The $500 Trillion AI Bet Depends on Energy, Infrastructure, and Policy, Not Just Code

The $500 Trillion AI Bet Depends on Energy, Infrastructure, and Policy, Not Just Code

Jensen Huang’s recent remarks on AI’s economic trajectory are as bold as they are inevitable. “There’s a belief that the world’s GDP is somehow limited at a hundred trillion dollars,” he said. “AI is going to cause that hundred trillion dollars to become two hundred, three hundred, five hundred trillion… Everybody’s jobs will change.”

The pitch is seductive, and on the micro level, largely correct. AI will not simply replace jobs; it will strip away friction. Workers will spend less time wrangling spreadsheets or typing prompts and more time orchestrating, deciding, and creating. Productivity will surge. Those who fail to integrate AI will lose to those who do.

But macroeconomics rarely bends to technological optimism. The real question is not whether AI expands the economic pie. It is how that expansion prices out, and who captures the gains.

Pressure-testing Huang’s $500 trillion vision reveals two sharply different futures. One  to structural deflation and abundance. The other leads to inflationary distortion.

Scenario A: The Nominal Bubble

If the $500 trillion figure is driven more by financial engineering than physical output, the result could be an inflationary shock.

A booming AI sector would generate enormous paper wealth across companies such as NVIDIA, Microsoft, and OpenAI. Investors and founders would recycle those gains into real-world assets: housing, energy, food, and commodities. That is classic demand-pull inflation, amplified by unprecedented .

At the same time, AI’s digital promise collides with physical bottlenecks. Training models requires vast amounts of copper, semiconductors, data centers, and electricity. Competition for those constrained resources pushes up costs across the broader economy while non-AI sectors struggle to keep pace.

In this scenario, the $500 trillion economy is not real growth. It is a valuation bubble chasing finite real-world supply.

Scenario B: The Deflationary Engine

The counterargument is that AI could create genuine GDP expansion while driving structural deflation.

Jensen Huang, Founder and CEO of Nvidia, Source: Wikipedia

GDP is ultimately price multiplied by quantity. If AI removes the constraints of human labor and intelligence, the quantity of goods and services could scale dramatically even as prices fall.

When AI automates coding, legal work, diagnostics, research, and eventually physical production through robotics and automated manufacturing, the marginal cost of creating products and services collapses. Software, logistics, energy optimization, and even manufacturing become radically cheaper.

If output expands severalfold while costs decline, the economy grows in real terms. Living costs fall, purchasing power rises, and abundance—not inflation—defines the outcome.

This is the future Huang is implicitly betting on. And mathematically, it is possible.

The Dangerous Transition Gap

The real risk lies between those two scenarios.

Markets may price in AI-driven abundance long before the physical infrastructure exists to support it. Building advanced energy grids, semiconductor fabs, robotics supply chains, and transmission networks could take 10 to 15 years.

That creates a dangerous mismatch. Capital floods into AI today, asset prices surge, and resource competition intensifies before supply-side abundance arrives. Energy, housing, metals, and essential goods could all become more expensive during the transition.

In effect, the path to abundance may first pass through inflation.

Central banks would face an impossible balancing act between suppressing inflation and supporting growth. Workers in disrupted industries could face displacement before new AI-augmented roles scale fast enough to absorb them. Social and political friction could undermine the productivity boom AI promises.

Abundance is not automatic. It has to be engineered.

The Real Question

Huang is probably right that GDP is not capped at $100 trillion. He is also right that AI will fundamentally change how people work.

But whether the world reaches $500 trillion through abundance or distortion will depend less on algorithms and more on institutions.

The outcome will hinge on energy policy, industrial capacity, monetary discipline, and labor adaptation. Technology creates productive capacity. Governments, central banks, and markets determine whether that capacity translates into stability.

AI will reshape the global economy. The real question is whether society can manage the transition as effectively as it trains the models powering it.

 

Source: https://www.financemagnates.com/institutional-forex/the-500-trillion-ai-bet-depends-on-energy-infrastructure-and-policy-not-just-code/

j j j

The tech record vs crypto crash: Why the liquidity roadmap just split in two

The tech record vs crypto crash: Why the liquidity roadmap just split in two

The global financial landscape is currently presenting a striking paradox as traditional equities power to fresh records while digital assets face heavy liquidation. This divergence highlights how differently various asset classes absorb macroeconomic shocks and structural shifts.

While a tentative ceasefire agreement in the Middle East and a massive wave of corporate investments in artificial intelligence breathe new life into global stock indices, the cryptocurrency market is grappling with aggressive capital flight. This situation reveals a distinct decoupling of sentiment: traditional markets celebrate a reduction in systemic risk, while digital assets remain trapped in a feedback loop of institutional outflows and forced derivatives liquidations.

In traditional equity markets, investors are celebrating a confluence of positive geopolitical and macroeconomic developments. The primary catalyst for this optimism is a draft 60-day ceasefire agreement between United States and Iranian negotiators. This development has significantly lowered the geopolitical risk premium that previously weighed on global commerce.

A direct result of this de-escalation is the retreatment of crude oil, with Brent crude stabilising below US$100 per barrel, specifically around US$93. This drop offers immediate relief to global inflation expectations and energy-strapped consumer supply chains, which in turn provides central banks with more breathing room.

Concurrently, a mixed macroeconomic picture in the United States supports the soft-landing narrative. The April Personal Consumption Expenditures price index registered a headline increase of 0.4 per cent and a core increase of 0.2 per cent, coming in slightly cooler than consensus expectations. Additionally, the United States 1st-quarter gross domestic product was revised lower to 1.6 per cent annualised, down from the initial two per cent prints, confirming an economic cooling that could deter overly aggressive monetary tightening.

This stabilisation in inflation and geopolitics provided the perfect launchpad for an explosive artificial intelligence and technology earnings rally, driving major indices to record closing levels. The S&P 500 advanced 0.58 per cent to close at 7,563.63, propelled by artificial-intelligence infrastructure spending and lower oil prices. The Nasdaq Composite led the gains with a 0.91 per cent surge to 26,917.47, fueled by technology leadership and stellar corporate performances. Meanwhile, the Dow Jones Industrial Average eked out a late record during a more subdued session, rising 0.05 per cent to close at 50,668.97.

Individual corporate movers illustrate the sheer scale of this technology-driven euphoria. In software, Snowflake surged 36 per cent on blowout guidance and a massive US$6,000,000,000 compute deal with Amazon Web Services, reigniting interest across the sector. Consequently, Palantir climbed eight per cent, and ServiceNow advanced 6.5 per cent. In hardware, Dell Technologies surged roughly 40 per cent in extended trading after smashing revenue estimates by 88 per cent, driven by an insatiable demand for artificial intelligence servers. Private markets mirrored this enthusiasm, as Anthropic raised US$65,000,000,000 at a staggering US$965,000,000,000 valuation, surpassing its chief rival OpenAI for the very first time. Beyond technology,

Microsoft rose 3.5 per cent following reports that it will launch a next-generation artificial intelligence coding model, while Eli Lilly rallied 4.0 per cent after CVS Health restored insurance coverage for its weight-loss drug, Zepbound, and added its new obesity pill, Foundayo. Asian markets advanced broadly on these positive cues, with Japan’s Topix up 0.5 per cent and Australia’s S&P/ASX 200 climbing 0.8 per cent in early trading, while BYD Company unveiled China’s first automotive-grade 4-nanometer self-driving chip to boost high-margin electric vehicle models.

In stark contrast to this equity market euphoria, the cryptocurrency market has entered a sharp correction, failing to benefit from the broader risk-on environment. Bitcoin fell 0.89 per cent over 24 hours to US$73,709.75, underperforming the broader financial trends and showing a strong 61 per cent correlation with the S&P 500 during the initial phases of the move. This indicates that digital assets are reacting strongly to shifts in institutional capital rather than to internal crypto factors.

The primary driver behind this downward price pressure is a massive wave of institutional selling through spot exchange-traded funds. This selling coincided with the eighth consecutive day of net outflows from United States spot Bitcoin vehicles, totaling US$733,000,000 on a single day. BlackRock’s IBIT alone experienced a significant US$527,800,000 redemption, reversing the strong institutional inflow narrative that had previously supported the asset class.

This institutional withdrawal triggered secondary pain points across the cryptocurrency derivatives markets, turning a standard correction into a cascading sell-off. As prices slipped, overleveraged long positions were forced to close. Bitcoin liquidations surged 71.65 per cent to US$277,780,000 within 24 hours, with long positions accounting for an overwhelming 92 per cent of that total. This created a destructive feedback loop of forced selling into weak order books, which accelerated the decline past key moving averages.

If Bitcoin manages to defend its support at US$73,000, near the 78.6 per cent Fibonacci retracement, it may enter a period of consolidation and attempt to reclaim US$74,200. A break below the recent swing low of US$72,500 would risk a deeper retest of the psychological US$70,000 boundary. For bullish momentum to fully return, buyers must reclaim the previous swing high of $75,278.

Ethereum mirrored this bearish sentiment almost perfectly, dropping 0.59 per cent over 24 hours to US$2,010.32. Just like Bitcoin, Ethereum was heavily impacted by institutional capital flight, with United States spot Ether exchange-traded funds recording US$67,000,000 in net outflows. Ethereum faced unique structural pressure from its derivatives market. Even as the price declined, open interest in Ether futures hit a record high of 16,390,000 ETH, signalling that aggressive traders were adding leveraged short positions.

This aggressive shorting fueled a painful cascade of $241,000,000 in long liquidations, breaking the price below the psychological $2,000 support level. Ethereum has now entered a critical demand zone between the 78.6 per cent Fibonacci retracement at $2,064 and the March swing low near $1,900. The 4-hour relative strength index stands at 30.94, suggesting heavily oversold conditions that could support a short-term relief bounce toward $2,070, but the overall structure remains fragile. Traders are closely watching the upcoming $8,000,000,000 Deribit options expiry for further volatility.

While equity benchmarks bask in the glow of lower oil prices and breakthroughs in artificial intelligence, beneath the surface, professional investors are quietly preparing for potential turbulence.

We are not “max pain” yet.

Source:
 
j j j

ETF outflows and macro fear put Bitcoin and Ethereum under pressure

ETF outflows and macro fear put Bitcoin and Ethereum under pressure

Bitcoin trades at US$74,326.85 after a 2.02 per cent decline over 24 hours, underperforming a slightly softer broader market. This move reflects a clear shift in institutional sentiment rather than retail panic. A single dark pool transaction involving 29.2 million shares of BlackRock’s iShares Bitcoin Trust, valued at US$1.289 billion, triggered the initial selloff on 26 May. That block trade signalled large-scale de-risking by sophisticated players who now face mounting macro uncertainty. The consequence became visible the following day when US spot Bitcoin ETFs recorded US$333.6 million in net outflows, extending the withdrawal streak to seven consecutive sessions. When the most reliable source of demand reverses direction, price discovery inevitably follows a lower path.

The correlation between Bitcoin and the Nasdaq-100 ETF, currently running at 65 per cent, confirms that crypto no longer trades in isolation. Macro drivers now dominate short-term price action. Renewed tensions between the United States and Iran pushed the Crypto Fear and Greed Index down to 34, firmly in fear territory. That sentiment shift accelerated a cascade of leveraged long liquidations totalling US$142.24 million within 24 hours, with long positions accounting for 92 per cent of that figure. Markets hate uncertainty, and the current environment offers plenty. Traders positioned for continuation now face the reality that institutional capital moves first and asks questions later.

Technically, Bitcoin broke below an ascending channel and now tests the 38.2 per cent Fibonacci retracement level near US$74,500. The seven-day RSI reading of 27.42 suggests oversold conditions, which often precede a short-term bounce. Oversold does not mean reversed. The critical support cluster ranges from US$74,000 to US$74,500. A decisive break below that zone opens the path toward US$73,000. A reclaim of the pivot point at US$74,309 would signal early stabilisation and could fuel a rebound attempt toward US$76,500. Traders should watch this range closely, but they must also recognise that technical levels matter less when institutional flows dominate the tape.

Ethereum faces even steeper headwinds, down 2.72 per cent to US$2,019.19 over the same period. The primary driver remains persistent capital flight from US spot Ethereum ETFs, which have now seen 11 consecutive days of net outflows totalling over US$506 million. That streak represents the longest withdrawal period in 2026 and signals fading institutional conviction. When regulated products lose their appeal, the market loses its most stable buyer. Ethereum now trades without that structural support, leaving it more vulnerable to spot market selling and broader risk-off moves. The Ethereum Foundation needs an overhaul – but that is another story for another day.

The situation worsens when we examine on-chain activity. Ethereum’s network utility has collapsed, with median transfer size and fees down 80 to 90 per cent from their 90-day baseline. That decline indicates a lack of organic, price-supportive demand. While developers debate roadmap priorities, users vote with their wallets, and right now, they are not paying to use the network. This creates a double headwind for ETH. It moves like a risk asset in a fearful macro environment, even as its own ecosystem fails to generate a bullish counter-narrative. The technical structure reflects this weakness. ETH trades below all key moving averages, with the 23.6 per cent Fibonacci retracement level at US$2,074 now acting as near-term resistance. A daily close above that level would suggest downside exhaustion, but a break below the recent US$2,014 low could accelerate selling toward the US$1,800 to US$1,900 support zone.

Global equity markets present a confusing backdrop. US indices notched fresh record closes recently, with the Dow Jones Industrial Average rising 182.60 points to 50,644.28, the S&P 500 edging up 1.24 points to 7,520.36, and the Nasdaq Composite gaining 18.55 points to 26,674.73. AI and tech momentum remains strong, as evidenced by Snowflake shares rising as much as 35 per cent in after-hours trading following a revenue beat and a US$6 billion multi-year commitment with AWS. Crypto diverges from this strength. That divergence matters. It suggests that while traditional markets celebrate corporate earnings and AI narratives, digital assets grapple with structural challenges of their own. Brent Crude oil tumbling to a five-week low near US$94.29 a barrel reflects shifting geopolitical expectations, but it has not provided the risk-on tailwind crypto traders hoped for.

Federal Reserve policy remains the ultimate macro wildcard. Governors Lisa Cook and Neel Kashkari recently signalled their readiness to raise rates if sticky inflation persists, helping keep bond yields stable. That hawkish tone weighs on all risk assets, but crypto feels the pressure more acutely due to its higher beta profile. The upcoming US PCE inflation report due on 30 May will serve as the next major catalyst. If the data shows cooling price pressures, markets could stage a relief rally. If inflation proves persistent, the Fed’s hands remain tied, and risk assets likely face further pressure. Traders should position accordingly, but they must also recognise that macro data only sets the stage. Institutional flows write the script.

We built these networks to operate outside traditional financial systems, yet price action now hinges on ETF flows, Fed policy, and institutional block trades. That reality does not invalidate decentralisation, but it does demand honesty about where we stand. Institutional participation brings liquidity and legitimacy, but it also imports traditional market dynamics, including correlation, leverage, and sentiment cycles. The current selloff shows what happens when those forces align against price. It also highlights the importance of organic, on-chain demand. When fees and transfer activity collapse, as we see on Ethereum, the market loses its fundamental anchor.

Beyond the charts, the deeper question remains whether institutional flows will stabilise or continue to dominate price discovery. Watch for a reversal in daily ETF flow data. That signal, more than any technical level, will indicate whether institutional sentiment has turned. Until then, expect volatility, respect the macro backdrop, and remember that markets reward those who prepare for multiple outcomes rather than betting on a single narrative.

Source:
 
j j j