Alphabet Archives - Taking Stock

February 25, 2026February 25, 2026

IBM Shares Slide as AI Threatens Its Legacy Stronghold

When artificial intelligence first ignited investor enthusiasm, it lifted almost every major technology stock.

The narrative was simple: AI would transform industries, boost productivity and unlock vast new revenue streams.

Yet as the cycle matures, markets are becoming more selective. In recent weeks, shares of IBM have drifted lower, illustrating how the ‘AI effect’ can cut both ways.

At first glance, IBM should be a prime beneficiary. The company has spent years repositioning itself around hybrid cloud infrastructure, data analytics and enterprise AI solutions.

Its Watson platform has been refreshed with generative AI tools designed to automate customer service, streamline software development and enhance business decision-making. Management has repeatedly emphasised AI as a core growth engine.

Market Expectations

However, the market’s expectations have shifted. Investors are increasingly rewarding companies that sit at the very heart of AI infrastructure — those supplying advanced semiconductors, high-performance computing capacity and hyperscale cloud services.

These businesses are reporting visible surges in AI-related demand, often accompanied by sharp revenue acceleration and expanding margins.

By contrast, IBM’s AI exposure is embedded within broader consulting and software operations, making its growth trajectory appear steadier rather than explosive.

This distinction matters in a momentum-driven environment. When earnings updates fail to deliver dramatic upside surprises, shares can quickly lose favour.

Less AI Effect

IBM’s results have shown progress in software and recurring revenue, but they have not reflected the kind of dramatic AI-driven uplift seen elsewhere in the sector. For some investors, that raises questions about competitive positioning and pricing power.

There is also a perception issue. Despite its reinvention efforts, IBM still carries the legacy image of a mature technology conglomerate rather than a cutting-edge AI disruptor.

In a market captivated by bold innovation stories, narrative can influence valuation just as much as fundamentals.

If capital flows concentrate in a handful of high-growth AI names, diversified players may struggle to keep pace in share price performance.

AI Tension

Yet the sell-off may also highlight a deeper tension within the AI theme. Enterprise adoption of AI tools tends to be gradual, cautious and closely tied to measurable productivity gains.

IBM’s strategy is built around long-term integration rather than short-term hype. While that approach may lack immediate fireworks, it could prove more durable as corporate clients prioritise reliability, governance and cost control.

For now, though, the AI effect is amplifying investor discrimination. In a market eager for rapid transformation, IBM’s more measured path has translated into weaker share performance — a reminder that not all AI exposure is valued equally.

Further discussion

IBM has found itself on the wrong side of the artificial intelligence boom, with its shares tumbling more than 13% after Anthropic unveiled a new capability that directly targets one of the company’s most enduring revenue pillars: COBOL modernisation.

The sell‑off reflects a broader market anxiety that AI is beginning to erode long‑protected niches in enterprise technology, and IBM has become the latest high‑profile casualty.

For decades, IBM has been synonymous with mainframe computing and the maintenance of vast COBOL‑based systems that underpin global finance, government services, airlines, and retail transactions.

These systems are notoriously complex, expensive to update, and dependent on a shrinking pool of specialist developers.

Premium Brand

That scarcity has long worked in IBM’s favour, allowing it to charge a premium for modernisation and support.

Anthropic’s announcement threatens to upend that equation. Its Claude Code tool, the company claims, can automate the most time‑consuming and costly parts of understanding and restructuring legacy COBOL environments.

Tasks that once required teams of analysts months to complete—mapping dependencies, documenting workflows, identifying risks—can now be accelerated dramatically through AI‑driven analysis.

The implication is clear: modernising legacy systems may no longer require the same level of human expertise, nor the same level of spending.

Investors reacted swiftly. IBM’s share price fell to $223.35, extending a year‑to‑date decline of more than 24% – recovering later to $229.39

IBM one-year chart as of 24th February 2026

The drop reflects not only concerns about lost revenue, but also the fear that IBM’s competitive moat—built on decades of institutional reliance on COBOL—may be eroding faster than expected.

The timing has amplified market jitters. Only days earlier, cybersecurity stocks were hit by another Anthropic announcement: Claude Code Security, a feature designed to scan codebases for vulnerabilities.

AI Mood Logic

The rapid expansion of AI into specialised technical domains has created a ‘sell first, ask questions later’ mood across the market, with investors increasingly wary of companies whose business models depend on labour‑intensive or legacy‑bound processes.

For IBM, the challenge now is to demonstrate that it can harness AI rather than be displaced by it.

The company has invested heavily in its own AI initiatives, but the latest market reaction suggests investors are unconvinced that these efforts will offset the threat to its traditional strongholds.

The AI revolution is reshaping the technology landscape at speed. IBM’s sharp decline is a reminder that even the industry’s oldest giants are not insulated from disruption—and that the next wave of AI competition may hit the most established players hardest.

But remember, this is IBM we are talking about.

Explainer

What is COBOL?

COBOL is an old but remarkably durable programming language created in the late 1950s to run business, finance, and government systems, and it’s still powering much of the world’s banking and administrative infrastructure today.

It was designed to read almost like plain English, making it easier for non‑technical managers to understand, and its stability means many core systems have never been replaced.

February 24, 2026February 24, 2026

Is the Magnificent Seven Trade a little less Magnificent now?

For much of the past three years, the so‑called Magnificent Seven – Apple, Microsoft, Alphabet, Amazon, Meta, Tesla and Nvidia – have powered US equities to repeated record highs.

Their sheer scale, earnings strength and centrality to the AI boom turned them into a market narrative as much as an investment theme.

But as 2026 unfolds, the question is no longer whether they can keep leading the market higher, but whether the idea of treating them as a single trade still makes sense.

The short answer is closer to: the trade isn’t dead, but the era of effortless, broad‑based mega‑cap dominance is fading.

Mag 7 fatigue

The first sign of fatigue is the breakdown in cohesion. Last year, only a minority of the seven outperformed the wider S&P 500, a sharp contrast to the near‑uniform surges of 2023 and early 2024.

Nvidia and Alphabet continue to benefit from the structural demand for AI infrastructure and cloud‑driven productivity gains. Others, however, appear to be wrestling with slower growth, regulatory pressure or strategic resets.

Apple faces a maturing hardware cycle, Tesla is contending with intensifying global competition, and Meta’s spending plans continue to divide investors.

Divergence

This divergence matters. For years, investors could simply buy the group and let the rising tide of AI enthusiasm and index concentration do the work.

That simplicity has evaporated. Stock‑picking is back, and the market is finally distinguishing between companies with accelerating earnings power and those relying on past momentum.

At the same time, market breadth is improving. Capital is rotating into industrials and defensive sectors as investors seek exposure to areas that have lagged the mega‑cap rally. However, AI is affecting software stocks, law and financial sectors.

Healthy future

This broadening is healthy: it reduces concentration risk and signals that the U.S. economy is no longer dependent on a handful of tech giants to sustain equity performance.

Yet it would be premature to declare the Magnificent Seven irrelevant. Their combined earnings growth is still expected to outpace the rest of the index, and their role in AI, cloud computing and digital infrastructure remains foundational.

Change

What has changed is the nature of the trade. These are no longer seven interchangeable vehicles for tech exposure; they are seven distinct stories with diverging trajectories.

The Magnificent Seven haven’t left the stage. They have likely stopped performing in unison – and for investors, that marks the beginning of a more nuanced, more selective chapter.

February 19, 2026February 18, 2026

Alibaba’s Qwen 3.5 Marks a Strategic Shift Toward AI Agents

Alibaba has unveiled Qwen 3.5, its latest large language model series, signalling a decisive shift in China’s increasingly competitive AI landscape.

Released on the eve of the Chinese New Year, the new model arrives with both open‑weight and hosted versions, giving developers the option to run the system on their own infrastructure or through Alibaba’s cloud platform.

The company emphasises that Qwen 3.5 delivers improved performance and lower operating costs compared with earlier iterations, while introducing ‘native multimodal capabilities’ that allow it to process text, images, and video within a single system.

Ability

What sets Qwen 3.5 apart is its focus on agentic behaviour — the ability for AI systems to take actions, complete multi‑step tasks, and operate with minimal human supervision.

This trend has accelerated globally following recent releases from Anthropic and other U.S. based developers, prompting Chinese firms to respond rapidly.

Alibaba says Qwen 3.5 is compatible with popular open‑source agent frameworks such as OpenClaw, which has surged in adoption among developers seeking more autonomous AI tools.

Capable

The open‑weight version features 397 billion parameters, fewer than Alibaba’s previous flagship model, yet the company claims significant gains in reasoning and benchmark performance.

It also supports 201 languages and dialects — a notable expansion that reflects Alibaba’s ambition to position Qwen as a global‑ready platform rather than a purely domestic competitor.

With rivals like ByteDance and Zhipu AI launching their own upgraded models, Qwen 3.5 underscores how China’s AI race is evolving from chatbot development to full‑scale autonomous agents — a shift that could reshape software markets and business models worldwide.

February 17, 2026February 17, 2026

Can Hyperscalers Really Justify Their Colossal AI Capex?

The world’s largest cloud providers are engaged in one of the most expensive technological races in history.

Amazon, Microsoft, Meta and Alphabet are collectively on track to spend as much as $700 billion on AI‑related capital expenditure this year — a figure that rivals the GDP of mid‑sized nations and has understandably rattled investors.

The question now dominating markets is simple: can hyperscalers justify this level of spending, and should analysts remain so bullish on their stocks?

A Binary Bet on the Future of AI

The scale of investment has shifted the AI build‑out from a strategic growth initiative to what some analysts describe as a binary corporate bet. As some analysts suggest, the leap in capex — up roughly 60% year‑on‑year — means the payoff must be both rapid and substantial.

If monetisation fails to keep pace, the consequences could be of severe concern.

This is compounded by the fact that hyperscalers are now consuming nearly all of their operating cash flow to fund AI infrastructure, compared with a decade‑long average of around 40%. That shift alone explains the recent market jitters.

Why Analysts Remain Upbeat

Despite the turbulence, many analysts still argue the long‑term fundamentals remain intact. One reason is that hyperscalers are pre‑selling data‑centre capacity before it is even built, effectively locking in revenue ahead of deployment.

That dynamic supports the bullish view that AI demand is not only real but accelerating.

There is also a belief that as AI tools become embedded across consumer and enterprise workflows, willingness to pay will rise sharply.

If that scenario plays out, today’s eye‑watering capex could look prescient rather than reckless.

The Real Risk: Timelines

The challenge is timing. Much of the infrastructure being deployed — from chips to data‑centre hardware — has a useful life of just three to five years.

That gives hyperscalers a narrow window to recoup investment before the next upgrade cycle hits.

Without clearer monetisation strategies and firmer payback timelines, investor anxiety is likely to persist.

AI capex justification?

Hyperscalers can justify their AI capex — but only if demand scales as quickly as they expect and monetisation becomes more transparent.

Analysts may be right to stay bullish, but the margin for error is shrinking. In the coming quarters, clarity will matter as much as capital.

February 13, 2026February 13, 2026

Alphabet’s 100‑Year Bond: Ambition, Appetite and Anxiety in the AI Debt Boom

Alphabet’s decision to issue a 100-year sterling bond has captured the attention of global markets, not only because of its rarity but also because of what it signals about the escalating competition in artificial intelligence.

100 year sterling bond

A century-long bond denominated in pounds is an extraordinary financing move, particularly for a technology company.

It reflects both investor confidence in Alphabet’s long-term prospects and the scale of capital now required to compete in the AI era.

On the surface, the benefits are clear. Locking in funding for 100 years at today’s rates provides financial certainty. Alphabet can secure vast sums of capital without facing refinancing risk for generations.

In an industry defined by rapid change and enormous upfront costs — from data centres and semiconductor procurement to specialised AI chips and energy infrastructure — patient capital is invaluable.

Sterling

The sterling denomination also diversifies Alphabet’s funding base beyond U.S. dollar markets, potentially appealing to European institutional investors seeking stable, long-duration assets.

The bond may also be interpreted as a strategic signal. By committing to long-term financing, Alphabet demonstrates confidence in its ability to generate cash flows well into the next century.

It reinforces the company’s image as a durable, infrastructure-like enterprise rather than a volatile technology stock.

For investors such as pension funds and insurers, a 100-year instrument from a highly rated issuer can offer predictable returns in a world where long-term yield is scarce.

Cyclical

However, the move is not without shortcomings. Committing to fixed debt obligations over such an extended horizon reduces flexibility. While Alphabet currently enjoys strong balance sheet metrics, the technology sector is notoriously cyclical.

A century is an eternity in innovation terms. Business models, regulatory frameworks and geopolitical dynamics may shift dramatically.

Future generations of management will inherit the obligation, regardless of whether today’s AI investments deliver the expected returns.

More broadly, the bond feeds concern about a debt-fuelled AI arms race. As technology giants pour tens of billions into AI research, chip design and cloud infrastructure, borrowing is becoming an increasingly prominent tool.

If rivals respond with similar long-dated issuance, the sector’s leverage could rise meaningfully. In a downturn or if AI monetisation disappoints; heavy debt burdens could amplify financial strain.

Ultimately, Alphabet’s 100-year sterling bond embodies both ambition and risk. It underlines the immense capital demands of the AI revolution while raising questions about whether today’s competitive fervour is encouraging companies to stretch their balance sheets too far in pursuit of technological dominance.

Systemic anxiety

The deeper anxiety is systemic. With Oracle, Amazon, Microsoft and others also scaling up borrowing, total tech‑sector issuance is projected to hit $3 trillion over five years.

Some analysts warn this resembles a late‑cycle credit boom, where investors chase thematic excitement rather than sober fundamentals.

Alphabet’s century bond may be a masterstroke of timing — or a marker of excess.

Either way, it crystallises the tension at the heart of the AI revolution: extraordinary promise, financed by extraordinary debt.

Why a Sterling Bond?

Alphabet issued its 100‑year sterling bond to tap deep UK demand for ultra‑long‑dated assets, especially from pension funds seeking to match long‑term liabilities.

The sterling market offered strong appetite, with orders reportedly reaching nearly ten times the £1 billion on offer.

It also formed part of Alphabet’s broader multi‑currency fundraising drive to finance massive AI‑related capital spending, including data‑centre expansion.

Issuing in sterling diversified its investor base, reduced reliance on U.S. dollar markets, and signalled confidence in its long‑term stability as a quasi‑infrastructure‑scale business.

It’s all debt; however you look at it!

December 2, 2025December 2, 2025

Artificially Inflated Artificial Intelligence Stocks – The FOMO Effect?

The meteoric rise of artificial intelligence (AI) stocks has captivated investors worldwide, but beneath the headlines lies a growing concern: are these valuations built on genuine fundamentals, or are they the product of collective psychology?

Increasingly, analysts point to the possibility that the fear of missing out (FOMO) is a potential driver of this rally, especially in the AI related ‘retail’ trader.

The European Central Bank recently warned that AI-related equities, particularly the so-called ‘Magnificent Seven’ tech giants—Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla—are showing signs of ‘stretched valuations‘.

This echoes the dot-com bubble of the late 1990s, when enthusiasm for the internet led to unsustainable price surges.

Today, investors are piling into AI stocks not only because of their technological promise but also because they fear being left behind in what could be a transformative era.

Nvidia, now the world’s most valuable company, exemplifies this trend. Its dominance in AI chips has fuelled extraordinary gains, yet critics argue its valuation has raced far ahead of realistic earnings expectations.

The psychology is clear: when investors see others profiting, they rush in, often ignoring traditional measures of risk and return.

This dynamic creates a paradox. On one hand, AI undeniably represents a revolutionary force with vast potential across industries. On the other, the concentration of capital in a handful of firms raises systemic risks.

If expectations falter, the correction could be brutal, much like the dot-com crash that erased trillions in market value.

Ultimately, the AI boom may prove to be both a genuine technological leap and a speculative bubble. For sure there are undeniable revolutionary technological advancements right now – but is it all just too fast and too soon?

The challenge for investors is to distinguish between sustainable growth and hype-driven inflation—before it is too late.

The FOMO monster is definitely ‘artificially’ affecting the U.S. stock market – it will likely reveal itself soon.

November 26, 2025November 26, 2025

When Markets Lean Too Heavily on High Flyers

The recent rebound in technology shares, led by Google’s surge in artificial intelligence optimism, offered a welcome lift to investors weary of recent market sluggishness.

Yet beneath the headlines lies a more troubling dynamic: the increasing reliance on a handful of mega‑capitalisation firms to sustain broader equity gains.

Breadth

Markets thrive on breadth. A healthy rally is one in which gains are distributed across sectors, signalling confidence in the wider economy. When only one or two companies shoulder the weight of investor sentiment, the picture becomes distorted.

Google’s AI announcements may well justify enthusiasm, but the fact that its performance alone can swing indices highlights a fragility in the current market structure.

This concentration risk is not new. In recent years, the so‑called ‘Magnificent Seven‘ technology giants have dominated returns, masking weakness in smaller firms and traditional industries.

While investors cheer the headline numbers, the underlying reality is that many sectors remain subdued. Manufacturing, retail, and even parts of the financial industry are not sharing equally in the rally.

Over Dependence

Over‑dependence on highflyers creates two problems. First, it exposes markets to sudden shocks: if sentiment turns against one of these giants, indices can tumble disproportionately.

Second, it discourages capital from flowing into diverse opportunities, stifling innovation outside the tech elite.

For long‑term stability, investors and policymakers alike should be wary of celebrating narrow gains. A resilient market requires participation from a broad base of companies, not just the fortunes of a few.

Google’s success in AI is impressive, but true economic strength will only be evident when growth spreads beyond the marquee names.

Until then, the market remains vulnerable, propped up by giants whose shoulders, however broad, cannot carry the entire economy indefinitely.

November 19, 2025November 19, 2025

Anthropic’s ‘connected’ AI deal and others too

Anthropic has reportedly struck major deals with Microsoft and Nvidia. On Tuesday 18th November 2025, Microsoft announced plans to invest up to $5 billion in the startup, while Nvidia will contribute as much as $10 billion. According to a reports, this brings Anthropic’s valuation to around $350 billion. Wow!

Google has unveiled its newest AI model, Gemini 3. According to Alphabet CEO Sundar Pichai, it will deliver desired answers with less prompting.

This update comes just eight months after the launch of Gemini 2.5 and is reported to be available in the coming weeks.

Money keeps flowing

Money keeps flowing into artificial intelligence companies but out of AI stocks

In what seems like yet another case of mutual ‘back-scratching’, Microsoft and Nvidia are set to invest a combined $15 billion in Anthropic, with the OpenAI rival agreeing to purchase computing power from its two newest backers.

Lately, a large chunk of AI news feels like it boils down to: ‘Company X invests in Company Y, and Company Y turns around and buys from Company X’.

That’s not entirely correct or fair. There are plenty of advancements in the AI world that focus on actual development rather than investments. Google recently introduced the third version of Gemini, its AI model.

Anthropic’s valuation has surged to around $350 billion, propelled by a landmark $15 billion investment from Microsoft and Nvidia.

Anthropic, the AI start-up founded in 2021 by former OpenAI employees, has rapidly ascended into the ranks of the world’s most valuable companies, more than doubling its worth from $183 billion just a few months earlier.

A valuation of $350 billion for a company only 4 years old is astounding!

The deal reportedly sees Microsoft commit up to $5 billion and Nvidia up to $10 billion. Anthropic has agreed to purchase an extraordinary $30 billion in Azure compute capacity and additional infrastructure from Nvidia.

This strategic alliance is not merely financial; it signals a deliberate diversification of Microsoft’s AI ecosystem beyond its reliance on OpenAI. And Nvidia strengthens its dominance in AI hardware.

Anthropic’s valuation has reached $350 billion, following the massive $15 billion investment from Microsoft and Nvidia, which positions the company among the most valuable in the world.

This astronomical figure reflects both the scale of its partnerships — including $30 billion in Azure compute commitments and Nvidia’s cutting-edge hardware.

The valuation underscores both the intensity of the global AI race and the confidence investors place in Anthropic’s safety-conscious approach to artificial intelligence.

Yet, it also raises questions about whether such astronomical figures reflect genuine long-term value. Or is it the froth of an overheated market.

Hyperscalers keep pumping the money into AI but are they getting the justified returns yet? Probably not yet – but it will come in the future.

But by then, it will be time to upgrade the system as it develops and so more money will be pumped in

November 18, 2025

Pichai Warns of AI Bubble: Google Not Immune to Market Correction

Google CEO Sundar Pichai has warned that no company, including his own, will be immune if the current AI bubble bursts.

He described the boom as both extraordinary and irrational, urging caution amid soaring valuations and investment hype

In a recent interview, Google’s chief executive Sundar Pichai offered a sobering perspective on the rapid expansion of artificial intelligence.

Profound Tech Creation

While he reportedly reaffirmed his belief that AI is ‘the most profound technology humanity has developed‘, he acknowledged growing concerns that the sector may be overheating.

According to Pichai, the surge in investment and valuations has created an atmosphere of exuberance that risks tipping into irrationality.

Pichai stressed that if the so-called AI bubble were to collapse, no company would escape unscathed. Even Google, one of the world’s most powerful technology firms, would feel the impact.

Remember Dot-Com?

He likened the current moment to past speculative cycles, such as the dot-com boom, where innovation was genuine, but market expectations outpaced reality.

Despite these warnings, Pichai emphasised that the long-term potential of AI remains intact.

He argued that professions across the board—from teaching to medicine—will continue to exist, but success will depend on how well individuals adapt to using AI tools.

In his view, the technology will reshape industries, but the hype surrounding short-term gains could distort investment flows and create instability.

His comments arrive at a time when Silicon Valley is grappling with questions about sustainability. Tech stocks have surged on AI optimism, yet analysts caution that inflated valuations may not reflect the true pace of adoption.

Pichai’s intervention serves as both a reality check and a reminder: AI is transformative, but it is not immune to market corrections.

For investors and innovators alike, the message is clear—embrace AI’s promise but prepare for turbulence if the bubble bursts.

November 3, 2025November 4, 2025

Google Goes Nuclear: Part 1 Powering the AI Revolution with Atomic Energy

In a bold move that signals the escalating energy demands of artificial intelligence, Google has announced plans to invest heavily in nuclear power to fuel its data centres.

As AI models grow more complex and compute-intensive, the tech giant is turning to atomic energy as a stable, carbon-free solution to meet its insatiable appetite for electricity.

The shift comes amid mounting scrutiny over the environmental impact of AI. Training large language models and running real-time inference across billions of queries requires vast amounts of energy—often sourced from fossil fuels.

Google’s pivot to nuclear is both a strategic and symbolic gesture: a commitment to sustainability, but also a recognition that the AI era demands a fundamentally different energy paradigm.

SMR’s

At the heart of this initiative is Google’s partnership with advanced nuclear startups exploring small modular reactors (SMRs) and next-generation fission technologies.

Unlike traditional nuclear plants, SMRs are designed to be safer, more scalable, and quicker to deploy—making them ideal for powering decentralised data infrastructure.

Google’s goal is to integrate these reactors directly into its cloud and AI campuses, creating a closed-loop ecosystem where clean energy powers the very machines shaping the future.

Critics, however, warn of the risks. Nuclear waste, regulatory hurdles, and public perception remain significant barriers.

Some environmentalists argue that the urgency of the climate crisis demands faster, more proven solutions like solar and wind. Yet others see nuclear as a necessary complement—especially as AI accelerates demand beyond what renewables alone can supply.

This isn’t Google’s first foray into atomic ambition. In 2022, it backed nuclear fusion research through its DeepMind subsidiary, applying AI to optimise plasma control.

Now, with fission in focus, the company appears determined to lead not just in AI innovation, but in the infrastructure that sustains it.

The implications are profound. If successful, Google’s nuclear strategy could set a precedent for the entire tech industry, reshaping how data is powered in the 21st century.

It also raises deeper questions: Can the tools of the future be truly sustainable? And what does it mean when the intelligence we build begins to reshape the energy systems that built us?

One thing is clear—AI isn’t just changing how we think. It’s changing what we power, and how we power it.

October 24, 2025October 23, 2025

Has the S&P 500 Become an AI Index?

In recent months, the S&P 500 has shown signs of evolving from a broad economic barometer into something far more concentrated: a proxy for artificial intelligence optimism.

While traditionally viewed as a diversified snapshot of American corporate health, the index’s current composition and market behaviour suggest it’s increasingly tethered to the fortunes of a handful of AI-driven giants.

At the heart of this transformation is the dominance of mega-cap tech firms. Microsoft, Nvidia, Alphabet, Amazon, Meta, and Apple now account for a disproportionate share of the index’s total market capitalisation.

As of late 2025 that heady combination of AI led tech represents just over 30% of the S&P 500.

AI in S&P 500 — Six AI related companies represent 30% of the S&P 500

These companies aren’t merely adjacent to AI—they’re building its infrastructure, shaping its software ecosystems, and embedding it into consumer and enterprise products.

Nvidia, for instance, has become synonymous with AI hardware, its valuation soaring on the back of demand for high-performance chips powering generative models and data centres.

Recent analysis reveals that roughly 8% of the S&P 500’s weight is directly tied to AI-related revenue.

An additional 25 companies within the index are actively developing AI technologies, even if those efforts haven’t yet translated into standalone revenue streams. This includes sectors as varied as autonomous vehicles, quantum computing, and predictive analytics.

Investor behaviour has only amplified this shift. The index’s recent rally has been fuelled largely by enthusiasm for AI breakthroughs, with capital flowing into stocks perceived as future beneficiaries of machine learning and automation.

This momentum has led some analysts to warn of valuation bubbles, urging diversification away from AI-heavy names in case of a sector-wide correction.

Narrower narrative

Symbolically, the S&P 500’s identity is shifting. Once a mirror of industrial and consumer strength, it now reflects a narrower narrative—one of technological acceleration and speculative belief in artificial intelligence.

This raises philosophical questions about what the index truly represents: is it still a measure of economic breadth, or has it become a momentum gauge for a single transformative theme?

For editorial observers, this evolution offers fertile ground. The index’s transformation can be read not just as a financial trend, but as a cultural signal—suggesting that AI is no longer a niche innovation, but the dominant lens through which investors, executives, and policymakers interpret the future.

Whether this concentration proves visionary or vulnerable remains to be seen.

But one thing is clear: the S&P 500 is no longer just a mirror of the American economy—it’s increasingly a reflection of our collective bet on intelligent machines.

30% of S&P 500

As of 2025, Microsoft, Nvidia, Alphabet, Amazon, Meta, and Apple—often grouped as part of the ‘Magnificent Seven’—collectively represent approximately 30% of the S&P 500’s total market capitalisation.

That’s a staggering concentration for just six companies in an index meant to reflect the broader U.S. economy.

For context, their combined performance was responsible for roughly two-thirds of the S&P 500’s total gains in 2024—a clear signal that the index’s movement is increasingly tethered to the fortunes of a few dominant tech giants.

October 9, 2025October 9, 2025

AI Crash! Correction or pullback? Something is coming…

Influential figures and institutions are sounding the AI alarm—or at least raising eyebrows—about the frothy valuations and speculative fervour surrounding artificial intelligence.

Who’s Warning About the AI Bubble?

🏛️ Bank of England – Financial Policy Committee

View: Stark warning.
Quote: “The risk of a sharp market correction has increased.”
Why it matters: The BoE compares current AI stock valuations to the dotcom bubble, noting that the top five S&P 500 firms now command nearly 30% of market cap—the highest concentration in 50 years.

🏦 Jerome Powell – Chair, U.S. Federal Reserve

View: Cautiously sceptical.
Quote: Assets are “fairly highly valued.”
Why it matters: While not naming AI directly, Powell’s remarks echo broader concerns about tech valuations and investor exuberance.

🧮 Lisa Shalett – Chief Investment Officer, Morgan Stanley Wealth Management

View: Deeply concerned.
Quote: “This is not going to be pretty” if AI capital expenditure disappoints.
Why it matters: Shalett warns that 75% of S&P 500 returns are tied to AI hype, likening the moment to the “Cisco cliff” of the early 2000s.

🌍 Kristalina Georgieva – Managing Director, IMF

View: Watchful.
Quote: Financial conditions could “turn abruptly.”
Why it matters: Georgieva highlights the fragility of markets despite AI’s productivity promise, warning of sudden sentiment shifts.

🧨 Sam Altman – CEO, OpenAI

View: Self-aware caution.
Quote: “People will overinvest and lose money.”
Why it matters: Altman’s admission from inside the AI gold rush adds credibility to bubble concerns—even as his company fuels the hype.

📦 Jeff Bezos – Founder, Amazon

View: Bubble-aware.
Quote: Described the current environment as “kind of an industrial bubble.”
Why it matters: Bezos sees parallels with past tech manias, suggesting that infrastructure spending may be overextended.

🧠 Adam Slater – Lead Economist, Oxford Economics

View: Analytical.
Quote: “There are a few potential symptoms of a bubble.”
Why it matters: Slater points to stretched valuations and extreme optimism, noting that productivity projections vary wildly.

🏛️ Goldman Sachs – Investment Strategy Division

View: Cautiously optimistic.
Quote: “A bubble has not yet formed,” but investors should “diversify.”
Why it matters: Goldman acknowledges the risks while maintaining that fundamentals may still justify valuations—though they advise caution.

AI Bubble voices infographic October 2025

🧠 Julius Černiauskas and the Oxylabs AI/ML Advisory Board

🔍 View: The AI hype is nearing its peak—and may soon deflate.

Černiauskas warns that AI development is straining environmental resources and public trust. He’s pushing for responsible and sustainable AI practices, noting that transparency is lacking in how many models operate.
Ali Chaudhry, research fellow at UCL and founder of ResearchPal, adds that scaling laws are showing their limits. He predicts diminishing returns from simply making models bigger, and expects tightened regulations around generative AI in 2025.
Adi Andrei, cofounder of Technosophics, goes further: he believes the Gen AI bubble is on the verge of bursting, citing overinvestment and unmet expectations

🧠 Jamie Dimon on the AI Bubble

🔥 View: Sharply concerned—more than most as widely reported

Quote: “I’m far more worried than others about the prospects of a downturn.”
Context: Dimon believes AI stock valuations are “stretched” and compares the current surge to the dotcom bubble of the late 1990s.

📉 Key Warnings from Dimon

“Sharp correction” risk: He sees a real danger of a sudden market pullback, especially given how AI-related stocks have surged disproportionately—like AMD jumping 24% in a single day after an OpenAI deal.
“Most people involved won’t do well”: Dimon told the BBC that while AI will ultimately pay off—like cars and TVs did—many investors will lose money along the way.
“Governments are distracted”: He criticised policymakers for focusing on crypto and ignoring real security threats, saying: “We should be stockpiling bullets, guns and bombs”.
“AI will disrupt jobs and companies”: At a trade event in Dublin, he warned that AI’s ubiquity will shake up industries and employment across the board.

And so…

The AI boom of 2025 has ignited a speculative frenzy across global markets, with tech stocks soaring and investors piling into anything labelled “AI-adjacent.”

But beneath the euphoria, a chorus of high-profile warnings is growing louder. From the Bank of England and IMF to JPMorgan’s Jamie Dimon and OpenAI’s Sam Altman, concerns are mounting that valuations are dangerously stretched, capital is overconcentrated, and the narrative is outpacing reality.

Dimon likens the moment to the dotcom bubble, while Altman admits many will “lose money” chasing the hype. Analysts point to classic bubble signals: retail mania, corporate FOMO, and earnings divorced from fundamentals.

Even as AI’s long-term utility remains promising, the short-term exuberance may be setting the stage for a sharp correction.

Whether it’s a pullback or a full-blown crash, the mood is shifting—from uncritical optimism to wary anticipation.

The question now is not whether AI will change the world, but whether markets have priced in too much, too soon.

We have been warned!

The AI bubble will pop – it’s just a matter of when and not if.

Go lock up your investments!

August 22, 2025September 12, 2025

U.S. zombie companies on the rise!

As BIG tech poaches top AI talent, these companies are stripped to the bone as the tech talent is being hollowed out!

In the race to dominate artificial intelligence, America’s tech giants are vacuuming up talent at an unprecedented pace.

But behind the headlines of billion-dollar acquisitions and flashy AI demos lies a quieter crisis. The creation of ‘zombie companies’ — startups left staggering and soulless after their brightest minds are poached by Big Tech.

These zombie firms aren’t dead, but they’re no longer truly alive either. They continue to operate, maintain websites, and pitch to investors, yet their core innovation engine has stalled. The problem isn’t just brain drain — it’s brain decapitation.

When a startup loses its founding engineers, lead researchers, or visionary product designers to the likes of Google, Meta, or Microsoft, what remains is often a shell with no clear path forward.

The allure is understandable. Big Tech offers salaries that dwarf startup equity, access to massive compute resources, and the prestige of working on frontier models. But the downstream effect is corrosive.

Startups, once the lifeblood of AI experimentation, are now struggling to retain talent long enough to reach product maturity. Some pivot to consultancy, others limp along with outsourced development, and many quietly fold — their IP absorbed, their vision diluted.

This phenomenon is particularly acute in the U.S., where venture capital encourages rapid scaling but rarely protects against talent attrition. The result is a growing class of companies that exist more for optics than output — kept alive by inertia, legacy funding, or the hope of acquisition.

They clutter the innovation landscape, making it harder for truly disruptive ideas to gain traction.

Ironically, Big Tech’s hunger for talent may be undermining the very ecosystem it depends on. By stripping startups of their creative lifeblood, it risks turning the AI sector into a monoculture. This culture is then dominated by a few players, with fewer voices and less diversity of thought.

The solution isn’t simple. It may require new funding models, stronger incentives for retention, or even regulatory scrutiny of talent acquisition practices.

But one thing is clear: if the U.S. wants to remain the global leader in AI, it must find a way to nurture its startups — not just harvest them.

Otherwise, the future of innovation may be haunted by the walking dead.

July 22, 2025September 12, 2025

Wall Street surges: S&P 500 breaks 6300 as tech optimism outpaces tariff tensions

The S&P 500 closed above 6,300 for the first time in history on Monday 21st July 2025, while the Nasdaq Composite notched yet another record, finishing at 20,974.17.

Investor enthusiasm for upcoming tech earnings has eclipsed broader concerns over looming global tariffs, fuelling a rally in major indexes.

Despite marginal losses in the Dow Jones Industrial Average, the tech-heavy Nasdaq rose 0.38% while the S&P 500 climbed 0.14%, buoyed by gains in heavyweights like Meta Platforms, Alphabet, and Amazon.

With over 60 S&P 500 companies having reported so far this earnings season, more than 85% have exceeded expectations, according to FactSet.

S&P 500 and Nasdaq Comp at new record highs 21st July 2025

redo the charts side by side and correct the S&P 500 value — S&P 500 and Nasdaq Comp at new record highs 21st July 2025

Alphabet shares advanced over 2% ahead of Wednesday’s results, and Tesla headlines the ‘Magnificent Seven’ group expected to drive the bulk of earnings growth this quarter. And not necessarily for the right reason.

Analysts reportedly expect the group to deliver 14% growth year-on-year, far outpacing the remaining S&P constituents’ average of 3.4%.

S&P 500

Despite tariff tensions simmering — with the U.S. setting a 1st August deadline for levy enforcement — investor sentiment remains bullish.

Bank of America estimates Q2 earnings are tracking a 5% annual increase, suggesting resilience amid geopolitical headwinds.

Strategists warn of potential volatility, as earnings surprises or policy shifts could spark swift market reactions.

Still, some analysts see space for further upside, projecting a potential S&P climb to 6,600 before any meaningful pullback.

As the tech titans prepare to report, all eyes are on whether optimism can keep the rally alive — or if tariffs will return to centre stage.

From FANG stocks, MAG 7 stocks to AI – the tech titans just keep giving.

But when will it overload?

June 10, 2025September 12, 2025

AI creates paradigm shift in computing – programming AI is like training a person

At London Tech Week, Nvidia CEO Jensen Huang made a striking statement: “The way you program an AI is like the way you program a person.” (Do we really program people or do we teach)?

This marks a fundamental shift in how we interact with artificial intelligence, moving away from traditional coding languages and towards natural human communication.

Historically, programming required specialised knowledge of languages like C++ or Python. Developers had to meticulously craft instructions for computers to follow.

Huang argues that AI has now evolved to understand and respond to human language, making programming more intuitive and accessible.

This transformation is largely driven by advancements in conversational AI models, such as ChatGPT, Gemini, and Copilot.

These systems allow users to issue commands in plain English – whether asking an AI to generate images, write a poem, or even create software code. Instead of writing complex algorithms, users can simply ask nicely, much like instructing a colleague or student.

Huang’s analogy extends beyond convenience. Just as people learn through feedback and iteration, AI models refine their responses based on user input.

If an AI-generated poem isn’t quite right, users can prompt it to improve, and it will think and adjust accordingly.

This iterative process mirrors human learning, where guidance and refinement lead to better outcomes.

The implications of this shift are profound. AI is no longer just a tool for experts – it is a great equalizer, enabling anyone to harness computing power without technical expertise.

As businesses integrate AI into their workflows, employees will need to adapt, treating AI as a collaborative partner rather than a mere machine.

This evolution in AI programming is not just about efficiency; it represents a new era where technology aligns more closely with human thought and interaction.

February 7, 2025September 12, 2025

Could DeepSeek deliver another shock to the stock market and to tech stocks in particular?

DeepSeek’s impact probably isn’t yet fully reflected in U.S. stocks

The ramifications of the Chinese startup DeepSeek, with its promise of delivering cheaper and more energy-efficient alternatives to harness artificial intelligence (AI), have yet to be fully reflected in U.S. equities.

If DeepSeek ends up delivering a less costly way forward – it will make it much easier and cheaper for smaller more typical companies to create AI ‘agents’ or AI opportunities for their businesses.

Under this scenario there will be ‘useful’ and meaningful benefits from DeepSeek that could bring huge earnings potential for a broader mix of companies beyond the current AI heavyweights through greater efficiencies and productivity from less-expensive AI solutions.

AI spending race

When DeepSeek’s chatbot launched earlier this month in the U.S., it shocked Wall Street, prompting a historic $600 billion one-day wipeout for AI chip developer Nvidia.

It also put huge sums being pledged for AI infrastructure by U.S. mega cap tech companies under a microscope. Rather than back down, the U.S. spending race has intensified.

Meta’s Chief Executive Mark Zuckerberg spoke a week ago of spending ‘hundreds of billions of dollars’ on AI infrastructure in the coming years, after pledging $60 billion to $65 billion on AI this year.
Alphabet announced AI investment for 2025, a bigger figure than Wall Street was anticipating.
Google forecast $75 billion in capital expenditures in 2025, a bigger figure than Wall Street was anticipating.
Microsoft reported its cloud and AI spending grew 95% in its fiscal second quarter to $22.6 billion.
Amazon has reported big AI investment too.

The spending frenzy on anything AI sends the market into a spin. How much more has to be spent before we see capital expenditures reduced or decrease is anyone’s guess right now – but current levels of AI expenditure are high, and returns will be expected.

“When is enough, enough?”

Or more to the point you might ask – when is ‘enough’ too much?

Fresh AI-spending commitments helped lift shares of Nvidia on while we saw a slump for Tesla shares in the week.

China this week saw the U.S. slap new 10% tariffs, while Canada and Mexico saw Trump threaten but delay 25% tariffs by 30 days. China retaliated in kind.

Catching up with the ‘Magnificent Seven’

Despite the high scrutiny on AI stocks, there is also much renewed focus from investors on other areas of the market.

There has been a bit of a rotation – while tech has been under pressure, defensive and rate-sensitive parts of the market have been gaining. This seems to be an emerging pattern.

But there should be reason for caution. For one thing, the growth rate of ‘Magnificent Seven’ earnings has been tailing off in recent quarters, especially since the group reached a 61% yearly rate in the fourth quarter of 2023 – the spend on AI investment has yet to fully appreciate the full return.

Forward analysts’ expectations have this percentage reportedly closer to 16% to 18% for the end of this year.

But that also would move the group closer to the roughly 12% to 13% yearly growth rate expected for the rest of the companies in the S&P 500 index, potentially making the high valuations of the ‘Magnificent Seven’ tougher to justify.

One of the most surprising things of the past couple of weeks, given the news around DeepSeek and shocks on the trade front, is the fact that stocks were still close to their all-time highs.

The market is pretty resilient right now, but tech stocks are sitting at a very high valuation – a pullback is due, even a correction (in my opinion).

The arrival of DeepSeek creates an alternative ‘cheaper’ AI option and that will unravel the status quo.

September 10, 2024September 12, 2025

Google’s advertising business goes on trial

The U.S. government is targeting the heart of Google’s vast wealth – its highly profitable monopolising advertising technology business

A trial scheduled to begin on Monday 9th September 2024 will scrutinise the Department of Justice’s (DoJ) claims that Alphabet, the parent company of Google, is unlawfully sustaining a monopoly in the marketplace.

In the previous year, the firm amassed over $200 billion (£152 billion) through the placement and sale of online advertisements.

Alphabet attributes its success to the ‘effectiveness’ of its business. Conversely, prosecutors contend that the company has leveraged its market control to stifle competition.

The legal action, launched by the Department of Justice (DoJ) and several states in 2023, charges Google with dominating the digital advertising market and employing its influence to obstruct innovation and competition.

Google asserts that it is simply one of numerous companies that arrange digital advertisement placements for consumers.

The corporation argues that the digital advertising industry is increasingly competitive, citing the growing advertising revenues of entities like Apple, Amazon, and TikTok as proof, as mentioned in a blog post responding to the DoJ’s lawsuit in 2023.

The contentions will be laid out before the U.S. District Judge who is expected to deliver a verdict.

This trial comes on the heels of a notable decision in a separate antitrust lawsuit against Google by the Justice Department last month. Judge Amit Mehta ruled that Google had illegally stifled competition in its online search services.

He reportedly stated that, “Google is a monopolist and has acted as such to maintain its monopoly.”

Alphabet one year chart

August 29, 2024September 12, 2025

Company says it can cut data centre energy use by 50% as AI boom places increased strain on power grids

Major technology corporations such as Microsoft, Alphabet, and Meta are channelling billions into data centre infrastructures to bolster generative AI, which is causing a spike in energy demand.

Sustainable Metal Cloud has announced that its immersion cooling technology is 28% less expensive to install compared to other liquid-based cooling methods and can cut energy use by up to 50%.

The surge in artificial intelligence has increased the need for more robust processors and the energy to cool data centres.

This presents an opportunity for Sustainable Metal Cloud, which runs ‘sustainable AI factories’ consisting of HyperCubes located in Singapore and Australia.

These HyperCubes house servers equipped with Nvidia processors immersed in a synthetic oil known as polyalphaolefin, which is more effective at dissipating heat than air. The company claims this technology can reduce energy consumption by as much as 50% when compared to the conventional air-cooling systems found in most data centres.

Additionally, the Singapore-based company states that its immersion cooling technology is more cost-effective to install by 28% than other liquid cooling options. The HyperCubes are modular and can be integrated into any data centre, utilising spaces that are currently unoccupied within existing facilities.

What is a Hypercube?

Structure: A hypercube topology connects nodes in a way that each node is connected to others in a manner similar to the geometric hypercube. For example, in a 3-dimensional hypercube (a cube), each node is connected to three other nodes.
Scalability: This structure allows for efficient scaling. As the number of dimensions increases, the number of nodes that can be connected grows exponentially.
Fault Tolerance: Hypercube networks are known for their robustness. If one connection fails, there are multiple alternative paths for data to travel, ensuring reliability.

Benefits in data centres

High Performance: The multiple pathways in a hypercube network reduce latency and increase data transfer speeds, which is crucial for big tech companies handling vast amounts of data.
Efficient Resource Utilisation: The topology allows for better load balancing and resource allocation, optimising the performance of data centres.
Flexibility: Hypercube networks can easily adapt to changes in the network, such as adding or removing nodes, without significant reconfiguration.
Big Tech Companies: Companies like Google, Amazon, and Microsoft likely use hypercube topologies in their data centres to ensure high performance and reliability.
High-Performance Computing (HPC): Hypercube networks are also used in supercomputers and other HPC environments where efficient data transfer is critical.

August 7, 2024September 12, 2025

Judge ruling says Google’s monopoly of online searches is illegal

Too much monopolistic power held by too few

A U.S. judge has ruled that Google illegally maintained a monopoly in online searches and related advertising. The lawsuit, brought by the Department of Justice, charged Google with controlling around 90% of the online search market.

It was reportedly noted by the judge that Google’s billions of dollars in investments to become the default search engine on smartphones and browsers could be anticompetitive.

The decision, issued on Monday 5th August 2024, could potentially change how tech giants operate.

It was reported that in his extensive 277-page decision, Judge Mehta remarked, “Google has acted as a monopolist and engaged in anticompetitive practices to maintain its monopoly.”

This represents a significant victory for federal antitrust enforcers who have pursued similar cases against other leading technology companies for illegal monopolistic behaviours.

Companies like Meta Platforms, which operate Facebook and WhatsApp, as well as companies like Amazon and Apple., have also faced lawsuits from federal regulators.

The judgment comes after a 10-week trial where it was argued that Google’s substantial payments to remain the primary search engine have impeded the competition’s ability to challenge effectively.

This is a seismic shift in the way search engines and advertising may operate in the future. Already with the advent of AI, search engines look and feel different.

Recently, OpenAI launched ‘SearchGPT’ – and Microsoft have named it a competitor in the world of search engines.

Times are changing.

August 6, 2024September 12, 2025

$1 trillion rout as Markets punishes tech stocks

The seven most valuable U.S. tech companies experienced a combined loss of $1 trillion in market value at the start of Monday’s trading session – 5th August 2024

The Nasdaq declined over 3% following its sharpest three-week drop in two years.

Nvidia’s shares fell approximately 6%, while Apple’s dropped more than 4%.

On Monday, as the U.S. markets commenced trading, the market capitalization of the largest tech companies plummeted by about $1 trillion, exacerbating a decline that pushed the Nasdaq into correction territory the previous week.

Markets go up and markets go down

In early trade Nvidia’s market cap decreased by over $300 billion, but it swiftly regained about half of that loss. The chipmaker’s shares ultimately closed down 6.4%, equating to a $168 billion loss. Apple and Amazon saw their valuations fall by $224 billion and $109 billion at market open. Apple’s market cap finished 4.8% lower, a $162 billion decrease. Amazon’s valuation fell by 4.1% at closing, a $72 billion reduction.

Including significant drops in Meta, Microsoft, Alphabet, and Tesla, the top seven tech giants saw a $995 billion loss in market value in the initial moments of trading, although they did recover somewhat as the day went on.

July 26, 2024September 12, 2025

OpenAI announces a search engine called SearchGPT

OpenAI on Thursday 25th July 2024 announced a prototype of its search engine, called SearchGPT, which aims to give users “fast and timely answers with clear and relevant sources.”

The company has announced plans to eventually incorporate the tool, presently in testing with a select user group, into its ChatGPT chatbot.

The introduction of ChatGPT could have significant implications for Google’s search engine dominance. Since ChatGPT’s debut in November 2022, there has been growing concern among Alphabet’s investors that OpenAI may capture a portion of Google’s market share by offering consumers innovative methods to obtain information on the internet.

Alphabet three month share price as of 25th July 2024

OpenAI’s ChatGPT was incorporated into Microsoft’s search engine Bing as Copilot and the companies have kept market dominance with this shrewd AI move. Google, on the other hand, has struggled to keep up in the AI race and may now be suffering the effects.

This announcement could have implications for Microsoft’s Copilot as well.

July 25, 2024September 12, 2025

U.S. stocks slip as Nasdaq tumbles for worst day since 2022 – Tesla and Alphabet fall

Stocks sold off Wednesday 24th July 2024, blighted by underwhelming reports from Tesla and Alphabet – leading the Nasdaq Composite and the S&P 500 to post their worst sessions since 2022.

The S&P 500 index dropped to closing at 5427, while the tech-heavy Nasdaq slid around 3.65% to end at 17342. The Dow Jones Industrial Average shed 504 points closing at 39853.

Nasdaq Comp one day chart 24th July 2024

Shares of Google parent company Alphabet fell 5% for their biggest one-day drop since 31st January, when they dropped 7.5%. Although Alphabet reported good numbers, YouTube advertising revenue came in below the consensus estimate causing share to dip.

Alphabet one day chart 24th July 2024

Tesla shares declined around 12% – their worst day since 2020 – on weaker-than-expected results and a 7% year-on-year drop in auto revenue.

Tesla one day chart 24th July 2024

June 19, 2024September 12, 2025

Nvidia passes Microsoft in market cap – should investors be concerned about the meteoric rise?

Nvidia, traditionally recognised within the gaming community for its graphics chips, has become the world’s most valuable publicly traded company.

On Tuesday 18th June 2024, Nvidia’s shares rose by 3.6%, increasing its market cap to $3.34 trillion and overtaking Microsoft, now valued at $3.32 trillion. Earlier in the month, Nvidia’s valuation reached $3 trillion for the first time, surpassing Apple.

Nvidia $3.34 trillion market cap

So far this year, Nvidia’s shares have surged over 170% and saw further gains after announcing first-quarter earnings in May 2024. Since the close of 2022, the stock has increased more than ninefold, paralleling the rise of generative artificial intelligence.

Apple’s shares dropped by 1.1% on Tuesday, resulting in a market value of $3.29 trillion for the tech giant.

Nvidia commands roughly 80% of the market share for AI chips in data centres, a sector that has expanded rapidly as companies like OpenAI, Microsoft, Alphabet, Amazon, and Meta have competed to acquire the necessary processors for constructing AI models and managing growing workloads.

In the latest quarter, Nvidia’s data centre business saw a 427% increase in revenue from the previous year, reaching $22.6 billion and comprising approximately 86% of the company’s total sales.

Established in 1991, Nvidia initially focused on hardware, selling gaming chips for running 3D games. The company has also ventured into cryptocurrency mining chips and cloud gaming services.

However, in the last two years, Nvidia’s stock has soared as investors recognised its pivotal role in the AI boom, a trend that continues to accelerate. This surge has increased the net worth of co-founder and CEO Jensen Huang to an estimated $117 billion, ranking him as the 11th richest individual globally, according to Forbes.

But is the rise too fast and is it time for a share price valuation adjustment in its meteoric rise, to bring it back down to Earth?

Nvidia share price one year chart 18th June 2024

April 26, 2024September 12, 2025

Alphabet shares climbed 15% after issuing first-ever dividend

Alphabet announced on Thursday 25th April 2024 that it is issuing its first-ever dividend of 20 cents per share and that its board has authorised a stock repurchase of up to $70 billion.

This announcement follows Meta’s board authorising its own inaugural dividend in February. As of 31st March 2024, Alphabet, the parent company of Google, had $108 billion in cash and marketable securities.

After the announcement, which coincided with the release of first-quarter earnings that surpassed expectations, shares surged by 15% in after-hours trading.

Alphabet trading chart 25th April 2024

March 25, 2024September 12, 2025

EU launches probe into Meta, Apple and Alphabet

On Monday, 25th March 2024, the European Union initiated its first investigation under the new Digital Markets Act, targeting Apple, Alphabet, and Meta for potential tech legislation breaches.

Statement

“Today, the Commission has opened non-compliance investigations under the Digital Markets Act (DMA) into Alphabet’s rules on steering in Google Play and self-preferencing on Google Search, Apple’s rules on steering in the App Store and the choice screen for Safari and Meta’s ‘pay or consent model” – the Commission said in a statement.

March 18, 2024September 12, 2025

Apple and Alphabet reportedly in Gemini AI talks

Apple playing AI catchup

Apple is reportedly engaged in negotiations to acquire a licence for Google’s Gemini, a generative AI platform, with the intention of integrating it into iPhones. These ongoing discussions may result in Gemini enhancing iPhone software with new features later this year.

The terms, branding, and implementation details have not been finalised. This potential partnership could significantly impact the AI capabilities of future iPhones.