We have deliberately waited a few days before commenting on “Liberation Day” and the fallout that would come from President Trump’s new tariffs regime.It will go down as just another historical period of heightened volatility, uncertainty, risk, and a whole manner of market turmoil. This is why we wanted to put what is happening right now into some context. (If that is possible, considering how volatile the period is and how erratic and how quick the president's manner can change.)US markets have seen this kind of violent move only three times since the 1950s. The S&P’s over 10 per cent drop in the final two sessions of the week following President Trump's "Liberation Day" tariff announcement has it in rare company – and not in a good way - October 1987 (Black Monday), November 2008 (Global Financial Crisis), March 2020 (COVID-19).So, why such a reaction?The market reaction reflects not the ‘shock’ but the scale and brevity of the tariffs. A 10% across-the-board tariff was broadly expected. There were some calculations as much as 15 to 20% judging by the net $1 trillion in and out of the federal government revenue. (This is the impact of DOGE and other government spending cuts coupled with the tariffs now in place that will offset the promised 0% personal income tax for those earning up to US$150,000)But what markets didn’t see coming was the country-specific layer. Take China as an example; the additional 34% reciprocal tariff on Chinese goods pushed the total to 54%. With other measures factored in, the effective burden could approach 65%.Then there were the tariffs that were tied to trade deficits, hitting Japan, South Korea and most emerging markets between the eyes (i.e. Vietnam).The EU saw a 20% rate, which was within expectations, while the UK, Australia, New Zealand and others landed at 10%. Canada and Mexico were spared, as was Russia, North Korea and Belarus, interestingly enough.Energy was excluded, which is unsurprising considering Trump’s goal of getting energy down, down and staying down. Pharmaceuticals and semiconductors were also carved out, however, this is more down to the probability of more targeted action like that of steel and aluminium.Now, what is different about this market shock and risk off trading is that it would send funds flowing to the US dollar, ratcheting it higher. But not this time. The dollar weakened against the euro. Theories as to why range from Europe’s lighter tariff load to euro-based investors pulling money out of the US. The same could be said of the Swiss Franc.All this leads to an average effective tariff rate of around 22%. That number will likely climb once product-specific tariffs on areas like pharmaceuticals and lumber are formalised. Some of this may be negotiated down, but not soon, and the possibility of tit-for-tat retaliation like China has now entered into could actually see it going higher still as the President looks to outdo country responses.The broader uncertainty this introduces to the US outlook is now at its highest since early 2020 and has the markets pricing in 110 basis points of Fed rate cuts this year – a near 5 cut call shows just how unprecedented this is.In fact, in no time in living memory has a developed economy lifted trade barriers this aggressively or abruptly. What has been implemented is textbook economics 101 supply-side shock.Input costs go up, finished goods get pricier, and the ripple effects hit margins and employment. Expect to see this in the next six months.Expect core PCE inflation to finish the year at 3.5% —nearly a full percentage point higher than the consensus forecast from just a week ago.Real GDP growth is forecast to slow to 0.1% on a quarter-on-quarter basis. That path may be volatile as Q1 could look worse due to soft consumption and strong imports, with a mechanical bounce in Q2.What has been lost in the chaos of last Thursday and Friday’s trade was the March Non-farm payrolls jobs print came in at 228,000, which was above consensus, the caveat being it is less so after downward revisions to prior months.Hospitality hiring was strong, likely helped by a weather rebound that won’t repeat. Government payrolls are holding steady for now, but cuts are coming. Layoffs in defence and aerospace (DOGE) are already underway, and tariffs will act as a brake on new hiring. Expect softer reports ahead.Unemployment ticked up slightly to 4.15%, reflecting a modest rise in participation. That’s still within range, giving the Fed cover to hold off on immediate action. But if job losses build pressure on the Fed to act, it will increase quickly.The consensus now is for the first rate cut of this cycle to start in May, triggered by softer April payrolls and earlier signs of deterioration in jobless claims and business sentiment.Zooming out from just a US-centric point of view, the macro standpoint is just as bad if not worse. The scale of tariffs adds pressure on industrial production, trade volumes and cross-border investment.That’s feeding into commodity markets, where the outlook has turned more cautious.Brent is expected to fall into the low US$60s as trade frictions and oversupply build. LNG looks weaker too, with soft Asian demand and less urgency in Europe to restock. Iron ore is more exposed to China, and the reciprocal tariffs put a vulnerability into the price due to the broader global slowdown and higher prices to the US.Looking at China specifically, infrastructure remains a key policy lever that would offset the possible loss of demand in aluminium, copper, and steel. Monetary indicators are beginning to turn, suggesting the start of a new easing cycle. It also suggests that policy remains inward-facing, and a focus on domestic stability would mean a metals-heavy growth path. Thus suggesting Australia could be the ‘lucky country’ once more and could escape the full burden of the global upheaval.In short, the global reaction isn’t just about tariffs. It’s about what happens when policy shocks collide with already-fragile global demand, and central banks are forced to navigate inflation that’s driven by politics, not just price cycles.This is the question for traders and investors alike over the coming period.
What Google announced
At Google Cloud Next 2026 in Las Vegas, Google made two distinct announcements. It confirmed general availability of Ironwood, its seventh-generation TPU, the first purpose-built for what Google calls the “agentic era” of inference at scale. It also previewed its eighth-generation architecture: two purpose-built chips, TPU 8t for large-scale training and TPU 8i for high-speed inference, both targeting TSMC 2nm manufacturing and expected to reach general availability later in 2026.
A TPU is Google’s custom alternative to NVIDIA’s graphics processing unit (GPU). Where a GPU is a general-purpose workhorse, a TPU is a specialist chip built from the ground up for AI calculations. Google has been building them since 2016. The eighth generation is its most ambitious split yet, and the first time the company has designed separate chips for each half of the AI lifecycle.
The TPU 8t training pod reportedly delivers nearly three times the compute of an equivalent Ironwood pod, with double the performance per watt. The TPU 8i inference chip is designed to serve millions of AI agents simultaneously for enterprise customers.
That last part carries a structural implication. On a recent earnings call, CEO Sundar Pichai indicated that as TPU demand grows from AI labs, capital markets firms and high-performance computing applications, Google would begin delivering TPUs to select customers in their own data centres. Google is no longer content to keep its silicon advantage internal.
Google is no longer just a TPU user. It is becoming a TPU vendor, and its biggest customers are already signed up.
Anthropic’s compute strategy
Anthropic, the AI company behind Claude, has confirmed a major infrastructure deal with Google covering access to up to one million Ironwood TPU chips. The commitment is worth tens of billions of dollars and was formally announced by both companies.
Understanding that deal requires understanding Anthropic’s compute strategy in full.
The multi-platform picture matters because coverage elsewhere has occasionally characterised this Google deal as Anthropic “switching” from NVIDIA. That framing understates the deliberate architecture of Anthropic’s compute strategy. The Google deal is an expansion, not a departure from either AWS or NVIDIA.
Why this matters beyond the benchmark
On a per-chip basis, the current generation comparison is closer than the headlines suggest. Ironwood, now in general availability, delivers approximately 4.6 petaflops of FP8 computing power. NVIDIA’s Blackwell B200 delivers roughly 4.5 petaflops at FP16, although cross-precision comparisons require care, as the two figures are not measured on an identical scale.
But benchmark comparisons miss the bigger story.
At pod scale, where these chips are actually deployed, the gap widens. An Ironwood superpod of 9,216 chips delivers 42.5 exaflops. The eighth-generation TPU 8t pod, at 9,600 chips, targets 121 exaflops at FP4 precision. Google also claims near-linear scaling to one million chips inside a single logical cluster. For hyperscalers running hundreds of thousands of chips simultaneously, pod-level economics matter far more than per-chip benchmarks.
The NVIDIA position
NVIDIA currently controls an estimated 81% of the AI data centre chip market, according to IDC. That is an extraordinary concentration of market power, and the near-term demand picture has remained resilient.
Recent analyst expectations have pointed to strong NVIDIA earnings growth, supported by elevated demand for AI infrastructure and broad adoption of the Blackwell platform. NVIDIA has itself guided for a combined US$1 trillion in Blackwell and upcoming Vera Rubin orders across 2026 and 2027.
AMD is developing rack-scale server systems and has gained meaningful ground. Estimates from analysts, including IDC, suggest AMD may now hold approximately 10% of the AI accelerator market, up from low single digits two years ago. Amazon and Google continue to expand custom chip businesses. The combined chip operations at Amazon alone, covering Trainium, Graviton and Nitro, have crossed a US$20 billion annual revenue run rate, growing at triple-digit percentages year over year, with nearly 40% sequential growth in Q1 2026.
The bull case for NVIDIA remains clear: demand has stayed strong, and NVIDIA’s ecosystem remains deeply embedded across the AI compute stack.
The longer-term question is less about near-term earnings and more about pricing power in the next upgrade cycle. Every reporting period in which Google, Amazon and Microsoft gain confidence in their own silicon is another data point in that debate. The incentive structure is powerful: these companies have every reason to reduce dependency on a single supplier, and the capital to act on it.
Stocks and sectors to watch
For NVIDIA, the near-term earnings story and the longer-term competitive story are pulling in different directions. Strong results may validate the current cycle. But the structural dynamic, where major customers build their own silicon, is unlikely to reverse.
For Alphabet, the Ironwood general availability and eighth-generation preview represent a potential monetisation opportunity well beyond advertising. Google Cloud grew 63% year over year in Q1 2026, among the fastest growth rates of any major hyperscaler. TPU-as-a-service, with confirmed anchor customers including Anthropic and Meta, could extend that runway materially if enterprise inference workloads continue migrating to Google infrastructure.
The less obvious plays are in the supply chain. TPU 8t and 8i are both targeting TSMC 2nm manufacturing, with Broadcom designing the training chip and MediaTek the inference chip. TSMC may remain a critical enabler regardless of which chip architecture gains share in each cycle, as may advanced packaging suppliers, liquid cooling companies and data centre real estate investment trusts (REITs).
Power infrastructure, liquid cooling suppliers and data centre REITs may also be exposed to sustained capital expenditure growth. Combined hyperscaler capital expenditure from the four major cloud providers is tracking toward US$700 billion or more in 2026, nearly double the US$388 billion spent in 2025. That scale of investment, sustained over multiple years, represents a different kind of macro signal.
Supply chain plays: If neither NVIDIA nor Google “wins” the chip war outright, infrastructure may still benefit. TSMC already manufactures both Ironwood and the upcoming eighth-generation chips. Advanced packaging suppliers, liquid cooling companies and data centre REITs may benefit regardless of which chip architecture gains share in each cycle.
Where the risks sit
Higher AI infrastructure spending does not automatically translate into stock gains. Several factors complicate a straight line from “chip war” to “buy everything”.
What investors might take away
The AI chip war is not a story of one winner and one loser. It is a story of a market that is too large and too strategically important for any single company to own indefinitely.
NVIDIA built its lead through genuine technical excellence and a decade of software investment. That lead is real, and near-term earnings are likely to continue reflecting it.
But the challengers are no longer startups with benchmark slides. They are trillion-dollar companies with their own silicon, their own cloud infrastructure and every incentive to reduce their dependency on a single supplier, along with the capital expenditure commitments to show they are following through.
One way to frame the longer-term question is this: demand for AI compute may not be the primary variable for investors to focus on. Who captures the margin from that demand, and at what valuation multiple, may matter just as much. Those are questions each investor may need to weigh against their own risk profile and objectives.
Scenario Disclaimer: The "Next 30 days" and "Next 3 months" scenarios are illustrative "what-if" models for stress-testing a market thesis and identifying potential catalysts. They do not constitute a house view, forecast, guarantee, or prediction of future market movement. Any Brent price targets, Fed policy references, or other market benchmarks are hypothetical only. Real-world conditions are subject to volatility and unforeseen shifts.









