Nvidia now accounts for more than 8% of the S&P 500, the largest share ever held by a single stock since records began in 1981. The company’s market value reached about $4.5 trillion on Monday, driven by unprecedented demand for its AI chips.
Its share price surged 239% in 2023, 171% in 2024, and 36% in 2025.
While investor sentiment remains strong, analysts warn of mounting risks. Political tensions with China, potential export restrictions, and reliance on overseas resellers could threaten sales.
Over the weekend, reports emerged of an agreement with the US government allowing Nvidia and AMD to give 15% of Chinese chip revenue in exchange for export licences, potentially boosting growth by more than 20%.
Infrastructure is another concern. Analysts say customers now face delays from chip shortages, limited power grid capacity, and data centre cooling systems.
Some of Nvidia’s biggest clients could become direct rivals, challenging its 75% profit margin and long-term dominance in AI infrastructure.
Nvidia’s unprecedented weight in the S&P 500 closely ties the index’s performance to its fortunes. While demand for AI hardware remains high, the company’s growth trajectory depends on navigating political, infrastructure, and competitive pressures.
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Elon Musk has announced plans to sue Apple, accusing the company of unfairly favouring OpenAI’s ChatGPT over his xAI app Grok on the App Store.
Musk claims that Apple’s ranking practices make it impossible for any AI app except OpenAI’s to reach the top spot, calling this behaviour an ‘unequivocal antitrust violation’. ChatGPT holds the number one position on Apple’s App Store, while Grok ranks fifth.
Musk expressed frustration on social media, questioning why his X app, which he describes as ‘the number one news app in the world,’ has not received higher placement. He suggested that Apple’s ranking decisions might be politically motivated.
The dispute highlights growing tensions as AI companies compete for prominence on major platforms.
Apple and Musk’s xAI have not responded yet to requests for comment.
The controversy unfolds amid increasing scrutiny of App Store policies and their impact on competition, especially within the fast-evolving AI sector.
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After Elon Musk accused Apple of favouring OpenAI’s ChatGPT over other AI applications on the App Store, there was a strong response from OpenAI CEO Sam Altman.
Altman alleged that Musk manipulates the social media platform X for his benefit, targeting competitors and critics. The exchange adds to their history of public disagreements since Musk left OpenAI’s board in 2018.
Musk’s claim centres on Apple’s refusal to list X or Grok (XAI’s AI app) in the App Store’s ‘Must have’ section, despite X being the top news app worldwide and Grok ranking fifth.
Although Musk has not provided evidence for antitrust violations, a recent US court ruling found Apple in contempt for restricting App Store competition. The EU also fined Apple €500 million earlier this year over commercial restrictions on app developers.
OpenAI’s ChatGPT currently leads the App Store’s ‘Top Free Apps’ list for iPhones in the US, while Grok holds the fifth spot. Musk’s accusations highlight ongoing tensions in the AI industry as big tech companies battle for app visibility and market dominance.
The situation emphasises how regulatory scrutiny and legal challenges shape competition within the digital economy.
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Indonesia is urgently working to secure strategic autonomy in AI as Huawei rapidly expands its presence in the country’s critical infrastructure. Officials are under pressure to swiftly adopt enforceable safeguards to balance innovation and security. The aim is to prevent critical vulnerabilities from emerging.
Huawei’s telecom dominance extends into AI through 5G infrastructure, network tools, and AI cloud centres. Partnerships with local telecoms, along with government engagement, position the company at the heart of Indonesia’s digital landscape.
Experts warn that concentrating AI under one foreign supplier could compromise data sovereignty and heighten security risks. Current governance relies on two non-binding guidelines, providing no enforceable oversight or urgent baseline for protecting critical infrastructure.
The withdrawal of Malaysia from Huawei’s AI projects highlights urgent geopolitical stakes. Indonesia’s fragmented approach, with ministries acting separately, risks producing conflicting policies and leaving immediate gaps in security oversight.
Analysts suggest a robust framework should require supply chain transparency, disclosure of system origins, and adherence to data protection laws. Indonesia must act swiftly to establish these rules and coordinate policy across ministries to safeguard its infrastructure.
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OpenAI has released reasoning-focused open-weight models in a strategic response to China’s surging AI ecosystem, led by DeepSeek’s disruptive efficiency. Unlike earlier coverage, the shift is framed not merely as competitive posturing but as a deeper recognition of shifting innovation philosophies.
DeepSeek’s rise stems from maximizing limited resources under the US’s export restrictions, proving that top-tier AI doesn’t require massive chip clusters. The agility has emboldened the open-source AI sector in China, where over 10 labs now rival those in the US, fundamentally reshaping competitive dynamics.
OpenAI’s ‘gpt-oss’ models, which reveal numerical parameters for customization, mark a departure from its traditional closed approach. Industry watchers see this as a hybrid play, retaining proprietary strengths while embracing openness to appeal to global developers.
The implications stretch beyond technology into geopolitics. US export controls may have inadvertently fueled Chinese AI innovation, with DeepSeek’s self-reliant architecture now serving as a proof point for resilience. DeepSeek’s achievement challenges the US’s historically resource-intensive approach to AI.
AI rivalry may spur collaboration or escalate competition. DeepSeek advances models like DeepSeek-MoE, while OpenAI strikes a balance between openness and monetization. Global AI dynamics shift, raising both technological and philosophical stakes.
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The UAE Ministry of Interior states that AI, surveillance, and modern laws are key to fighting crime. Offences are economic, traditional, or cyber, with data tools and legal updates improving investigations. Cybercrime is on the rise as digital technology expands.
Current measures include AI monitoring, intelligent surveillance, and new laws. Economic crimes like fraud and tax evasion are addressed through analytics and banking cooperation. Cross-border cases and digital evidence tampering continue to be significant challenges.
Traditional crimes, such as theft and assault, are addressed through cameras, patrols, and awareness drives. Some offences persist in remote or crowded areas. Technology and global cooperation have improved results in several categories.
UAE officials warn that AI and the internet of Things will lead to more sophisticated cyberattacks. Future risks include evolving criminal tactics, privacy threats, skills shortages, and balancing security and individual rights.
Opportunities include AI-powered security, stronger global ties, and better cybersecurity. Dubai Police have launched a bilingual platform to educate the public, viewing awareness as the first defence against online threats.
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Nvidia and Advanced Micro Devices have agreed to hand 15% of their Chinese AI chip sales revenue to the US government in return for export licences.
The arrangement, covering Nvidia’s H20 accelerator and AMD’s MI308 model, is considered unusual and could prove contentious for both companies and Beijing.
The deal reflects Washington’s willingness to link trade concessions to financial payments, but analysts note there is little precedent for such a targeted export levy.
Critics warn the move could undermine the national security rationale for export controls, making it harder to convince allies to adopt similar measures. Beijing, meanwhile, has voiced security concerns over the H20 chip’s performance and alleged vulnerabilities.
Industry observers suggest the payment requirement could discourage further expansion by US chipmakers in China, the world’s largest semiconductor importer, and give local producers an advantage in building domestic capacity.
Chinese firms such as Huawei are already increasing market share amid tighter restrictions on US technology.
The potential sums involved are significant. Before restrictions were imposed, Nvidia had generated over $7 billion in H20 sales to China in a single quarter. In comparison, AMD could earn up to $5 billion annually if full access to the market resumed.
However, uncertainties over demand and regulatory conditions remain.
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Tesla has reportedly shut down its Dojo supercomputer project following multiple high-profile departures, including that of project head Peter Bannon. CEO Elon Musk ended the AI chip programme, reassigning the remaining staff to other data centre projects.
Dojo aimed to process vehicle data for autonomous driving and reduce Tesla’s reliance on Nvidia and AMD. The project faced delays, with leaders such as Jim Keller, Ganesh Venkataramanan, and Bannon departing before its closure.
About 20 former Dojo employees have joined DensityAI, a stealth startup founded by ex-Tesla staff, which is expected to work on AI chips for robots and data centres. Tesla will now rely more on Nvidia, AMD, and Samsung.
Samsung recently secured a $16.5 billion deal to supply AI chips for Tesla’s self-driving cars, robots, and data centres. Musk said Samsung’s Texas factory will produce Tesla’s AI6 chips, with AI5 chips to be made in 2026.
Musk suggested that combining AI5 and AI6 chips could form a ‘Dojo 3’ system, while Dojo 2 would not launch. The shutdown comes as Tesla restructures, with executive exits, job cuts, and renewed focus on AI integration across Musk’s companies.
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Riverlane has deployed its Deltaflow 2 quantum error correction (QEC) technology in a UK commercial quantum setting for the first time. The system introduces streaming quantum memory, enabling real-time error correction fast enough to preserve data across thousands of operations.
Deltaflow 2 combines a custom QEC chip with FPGA hardware and Riverlane’s software stack, supporting superconducting, spin, trapped-ion, and neutral-atom qubit platforms. It has been integrated with high-performance classical systems and a digital twin for noise simulation and monitoring.
Control hardware from Qblox delivers high-fidelity readout and ultra-low-latency links to enable real-time QEC. The deployment will validate error correction routines and benchmark system performance, forming the basis for future integration with OQC’s superconducting qubits.
The project is part of the UK Government-funded DECIDE programme, which aims to strengthen national capability in quantum error correction. Riverlane and OQC plan to demonstrate live QEC during quantum operations, supporting the creation of logical qubits for scalable systems.
Riverlane is also partnering with Infleqtion, Rigetti Computing, and others through the UK’s National Quantum Computing Centre. The company says growing industry demand reflects QEC’s shift from research to deployment, positioning Deltaflow 2 as a commercially viable, universally compatible tool.
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Colorado lawmakers face a dual challenge as they return to the State Capitol on 21 August for a special session: closing a $1.2 billion budget shortfall and revisiting a pioneering yet controversial law regulating AI.
Senate Bill 24-205, signed into law in May 2024, aims to reduce bias in AI decision-making affecting areas such as lending, insurance, education, and healthcare. While not due for implementation until February 2026, critics and supporters now expect that deadline to be extended.
Representative Brianna Titone, one of the bill’s sponsors, emphasised the importance of transparency and consumer safeguards, warning of the risks associated with unregulated AI. However, unexpected costs have emerged. State agencies estimate implementation could cost up to $5 million, a far cry from the bill’s original fiscal note.
Governor Polis has called for amendments to prevent excessive financial and administrative burdens on state agencies and businesses. The Judicial Department now expects costs to double from initial projections, requiring supplementary budget requests.
Industry concerns centre on data-sharing requirements and vague regulatory definitions. Critics argue the law could erode competitive advantage and stall innovation in the United States. Developers are urging clarity and more time before compliance is enforced.
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