Economic

Nvidia nears $4 trillion milestone as AI boom continues

Nvidia has made financial history by nearly reaching a $4 trillion market valuation, a milestone highlighting investor confidence in AI as a powerful economic force.

Shares briefly peaked at $164.42 before closing slightly lower at $162.88, just under the record threshold. The rise underscores Nvidia’s position as the leading supplier of AI chips amid soaring demand from major tech firms.

Led by CEO Jensen Huang, the company now holds a market value larger than the economies of Britain, France, or India.

Nvidia’s growth has helped lift the Nasdaq to new highs, aided in part by improved market sentiment following Donald Trump’s softened stance on tariffs.

However, trade barriers with China continue to pose risks, including export restrictions that cost Nvidia $4.5 billion in the first quarter of 2025.

Despite those challenges, Nvidia secured a major AI infrastructure deal in Saudi Arabia during Trump’s visit in May. Innovations such as the next-generation Blackwell GPUs and ‘real-time digital twins’ have helped maintain investor confidence.

The company’s stock has risen over 21% in 2025, far outpacing the Nasdaq’s 6.7% gain. Nvidia chips are also being used by the US administration as leverage in global tech diplomacy.

While competition from Chinese AI firms like DeepSeek briefly knocked $600 billion off Nvidia’s valuation, Huang views rivalry as essential to progress. With the growing demand for complex reasoning models and AI agents, Nvidia remains at the forefront.

Still, the fast pace of AI adoption raises concerns about job displacement, with firms like Ford and JPMorgan already reporting workforce impacts.

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Greece seizes crypto tied to record Bybit hack

Greek authorities have successfully seized digital assets linked to a major international cybercrime case, marking the country’s first-ever recovery of cryptocurrency. The operation followed a months-long investigation into suspicious blockchain activity in collaboration with blockchain analytics firm Chainalysis.

The recovered funds are part of a record-breaking $1.5 billion theft from crypto exchange Bybit earlier this year. In February, hackers exploited a vulnerability in one of the platform’s Ethereum wallets, transferring the entire contents to an unknown address.

The incident, considered one of the largest crypto heists in history, has been widely attributed to North Korea’s Lazarus Group.

A suspect wallet was identified and frozen, cutting off access to the assets and transferring the case to prosecutors for further legal proceedings.

Officials hailed the move as a significant advance in combating digital crime. Analysts say the operation shows how blockchain transparency and forensic tools, combined with international cooperation, can disrupt even the most complex laundering networks.

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Bitcoin hits new all-time high as institutional demand surges

Bitcoin has broken past its previous record, trading above $111,970 in a move that defied technical indicators and widespread scepticism. The rally, fuelled by institutional flows and growing corporate adoption, forced short sellers to capitulate after building up $35 billion in open interest.

Bitcoin’s latest breakout is driven by spot ETF inflows and corporate adoption, rather than retail speculation or halving narratives. In the second quarter alone, ETF providers absorbed 245,000 BTC—around 1% of the total supply—tightening liquidity and amplifying price pressure.

Analysts now view this as a structural shift where institutional demand outpaces miner issuance by a factor of three.

Stronger-than-expected US job data and fading hopes for a July rate cut failed to dent the crypto rally. The broader equity market also gained, with the S&P 500, Nasdaq, and Dow posting solid advances.

Bitcoin’s parallel rise suggests it is no longer merely a high-risk asset but increasingly seen as a liquidity hedge in uncertain conditions.

Geopolitical risks are quietly building. The Trump administration introduced new tariffs against six countries, potentially escalating global trade tensions. Historically, such moves have weighed on risk assets, but Bitcoin has remained resilient.

Analysts warn, however, that the situation could change by August if the tariffs are implemented.

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xAI unveils Grok 4 with top benchmark scores

Elon Musk’s AI company, xAI, has launched its latest flagship model, Grok 4, alongside an ultra-premium $300 monthly plan named SuperGrok Heavy.

Grok 4, which competes with OpenAI’s ChatGPT and Google’s Gemini, can handle complex queries and interpret images. It is now integrated more deeply into the social media platform X, which Musk also owns.

Despite recent controversy, including antisemitic responses generated by Grok’s official X account, xAI focused on showcasing the model’s performance.

Musk claimed Grok 4 is ‘better than PhD level’ in all academic subjects and revealed a high-performing version called Grok 4 Heavy, which uses multiple AI agents to solve problems collaboratively.

The models scored strongly on benchmark exams, including a 25.4% score for Grok 4 on Humanity’s Last Exam, outperforming major rivals. With tools enabled, Grok 4 Heavy reached 44.4%, nearly doubling OpenAI’s and Google’s results.

It also achieved a leading score of 16.2% on the ARC-AGI-2 pattern recognition test, nearly double that of Claude Opus 4.

xAI is targeting developers through its API and enterprise partnerships while teasing upcoming tools: an AI coding model in August, a multi-modal agent in September, and video generation in October.

Yet the road ahead may be rocky, as the company works to overcome trust issues and position Grok as a serious rival in the AI arms race.

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AI interviews leave job candidates in the dark

An increasing number of startups are now using AI to conduct video job interviews, often without making this clear to applicants. Senior software developers are finding themselves unknowingly engaging with automated systems instead of human recruiters.

Applicants are typically asked to submit videos responding to broad interview prompts, including examples and case studies, often without time constraints or human engagement.

AI processes these asynchronous interviews, which evaluate responses using natural language processing, facial cues and tone to assign scores.

Critics argue that this approach shifts the burden of labour onto job seekers, while employers remain unaware of the hidden costs and flawed metrics. There is also concern about the erosion of dignity in hiring, with candidates treated as data points rather than individuals.

Although AI offers potential efficiencies, the current implementation risks deepening dysfunctions in recruitment by prioritising speed over fairness, transparency and candidate experience. Until the technology is used more thoughtfully, experts advise job seekers to avoid such processes altogether.

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AI industry warned of looming financial collapse

Despite widespread popularity and unprecedented investment, OpenAI may be facing a deepening financial crisis. Since launching ChatGPT, the company has lost billions yearly, including an estimated $5 billion in 2024 alone.

Tech critic Ed Zitron argues that the AI industry is heading towards a ‘subprime AI crisis’, comparing the sector’s inflated valuations and spiralling losses to the subprime mortgage collapse in 2007. Startups like OpenAI and Anthropic continue to operate at huge losses.

Companies relying on AI infrastructure are already feeling the squeeze. Anysphere, which uses Anthropic’s models, recently raised prices sharply, angering users and blaming costs passed down from its infrastructure provider.

To manage exploding demand, OpenAI has also introduced tiered pricing and restricted services for free users, raising concerns that access to AI tools will soon be locked behind expensive paywalls. With 800 million weekly users, any future revenue strategy could alienate a large part of its global base.

Zitron believes these conditions cannot sustain long-term growth and will ultimately damage revenues and public trust. The industry, he warns, may be building its future on unstable ground.

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AI scam targets donors with fake orphan images

Cambodian authorities have warned the public about increasing online scams using AI-generated images to deceive donors. The scams often show fabricated scenes of orphaned children or grieving families, with QR codes attached to collect money.

One Facebook account, ‘Khmer Khmer’, was named in an investigation by the Anti-Cyber Crime Department for spreading false stories and deepfake images to solicit charity donations. These included claims of a wife unable to afford a coffin and false fundraising efforts near the Thai border.

The department confirmed that AI-generated realistic visuals are designed to manipulate emotions and lure donations. Cambodian officials continue investigations and have promised legal action if evidence of criminal activity is confirmed.

Authorities reminded the public to remain cautious and to only contribute to verified and officially recognised campaigns. While AI’s ability to create realistic content has many uses, it also opens the door to dangerous forms of fraud and misinformation when abused.

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AI fluency is the new office software skill

As tools like ChatGPT, Copilot, and other generative AI systems become embedded in daily workflows, employers increasingly prioritise a new skill: AI fluency.

Much like proficiency in office software became essential in the past, knowing how to collaborate effectively with AI is now a growing requirement across industries.

But interacting with AI isn’t always intuitive. Many users encounter generic or unhelpful responses from chatbots and assume the technology is limited. In reality, AI systems rely heavily on the context they are given, and that’s where users come in.

Rather than considering AI as a search engine, it helps to see it as a partner needing guidance. A vague prompt like ‘write a proposal’ is unlikely to produce meaningful results. A better approach provides background, direction, and clear expectations.

One practical framework is CATS: context, angle, task, and style.

Context sets the stage. It includes your role, the situation, the audience, and constraints. For example, ‘I’m a nonprofit director writing a grant proposal for an environmental education program in urban schools’ offers much more to work with than a general request.

Angle defines the perspective. You can ask the AI to act as a peer reviewer, a mentor, or even a sceptical audience member. The roles help shape the tone and focus of the response.

Task clarifies the action you want. Instead of asking for help with a presentation, try ‘Suggest three ways to improve my opening slide for an audience of small business owners.’

Style determines the format and tone. Whether you need a formal report, a friendly email, or an outline in bullet points, specifying the style helps the AI deliver a more relevant output.

Beyond prompts, users can also practice context engineering—managing the environment around the prompt. The method includes uploading relevant documents, building on previous chats, or setting parameters through instructions. The steps help tailor responses more closely to your needs.

Think of prompting as a conversation, not a one-shot command. If the initial response isn’t ideal, clarify, refine, or build on it. Ask follow-up questions, adjust your instructions, or extract functional elements to develop further in a new thread.

That said, it’s essential to stay critical. AI systems can mimic natural conversation, but don’t truly understand the information they provide. Human oversight remains crucial. Always verify outputs, especially in professional or high-stakes contexts.

Ultimately, AI tools are powerful collaborators—but only when paired with clear guidance and human judgment. Provide the correct input, and you’ll often find the output exceeds expectations.

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UN reports surge in intangible investment driven by AI and data

Global investment is increasingly flowing into intangible assets such as software, data, and AI, marking what the UN has described as a ‘fundamental shift’ in how economies develop and compete.

According to a new report from the World Intellectual Property Organisation (WIPO), co-authored with the Luiss Business School based in Italy, investment in intellectual property-related assets grew three times faster in 2024 than spending on physical assets like buildings and machinery.

WIPO reported that total intangible investment reached $7.6 trillion across 27 high- and middle-income economies last year, up from $7.4 trillion in 2023—a real-term growth rate of 3 percent. In contrast, growth in physical asset investment has been more sluggish, hindered by high interest rates and a slow economic recovery.

‘We’re witnessing a fundamental shift in how economies grow and compete,’ said WIPO Director General Daren Tang. ‘While businesses have slowed down investing in factories and equipment during uncertain times, they’re doubling on intangible assets.’

The report highlights software and databases as the fastest-growing categories, expanding by more than 7 percent annually between 2013 and 2022. It attributes much of this trend to the accelerating adoption of AI, which requires significant investment in data infrastructure and training datasets.

WIPO also noted that the United States remains the global leader in absolute intangible investment, spending nearly twice as much as France, Germany, Japan, and the United Kingdom. However, Sweden topped the list regarding investment intensity, with intangible assets representing 16 per cent of its GDP.

The US, France, and Finland followed at 15 percent each, while India ranked ahead of several EU countries and Japan at an intensity of nearly 10 percent.

Despite economic disruptions over the past decade and a half, intangible investments have remained resilient, growing at a compound annual rate of 4 percent since 2008. By contrast, investment in tangible assets rose just 1 percent over the same period.

‘We are only at the beginning of the AI boom,’ said Sacha Wunsch-Vincent, head of WIPO’s economics and data analytics department.

He noted that in addition to driving demand for physical infrastructure like chips and servers, AI is now contributing to sustained investment growth in data and software, cornerstones of the intangible economy.

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Countries build state-level Bitcoin reserves worldwide

Bitcoin is no longer the preserve of tech-savvy investors and crypto enthusiasts. As of mid-2025, more than 460,000 BTC — around 2.3% of the total supply — is held by governments worldwide, according to blockchain data and legal disclosures.

The shift has elevated Bitcoin’s role in global finance, making it a strategic asset for nation-states.

The United States leads the pack with nearly 200,000 BTC, acquired mainly through criminal seizures. Unlike previous administrations, President Trump’s government has moved to consolidate these funds under a federal Strategic Bitcoin Reserve.

China follows closely behind, having confiscated 190,000 BTC from the PlusToken scam, though the fate of much of that stash remains unclear.

Beyond the prominent players, countries like Bhutan have quietly amassed impressive reserves. Using hydropower for mining, Bhutan has reportedly gathered up to 13,000 BTC — worth over $1 billion — equating to more than a third of its GDP.

Meanwhile, the UK holds 61,000 BTC from a money-laundering case, Ukraine used Bitcoin donations during wartime, and Iran requires licensed miners to send their BTC directly to the central bank.

While some nations broadcast their Bitcoin strategy, others operate in silence. From El Salvador’s legal tender experiment to rumours of holdings in the UAE and Bulgaria, the landscape is varied and opaque. Still, one trend is clear: state-level Bitcoin adoption is no longer theoretical.

Governments are actively shaping the future of decentralised money — sometimes loudly, often quietly, but always strategically.

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