSBC says it has more than 600 AI use cases across the group. These include fraud detection, cyber security, transaction monitoring, customer service, and risk assessment. More than 600 HSBC applications already run on Google Cloud.

    A 2026 Cambridge Centre for Alternative Finance report found that 71% of surveyed industry respondents were adopting generative AI, while 52% were adopting agentic AI.

    Existing AI work

    HSBC announced a separate multi-year partnership with Mistral AI in December 2025. The agreement gives the bank access to Mistral AI’s commercial models. HSBC said the models would support internal tools, financial analysis, multilingual reasoning, translation, and prototyping.

    HSBC has listed other generative AI uses in credit analysis, customer support, document analysis, and text assistance. CIO Dive reported in February that 85% of HSBC employees had access to generative AI tools.

    The report also said the bank was assessing the technology across 50 processes, including fraud detection and credit applications.

    Financial crime detection

    The Google Cloud agreement follows earlier AI work between HSBC and Google in financial crime detection. HSBC has previously said it partnered with Google to co-develop Dynamic Risk Assessment, an AI system used to check for financial crime.

    HSBC said the system was piloted in 2021 and found two to four times more financial crime than previous methods. Google Cloud has said HSBC screens more than 1.2 billion transactions each month for signs of financial crime.

    Under the new partnership, HSBC will use generative AI and agentic AI in financial crime risk management. The bank expects the tools to help it intervene twice as fast when risk is detected across the nearly one billion transactions it monitors each month.

    Wealth and staff tools

    In wealth management, HSBC plans to combine AI-generated insights with the work of relationship managers. The bank said the tools are intended to support financial advice and client service.

    HSBC said it will expand an AI-powered decision assistant already used by thousands of employees. The tool has reduced administrative work and client meeting preparation from hours to minutes, according to the bank.

    HSBC has applied generative AI in software development. More than 20,000 developers are using coding assistants, with a 15% efficiency gain in time spent coding, according to the bank.

    HSBC plans to use AI to organise regulatory procedures into a structured format. The bank said this would provide employees with options and analysis for decision-making while keeping human judgement involved.

    AI leadership

    In March, HSBC announced that David Rice would become its first Chief AI Officer, effective 1 April. HSBC said the role was created to oversee AI adoption across the group.

    Georges Elhedery, Group CEO of HSBC, said the bank is using AI to create more personalised customer experiences while retaining human judgement and accountability.

    Thomas Kurian, CEO of Google Cloud, said the partnership would support HSBC’s AI work through Gemini, the Gemini Enterprise Agent Platform, and Google DeepMind’s research expertise.

    See also: Visa ChatGPT integration enables AI agent retail purchasing

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    The post HSBC expands AI banking partnership with Google Cloud appeared first on AI News.

  • EU publishes its AI content labelling playbook ahead of the AI Act’s August deadline

    The European Union has published its AI content labelling playbook, a voluntary Code of Practice meant to help companies meet transparency rules that become law across the bloc on August 2 onwards. The European Commission released the final Code on 10 June, setting out practical steps for the businesses that build and use generative AI to mark and label what their systems produce.

    The Code itself is optional. The obligations it points to are not. They sit under Article 50 of the EU AI Act, and from August 2, 2026, they apply whether or not a company signs the Commission’s guidance. Signing simply gives a business a recognised way to show it complies.

    What the AI content labelling rules actually require

    From August, two things must be clearly flagged. Deepfakes and AI-generated or AI-manipulated text published on matters of public interest have to carry a label. Anyone chatting with an interactive AI system, such as a customer-service bot, also has to be told they are dealing with a machine. 

    The Commission frames it as a way to help users spot AI-made or AI-altered material and narrow the space for deception. “Europeans have a right to know whether what they see, hear or read has been made or altered by AI, especially when such content can shape public debate,” said Henna Virkkunen, the Commission’s executive vice-president for tech sovereignty, security and democracy. 

    She cast the Code as a practical route to labelling that AI providers and deployers can follow before the rules bite in August. The Code splits the work between the two sides of the AI supply chain. The companies that build generative models are asked to mark their output in a machine-readable format, so it can be detected further down the line. 

    The companies that deploy those models, the ones putting AI to work in real products, handle the visible labelling, which, for public-interest AI text, applies when the content has gone out without human review or editorial control. To keep it workable, the Code leans on open technical standards and a common EU icon, meant to give users a consistent visual cue and spare businesses from inventing their own.

    None of this is the final word. The Code is now open for signatures, and the Commission is urging all providers and deployers to sign. It still needs the Commission and the AI Board to judge it adequately, and separate Commission guidelines are due to clarify the law and cover what the Code leaves out. Drawn up by six independent experts with input from more than 180 stakeholders, it is the first instrument to tackle AI content labelling under the Act.

    The timing leaves little slack. Companies serving European users have under two months to work out what they need to label and how, and to decide whether to sign. Plenty of the harder detail still rests on guidelines the Commission has yet to publish.

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  • Waymo ‘Siren’ Continues To Wake Up East London Residents

    Car from Google sister company continues to get stuck in dead-end road in Spitalfields, a month after firm took action to fix issue

  • HarmonyOS 7 steps into the AI gap Apple left open in China

    Four days after Apple confirmed that Siri AI would not launch in China, Huawei took the stage in Dongguan and declared HarmonyOS 7 the beginning of the agent era. The gap Apple could not fill, Huawei has moved into with an architecture built specifically for it.

    What HarmonyOS 7 actually changes

    The headline change is the HarmonyOS Intelligent Agent Framework 2.0, which restructures the OS around what Huawei calls an “intent-as-service” model, compressing what previously required multiple app navigation into a single natural-language command.

    At the centre of this is Xiaoyi, Huawei’s AI assistant, rebuilt from a conventional voice tool into what the company describes as a system-level intelligence agent. Xiaoyi now controls over 2,100 system-level capabilities and coordinates with more than 2,000 third-party AI agents developed across Huawei’s developer ecosystem. 

    Richard Yu, chairman of Huawei’s Consumer Business Group, framed the release as a generational inflexion point: “In 2019, HarmonyOS was born. In 2023, native HarmonyOS apps began. In 2026, HarmonyOS enters the Agent era.”

    Underneath sits openPangu 2.0, Huawei’s updated foundation model, with 505 billion parameters in its Pro version and 92 billion in the Flash variant, both supporting 512K context windows. On-device models at 30 billion parameters are due on Kirin chips by autumn 2026. HarmonyOS 7 also delivers a 15%-plus performance improvement over HarmonyOS 6.1, according to Huawei’s own benchmarks. 

    The task execution rate claimed is above 90%, though that figure is Huawei’s own and has not been independently verified.

    The market position is consolidating

    The numbers shared at HDC 2026 reflect a shift that has already happened. In Q1 2026, HarmonyOS held 19% of China’s smartphone OS market against Apple iOS at 16%, with Android at 65%. HarmonyOS first overtook iOS in China in Q2 2025, according to Counterpoint Research.

    That trajectory matters more than any single feature because China is simultaneously the market Apple cannot currently operate in at the AI level and the one Huawei has fully optimised for. The agent network Xiaoyi coordinates includes partnerships with Ctrip for travel planning and Ant Medical for health data analysis, services woven into the Chinese consumer stack that Apple’s architecture does not reach.

    Where the limits are

    The scope of the challenge to Apple needs calibrating. HarmonyOS 7 is currently in developer beta, with the stable consumer release expected this autumn. The 2,000-plus AI agents are anchored in the Chinese app ecosystem. 

    The platform counts more than 400,000 applications and services, which is significant but still a fraction of what Apple’s App Store carries. Huawei’s ambitions to take HarmonyOS international remain aspirational for now.

    There is also a design note that softens any clean divergence narrative: HarmonyOS 7 adopts the same Liquid Glass aesthetic Apple introduced with iOS 26, and Samsung brought to One UI 9. Visual language converges even as underlying architectures and regulatory environments pull in opposite directions.

    The longer arc

    HarmonyOS exists because of US sanctions. When Huawei lost access to Google’s Android in 2019, it built its own OS from necessity. By January 2026, over 90% of Huawei devices were running the fully homegrown version. That forced independence is now a structural advantage in the one market where Apple cannot currently deploy its headline AI feature.

    Sanctions built the platform. Regulatory friction cleared its path.

    See also: Siri AI arrives with Google inside, and much of the world is locked out

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  • The AI off switch: How Anthropic’s export controls sparked a global AI sovereignty scramble

    Anthropic export controls turned an abstract policy fear into a live one last week: as of June 13, 2026, one US government directive took the company’s two most powerful AI models offline for users everywhere, including, briefly, Anthropic’s own foreign-born employees, and set off alarm bells across Europe and Canada about who really controls the AI the world runs on.

    The mechanics were startling in their speed. The reaction abroad has been louder still.

    Launch to lockdown in four days

    On June 9, 2026, Anthropic made Claude Fable 5 and Claude Mythos 5 generally available, the public face of a model class the company had developed under controlled access since April through a programme called Project Glasswing. Fable 5 was described as a Mythos-class model made safe for general use, state-of-the-art on nearly all tested benchmarks, with strong performance in software engineering, scientific research, and autonomous work. 

    Mythos 5, the more capable sibling, stayed restricted to Glasswing partners and selected biology researchers. Four days later, it was gone. Anthropic said it received an export control directive to suspend access to Fable 5 and Mythos 5 at 5:21 pm ET on June 12, with the letter not explaining the specific security concern in detail. 

    Unable to filter users by nationality in real time, the company said it had to “abruptly disable” access for all customers to comply. The order, issued by Commerce Secretary Howard Lutnick in a letter to CEO Dario Amodei, called for suspending all access by any foreign national, whether inside or outside the United States. 

    The jailbreak at the centre of it

    Washington cited national security, specifically, a method for “jailbreaking” Fable 5, or getting around its safety guardrails. Anthropic disputed the severity, saying the technique amounted to a limited capability to review programme code and identify errors, something rival models, including OpenAI’s GPT-5.5, can also do. 

    The government’s account is sharper. David Sacks, co-chair of the President’s Council of Advisers on Science and Technology, said on X that the administration asked Amodei to either fix the vulnerability or pull the model from deployment, and that Amodei refused. Sacks pressed the contradiction directly: “In their blog post, Anthropic defended its decision by saying the jailbreak isn’t serious. That is not what the trusted partner and the US government believe; nor is that kind of minimising language consistent with Anthropic’s brand as the AI safety company.

    The Wall Street Journal reported the move was also shaped by Amazon CEO Andy Jassy, who told Treasury Secretary Scott Bessent and other officials that Amazon researchers had used Fable 5 prompts to obtain information that could aid cyberattacks. Amazon is one of Anthropic’s largest investors. A spokesperson said it is “not uncommon for governments to seek our counsel on potential security risks,” but declined to share details. 

    A fight that started months before

    None of this began last week. The dispute erupted earlier this year after Anthropic insisted its technology should not be used for mass surveillance or fully autonomous weapons systems, infuriating Pentagon chief Pete Hegseth. President Trump ordered every federal agency to stop using Anthropic’s technology, and Hegseth designated the company a “Supply-Chain Risk to National Security“, a label, the company’s lawsuit notes, usually reserved for foreign adversary firms like Huawei. 

    Anthropic sued to reverse the blacklisting, warning it could jeopardise “hundreds of millions of dollars” in revenue. The result is a company simultaneously deemed too dangerous for the US government’s own use and too dangerous for foreign use, a contradiction not lost on observers. Dean Ball, an AI policy expert who briefly served in the Trump administration, called the order “simply cartoonish,” noting that an administration willing to export advanced AI chips to China now wants to ban Britain and every other non-American from using Anthropic’s best models.

    The export controls heard around the world

    Outside the US, the response went straight past the jailbreak debate and landed on a single, uncomfortable realisation: a tool embedded in companies, research institutions, and public services worldwide had been switched off by a foreign government, with an email, in an afternoon.

    The European Commission confirmed it is examining the fallout. Spokesperson Thomas Regnier said the new generation of highly capable AI models offers real benefits, including for cyber-defence, but raises serious cybersecurity concerns that need addressing, adding that “contingency measures taken in this light should not be discriminatory against partners.” 

    European politicians were blunter. French commentary framed the decision as an accelerator of the geopolitical battle over AI, with the argument that “Europe cannot settle for being an open market dependent on technologies designed, funded, and controlled elsewhere.” Finnish MEP Aura Salla said Europe “cannot continue to increase its technical potential by relying on access that can be turned off by a foreign government overnight.” The timing sharpened the point: the Commission had published its Technological Sovereignty Package — including a Cloud and AI Development Act — on June 3, just nine days before the shutdown. euronews + 2

    The unease crossed the Atlantic. Speaking in Ireland ahead of the G7 summit, Canadian Prime Minister Mark Carney said the restrictions show the dangers of overreliance on a limited number of American providers, framing it as a lesson in diversification. “The situation we’re in collectively right now with Mythos and Fable is something that can happen with overreliance on certain models,” Carney said, flagging AI as a major topic for the summit. In Britain, AI and Online Safety Minister Kanishka Narayan said the episode should drive deeper investment in the country’s own AI industry. 

    What happens next

    Anthropic’s position has not moved. It maintains that applying this standard across the industry “would essentially halt all new model deployments for all frontier model providers.” The route back runs through the Commerce Department’s Bureau of Industry and Security, where a licence is now required for export, re-export or domestic transfer of the two models, with individually validated licences needed for reinstatement and civil penalties for non-compliance. 

    Sacks framed the off-ramp plainly: fix the jailbreak, lift the control. “The ball is in Anthropic’s court,” he wrote. For the governments now watching from outside, the patch is almost beside the point. The lesson many of them have already drawn is that access to frontier AI is no longer purely a matter of price or product; it is a matter of whose jurisdiction holds the switch. Last week, the answer turned out to be Washington’s, and a lot of capitals didn’t like how that felt.

    See also: Anthropic IPO filing marks AI maturing into enterprise utility

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