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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Four Ghanaian nationals have been extradited to the United States over an international cybercrime scheme that stole more than $100 million, allegedly through sophisticated romance scams and business email compromise (BEC) attacks targeting individuals and companies nationwide.
The syndicate, led by Isaac Oduro Boateng, Inusah Ahmed, Derrick van Yeboah, and Patrick Kwame Asare, used fake romantic relationships and email spoofing to deceive victims. Businesses were targeted by altering payment details to divert funds.
US prosecutors say the group maintained a global infrastructure, with command and control elements in West Africa. Stolen funds were laundered through a hierarchical network to ‘chairmen’ who coordinated operations and directed subordinate operators executing fraud schemes.
Investigators found the romance scams used detailed victim profiling, while BEC attacks monitored transactions and swapped banking details. Multiple schemes ran concurrently under strict operational security to avoid detection.
Following their extradition, three suspects arrived in the United States on 7 August 2025, arranged through cooperation between US authorities and the Economic and Organised Crime Office of Ghana.
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Small language models are emerging as a serious challenger to large, general-purpose AI in translation, offering faster turnaround, lower costs, and greater accuracy for specific industries and language pairs.
Straker, an ASX-listed language technology firm, claims its Tiri model family can outperform larger systems by focusing on domain-specific understanding and terminology rather than broad coverage.
Tiri delivers higher contextual accuracy by training on carefully curated translation memories and sector-specific data, cutting the need for expensive human post-editing. The models also consume less computing power, benefiting finance, healthcare, and law industries.
Straker integrates human feedback directly into its workflows to ensure ongoing improvements and maintain client trust.
The company is expanding its technology into enterprise automation by integrating with the AI workflow platform n8n.
It adds Straker’s Verify tool to a network of over 230,000 users, allowing automated translation checks, real-time quality scores, and seamless escalation to human linguists. Further integrations with platforms like Microsoft Teams are planned.
Straker recently reported record profitability and secured a price target upgrade from broker Ord Minnett. The firm believes the future of AI translation lies not in scale but in specialised models that deliver translations that are both fluent and accurate in context.
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A recent report by Chainstory analysed 80,000 crypto news articles across five leading sites, revealing that 48% of them disclosed some form of AI use during 2025. Investing.com and The Defiant led in AI-generated or assisted content among the sites studied.
The extent of AI use across the broader industry may vary, as disclosure practices differ.
Editors interviewed for the report highlighted AI’s strengths and limitations. While AI proves valuable for research tasks such as summarising reports and extracting data, its storytelling ability remains weak.
Articles entirely written by AI often lack a genuine human tone, which can feel unnatural to audiences. One editor noted that readers can usually tell when content isn’t authored by a person, regardless of disclosure.
Afik Rechler, co-CEO of Chainstory, stated that AI is now an integral part of crypto journalism but has not replaced human reporters. He emphasised balancing AI help with human insight to keep readers’ trust, since current AI can’t manage complex, nuanced stories.
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Microsoft has launched Copilot 3D, an AI-powered tool that transforms 2D images into realistic 3D models without requiring specialist skills. Available through Copilot Labs, it aims to make 3D creation faster, more accessible, and more intuitive for global users signed in with a Microsoft account.
The tool supports only image-to-3D conversion, with no text-to-3D capability. Users can upload images up to 10 MB, generate a model, and download it in GLB format. Microsoft states uploaded images are used solely for model generation and are not retained for training or personalisation.
Copilot 3D is designed for applications that range from prototyping and creative exploration to interactive learning, thereby reducing the steep learning curve associated with conventional 3D programs. It can be used on PCs or mobile browsers; however, Microsoft recommends a desktop experience for optimal results.
Tech rivals are also advancing similar tools. Apple’s Matrix3D model can build 3D scenes from images, while Meta’s 3D Gen AI system creates 3D assets from text or applies textures to existing models. Nvidia’s NeRF technology generates realistic 3D scenes from multiple 2D images.
The release underscores growing competition in AI-driven 3D design, as companies race to make advanced modelling tools more accessible to everyday creators.
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The University of Western Australia has ordered a mass password reset for all staff and students after detecting unauthorised access to stored password data.
The incident was contained over the weekend by the university’s IT and security teams, who then moved to recovery and investigation. Australian authorities have been notified.
While no other systems are currently believed to have been compromised, access to UWA services remains locked until credentials are changed.
The university has not confirmed if its central access management system was targeted.
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US President Donald Trump has extended the pause on tariffs against Chinese goods by 90 days, postponing the deadline initially set for 12 August. The announcement triggered a sharp rise in Bitcoin’s price, which climbed to nearly $119,800 before returning to around $119,000.
Market watchers remain cautious, debating whether the price surge represents a lasting rally or a brief ‘Dead Cat Bounce.’ A CME futures gap below $119,000 may need to be filled before Bitcoin can sustain an uptrend.
The crypto market also awaits key US inflation data, with consumer and producer price figures expected in mid-August. These statistics could influence the Federal Reserve’s decisions, with a rate cut forecast for September growing more likely.
Crypto analyst Altcoin Sherpa outlined two possible paths for Bitcoin’s near-term movement. One scenario expects a gradual pullback to form a stable base, while the other anticipates a quick liquidity test near $120,000 influenced by treasury and economic factors.
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Hackers have stolen over $1 million in cryptocurrency using AI-generated malicious Firefox extensions disguised as legitimate wallet tools.
The group, known as GreedyBear, created over 150 fake add-ons for platforms like MetaMask and Phantom, bypassing security checks to drain funds from thousands of users. Analysts say AI enabled the attackers to automate coding and deployment at an industrial scale.
The theft comes amid a record-breaking year for crypto crime, with Chainalysis data showing over $2.17 billion stolen so far in 2025. Many incidents exploit smart contract flaws and human error, with access control attacks accounting for the most recent losses.
Security experts warn that AI is now a double-edged sword, helping attackers and defenders. They urge exchanges, developers, and users to adopt AI-powered monitoring, stronger verification, and collaborative defences to restore trust in digital assets.
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In mid-2025, the debate over AI in programming mirrors historic resistance to earlier breakthroughs in computing. Critics say current AI coding tools often slow developers and create overconfidence, while supporters argue they will eventually transform software creation.
The Register compares this moment to the 1950s, when Grace Hopper faced opposition to high-level programming languages. Similar scepticism greeted technologies such as C, Java, and intermediate representation, which later became integral to modern computing.
Current AI tools face limits in resources, business models, and capability. Yet, as past trends show, these constraints may fade as hardware, training, and developer practices improve. Advocates believe AI will shift human effort toward design and problem definition rather than manual coding.
For now, adoption remains a mixed blessing, with performance issues and unrealistic expectations. But history suggests that removing barriers between ideas and results catalyses lasting change.
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