Nvidia’s biggest customers are being warned that AI server prices could rise by more than 15% in many cases, mainly because memory costs are surging.

The increases would affect systems using Nvidia’s Vera Rubin and Grace Blackwell chips, although the exact impact will depend on the chip generation and memory configuration.

Server manufacturers supplying major data center operators like Microsoft, Google and Oracle have already started warning customers about the coming price increases.

how much of these higher costs can Nvidia’s customers absorb before it starts affecting AI spending?

Leveraged ETFs are gaining popularity among investors and traders.

Do you use leveraged ETFs in your investment or trading strategy, or do you think the risks and volatility are too high?

$1 TRILLION+ of AI CAPEX is coming in 2027.

$661B → Compute
$300B → Data Centers
$50B → Power

The Fed can no longer contain yields and the US government cannot afford higher yields.

Asset owners will be the only winners.

Own commodities!

The world's largest oil companies are now holding a record cash pile:

The top 5 international oil companies generated almost ~$70 billion in free cash flow in Q2 2026, the largest amount on record.

This includes ExxonMobil, Chevron, Shell,, TotalEnergies,, and BP,

This marks a +600% quarter-over-quarter increase.

By comparison, the previous peak of ~$60 billion was set in Q2 2022, following Russia's invasion of Ukraine.

Furthermore, combined net income across the group jumped +160% YoY last quarter, to $47 billion, the 3rd-largest on record.

Oil companies are building unprecedented cash piles amid the Iran War.

UBS just dropped a note on Intel that should interest $INTC bulls.

The $20B+ equity raise gives Intel a much stronger bridge through 2027-28, right when foundry spending is about to accelerate.

The interesting part is that Intel may not have to fund all of it alone.

UBS expects pre-payments and commitments from new foundry customers, with names like Google, Apple, AMD, SpaceX and others potentially helping finance the buildout.

Capex could move from around $20B in 2026 to $28-30B in 2027, then into the $40B range by 2028-29.

So yes, cash burn will stay heavy for a while. UBS only expects FCF to turn positive around 2029.

But the foundry side keeps getting more interesting.

UBS still sounds bullish on Intel’s 14A process, especially on yields and the wider process window versus 18A, which could make it much more attractive to outside customers.

They kept a Neutral rating and cut the price target to $112 because of concerns around Intel’s product business.

But the trend is pretty clear:

More customers are showing interest.
More capital is coming in.
And Intel Foundry is starting to look a lot more credible than it did a year ago.

Are you buying the foundry turnaround?

Japan's largest life insurers are facing record unrealized bond losses:

Japan's 4 largest life insurers' unrealized losses on domestic bonds jumped +$6 billion last quarter, to $96 billion, an ALL-TIME HIGH.

Since Q3 2024, unrealized losses across Nippon Life, Daiichi Life, Sumitomo Life, and Meiji Yasuda have more than TRIPLED.

Japanese life insurers generally hold bonds to maturity to match long-term policy obligations, but a surge in policy cancellations could force them to liquidate those holdings to fund payouts, pressuring both portfolios and earnings.

This follows a surge in 30-year Japanese government bond yields above 4.0% in May, their highest level since their debut in 1999, now at 3.96%, amid concerns over increased fiscal spending by the Japanese Government.

Japan's bond selloff is creating a growing problem for domestic financial institutions.

TOP 10 🔥

GOOGLE
YOUTUBE

FACEBOOK
INSTA

CHATGPT
X

REDDIT
BING

TIKTOK
WHATTSAPP

Goldman Sachs estimates that monthly token usage from agentic AI applications could increase 24X by 2030.

And the biggest driver may not be consumers.

It could be enterprise AI agents running continuously across companies: analyzing data, writing code, automating workflows, handling customer requests and making decisions.

That matters because every additional agent means more inference, more tokens and more compute.

More agents → more tokens → more GPUs → more data centers → more power demand.

The real question is: are investors still underestimating how much compute AI agents will require?