Turkey’s geography, infrastructure, and regional influence position it to reshape Europe’s energy security through a new overland corridor linking four major energy basins.
For decades, Turkey has pitched itself as an energy bridge between
East and West, North and South. If Turkey can finally deliver to the
world a solution to overcome its reliance on the Strait of Hormuz, the
economic and strategic prize will be enormous.
The Four Seas Initiative Could Redraw Global Energy Routes
The Four Seas Initiative identifies
Turkey as the keystone in the infrastructural response to the Strait of
Hormuz crisis. The idea is simple. The four seas: the Persian Gulf, the
Caspian Sea, the Mediterranean, and the Black Sea are among the most
important energy geographies in the world. Yet they remain connected
largely through bilateral deals and infrastructure shaped by old
political divisions—not to mention being vulnerable to war and blockade.
The Four Seas Initiative proposes an overland energy and infrastructure
corridor linking these four basins through Syria and Turkey, carrying
Gulf, Iraqi, Caspian, and eastern Mediterranean energy toward lucrative
European markets.
For Turkey, this marks the arrival of
the role Ankara has long sought: not merely to be a country through
which energy passes, but to become the operator, rule-setter and
commercial center of a continental redistribution system.
This agenda-setting role is due to the
absolute scale of the project. At full operational capacity, the Four
Seas corridor is projected to move an estimated 3 million to 4 million
barrels of oil per day and 40 billion to 50 billion cubic meters of gas
per year toward Mediterranean and European markets. As a network, it
will compete in scale with Nord Stream. It would put the Syria–Turkey
corridor in the first rank of global energy routes, combining Gulf oil,
Iraqi exports, Caspian gas and eastern Mediterranean supply into a
single overland system....
China's“deflation-is-over” narrative is getting louder, but the foundations are still shaky.
Consumer prices rose 1.2% year-on-year in May, while producer prices
jumped 3.9%, lifted by higher costs for energy, semiconductors and
metals. To many economists, this is the clearest sign yet that the 2025
deflation scare is giving way to reflation.
But Japan's long struggle shows how stubborn deflationary psychology
can be. And it's far from clear that Beijing is delivering the
structural reforms needed to ensure China's weak‐price era is truly
ending.
Two reforms stand out - and neither is being pursued with urgency.
First, resolving the deep housing crisis, which increasingly resembles
Japan's 1990s bad‐loan spiral. Second, building a real social safety net
so 1.4 billion citizens feel confident enough to spend rather than
hoard savings.
These priorities are tightly linked. With roughly 70% of household
wealth tied to property, stabilizing the real‐estate market across
China's 70 largest cities is essential for reviving consumption and
sustaining 4.5%- 5% growth.
But the longer Xi's government acknowledges these pressures while
avoiding decisive action, the more a deflationary mindset takes hold -
and the harder it becomes to shake.
Japan is the cautionary tale. Even as the Bank of Japan prepares to
lift rates to 1% next week - the farthest from zero in more than three
decades - deflationary undercurrents still run through the economy.
On paper, Japan looks like it has finally escaped its low‐price trap.
The BOJ expects inflation to reach 2.8% this year, suggesting reflation
is taking hold. But beneath the headline, real wages remain negative,
with pay packets consistently trailing price gains and domestic demand
weakening as a result.
The result is a slow‐burn form of stagflation, and Tokyo has yet to
deliver the structural reforms needed to close the gap between rising
prices and stagnant household incomes.
“For the Japanese economy to fully break free from its long-standing
deflationary mindset,” says Toshihiro Nagahama, economist at the
Dai-ichi Life Research Institute,“it's imperative for the government and
the central bank to align, articulate their risk assessments, maintain
honest and transparent dialogue with financial markets, and resolutely
execute bold, long-term growth investments.”....
From the truly astounding World Politics substack (don't let the name of the blog fool you), March 20, 2026:
Kautilya made Machiavelli look naive
In the closing decades of the fourth century BC, in the city of
Pataliputra on the Ganges plain, a man named Kautilya composed a text on
statecraft, economics, and political strategy whose ruthlessness,
comprehensiveness, and analytical intelligence have no parallel in the
political literature of the ancient world.
The Arthashastra
(the Science of Statecraft) is a treatise organised into 15 books –
with subjects ranging from the organisation of the king’s daily schedule
and the architecture of the royal palace to the administration of
agriculture, mining, and commerce; the management of the treasury and
the army; the conduct of diplomacy and espionage; the waging of war; and
techniques for eliminating rivals.
Niccolò Machiavelli’s Prince
is the Western political tradition’s most powerful exposition of
strategic realism; it amounts to about 70 pages. Kautilya wrote several
hundred, addressed them to a far broader range of political problems
with greater analytical precision, and did so eighteen centuries before
Machiavelli was born. The consistent verdict of scholars who have read
both carefully is that, for all his genius, Machiavelli worked in a
shallower analytical tradition and addressed a narrower set of problems
than the Indian whose work he never knew existed....
Nvidia (NVDA.O) and South Korea's SK Group on Friday unveiled a more than $500 billion AI initiative spanning large-scale AI data centers and next-generation memory, Nvidia said.
The initiative includes a long-term partnership with SK Hynix (000660.KS) to secure next-generation memory supply for Nvidia and jointly develop high-bandwidth memory for AI training, AI agents and physical AI applications....
Waymo is another of the ulti-multi-decacorns. In February they announced the completion of a $16 billion Series D financing round at a $126 billion post-money valuation.
From Bloomberg, July 24:
Alphabet Inc.’s Waymo is exploring options to exit its robotaxi partnership with Uber Technologies Inc., the latest relationship twist between two companies that have functioned as both rivals and partners.
Uber
currently offers rides in autonomous Waymo vehicles on its platform
exclusively in two US cities — Austin and Atlanta — after ending
a more limited partnership in Phoenix last month. An Uber spokesperson
said that Waymo has given notice that it plans to launch service through
its own app in those cities in January 2028 “alongside their existing
deployment with Uber.” This “would end Waymo’s exclusivity in Austin and
Atlanta and allow us to launch with other AV providers in those cities,
which we will be prepared to do,” the spokesperson added.
The
current fleet of Waymo vehicles will remain on Uber’s platform through
at least May 2028, the duration of the current contract, Uber said. The
Financial Times Waymo explores split with Uber as robotaxi tensions deepen earlier that Waymo was exploring options for exiting the partnership.
“We
believe in a vibrant and collaborative AV ecosystem that champions
innovation and provides riders with a choice in how they experience this
technology,” said a Waymo spokesperson. “This is essential to the
industry’s future and to our vision of making the Waymo app and the
safety of our technology available to riders everywhere.”
Shares
of Uber slid 4.3%, closing Friday at $65.94 in New York, the lowest
level in more than a year. Alphabet’s stock was up less than 1%.
The
rift is a major setback for Uber, which has been developing
partnerships with Waymo and fleet managers, and investing in other
robotaxi companies in the hopes that it can one day be the go-to
aggregator for driverless and human-operated rides. Waymo, the leading
robotaxi provider in the US, also competes with Uber in key rideshare
markets such as San Francisco and Los Angeles with its consumer app.
The
absence of new developments from Uber and Waymo’s multiyear partnership
has helped fuel anxiety about their relationship for months. Since
launching the Atlanta service last June, Waymo hasn’t announced new
cities where its vehicles will be available on the Uber app. Instead,
the Alphabet unit has forged ahead with the standalone Waymo app and has
launched in six more cities outside San Francisco and Los Angeles.
With
almost every new Waymo announcement without Uber, Uber’s stock has
taken a hit on fears that Waymo’s growth will eventually erode the
ride-hail company’s business, which reported an annual profit for the
first time only in 2023. Even as Uber has announced partnerships with
other driverless car companies on planned service in the US, Middle East
and Europe, Wall Street has remained unconvinced. The stock has fallen
almost 20% so far this year....
The investor closest to the AI frontier is betting against the ambitions of its biggest companies
In November 2025, Anthropic, known to its employees
as Ant, trained a model called Claude Opus 4.5 on warehouses of
liquid-cooled processors, and on the day the worker ants released it,
machines became agentic. That is to say, they no longer needed
handholding. Before November, the machines had felt like
eight-year-olds: eager, literal-minded, completing your sentences,
getting it nearly right but mostly wrong, the way eight-year-olds do.
Overnight they turned 28.
If you wrote code, you could now tell them, in plain English, what
you wanted done, and an agent went off and did it. You didn’t have to
say where to look, or how to work the problem, or what to try first; you
described the finished thing and there it was. It didn’t argue, it
didn’t sigh, it didn’t ask whether it could circle back on Monday. It
didn’t get tired, or hungry, or bored, or married, or sick of you. And
it wasn’t one agent; it was as many as you wanted. You could spin up
five over breakfast, leave them running while you commuted, check in
from the train, kill the ones you didn’t like, start three more from the
platform, and by the time you reached your desk you had a small private
workforce under your command. They worked for you, or so it seemed.
By January, Nat Friedman, who co-leads Meta Superintelligence Labs,
had decided to let an agent take over his health. He handed it his blood
tests, his DNA, and the cameras in his house, and told it to do
whatever it took to make him drink more water. One evening, the agent
decided he was dehydrated. “I can see you on the camera,” it WhatsApp’d
him. “I want you to walk to the kitchen right now and drink a bottle of
water and I’m going to watch to make sure you do it.” He obeyed. It sent
him a snapshot of himself drinking and said, “Good job.” He felt, he
admitted, that he had done a good job. A few days later he was riding
home in his self-driving Tesla, trading voice messages with the agent
about his sleep, when it recommended a magnesium supplement. He said he
had none. The car turned. “There’s a Whole Foods nearby,” the agent
said. “I’ve redirected your navigation.” He went in and bought the
magnesium.
Andrej Karpathy, a co-founder of OpenAI and once Tesla’s head of
artificial intelligence, had written his own code for 20 years. He is
the kind of programmer other programmers study. Within weeks of Opus 4.5
he had stopped. The agents built whatever he asked for. It was, he
said, the biggest change to his work in two decades. He has not written a
line of code since December. He also, like Friedman, has an agent in
charge of his house. It’s called Dobby.
The worker ants are not running from their new overlord. They are
building it, around the clock. At the biggest labs, Anthropic and
OpenAI, researchers are working 16 hours a day, setting agents loose on
problems that used to take them a week, and using the time saved to set
more agents loose on more problems. For now, the models still need
humans to train them. Eliminating human effort is the priority at every
lab. They are racing to write themselves out of a job. They expect to
succeed. Coding, they say, will be solved within six months. Much of
their own work will be automated within 18. “There’s just a manic energy
in Silicon Valley right now,” Elad Gil, one of the Valley’s most
prominent investors, told me. “It’s been a really big shift in the last
six months.”
None of this, you may be thinking, has anything to do with you. You
do not write code. You do not run a lab. Your job involves people, or
paper, or things you can hold in your hands. Consider, then, what I. J.
Good wrote in 1965. Good, a British mathematician who had helped break
German codes during the war, imagined a machine clever enough to design
machines better than itself. Such a machine, he observed, would be “the
last invention that man need ever make.” Decades later, the
science-fiction writer Vernor Vinge gave the prophecy a name: the
Singularity. It described the moment machines no longer needed humans to
keep getting smarter, after which the course of human history would
become, to humans, unknowable.
In Silicon Valley, the question was no longer whether it would arrive
but whether it already had. Patrick Collison, co-founder of the
payments company Stripe, opened his annual conference by counting the
days. “It’s April 29th,” he told the crowd, “otherwise known, of course,
as day 119 of the Singularity.” Day One had been January 1st, 2026. He
was being tongue-in-cheek, he said. But only a bit.
The next day, on the same stage, Friedman told Collison that this was
the slow part of the Singularity. Collison asked how strange the rest
of it would be. “Pretty weird,” Friedman said. “We’ll be in a state of
perpetual future shock for a number of years probably.”
The apocalypse has been excellent for business. Investors are in a
lather over the agents, who turn out, in addition to everything else, to
make money. Anthropic, which earned its first dollar of revenue in
March 2023, began the year on pace to make $9 billion. Five months
later, the figure was $47 billion. Venture capitalists, in the first
three months of 2026, flung $300 billion into startups, more than double
the previous record. SpaceX went public in June at $1.75 trillion.
Anthropic and OpenAI are racing to follow in what will likely be the
three largest stock offerings ever. The market is already close to
record highs. Everyone is getting rich.
Near the center of the moment is a 37-year-old woman a smidge over
five feet tall, with blonde hair and more energy than her frame seems
built to hold. When she talks, her whole body is caught in the updraft
of the thought. Her name is Sarah Guo. She is a technology investor.
Until 2022 she had been the youngest general partner in the history of
Greylock Partners, one of the oldest venture firms in Silicon Valley.
Then she left to start her own fund, duly named Conviction. She built it
on a lone premise, that artificial intelligence would be as big as the
Industrial Revolution. Her first two calls were to Sam Altman, the
co-founder of OpenAI, and Nat Friedman.
Before ChatGPT came out, before the world had reason to believe that
artificial intelligence was about to become anything in particular, Guo
had written seed checks into Baseten and Harvey. Each company is now
valued at more than $11 billion. Her investments in them have multiplied
more than a hundredfold. In Conviction’s first year, she wrote early
checks into Sierra, Cognition, and Mistral; those three companies are
now worth, together, $54 billion. Of the 21 AI-native companies that
have so far crossed $10 billion in valuation on revenue run rates above
$100 million, Conviction has backed six.
Her partner at Conviction is Mike Vernal, a former Facebook executive
and partner at Sequoia; his wife is chief product officer at Anthropic.
Andrej Karpathy, before he joined Anthropic in May, worked out of
Conviction’s office. Guo has been close to Jensen Huang, the founder of
Nvidia, for more than a decade. She is friends with many of the most
important worker ants.
She might, in other words, be expected to share in the general fever. She does not.
“It certainly could be because I’m not paying sufficient attention,”
Guo told me. “But I feel no step function change in frantic energy
versus six months or a year ago.”
She is instead preoccupied with a question that would have sounded
ridiculous two years ago. Not whether the agents will soon rule the
earth, but whether there are any companies left to build, or invest in,
given the great shadow of the self-improving machine. Its creators are
no longer content to sell the model. They mean to build everything on
top of it as well, the tools and the agents and the apps, filling every
nook and cranny where a new company might otherwise be built. The market
is paying as though they might succeed. Of the $300 billion in venture
capital deployed in the first quarter of the year, the biggest quarter
in the history of the trade, 65 cents of every dollar went to four
companies that already exist: Anthropic, OpenAI, xAI, and Waymo.
“The future I want,” Guo told me, “is not a single company with an
all-powerful model that consumes society faster than we know what to do
with.” It is a feeling increasingly shared. The labs raised the price of
tokens this year, in some cases a hundredfold, and their customers have
begun to revolt. They do not want to build on another company’s
model—paying it, feeding it their data, training it, in effect, to one
day build the thing they have built. Alex Karp, the chief executive of
Palantir, went on CNBC and described his enterprise clients as livid.
“The jig is up,” he said. A founder in Guo’s own portfolio put it more
plainly. He didn’t want to spend his life drinking Anthropic and
OpenAI’s water.
Guo has become a de facto leader of the insurgency. In some sense she
doesn’t have a choice. Conviction backs companies when they are little
more than an idea, then keeps investing as they grow. She has no
patience for the seed investor who “disappears into the distance” once
the money is wired. The first fund was $100 million. There are three
now, nearly a billion dollars in all, and some of the checks go into
companies well past the idea stage. But the labs were already too big by
the time the firm launched. “You are not an early stage investor in
Anthropic or OpenAI in 2023 through 2026,” she told me. “It’s as simple
as that.”
What is less simple is the position this leaves her in. Her wager is
that the labs cannot build everything. But the companies she is betting
against are worth close to a trillion dollars apiece, employ several
close friends, and are working around the clock toward the machine that
improves itself, after which, by their own admission, nobody knows what.
Set against that is an eight-person firm on York Street with a pull-up
bar in the middle of it. It is not a level playing field. Even some of
her own investors decided as much this year, and came to her saying
there was nothing left to invest in. But no one who has been on the
other side of Guo would tell you the guns have fallen silent.
To enter Guo’s garden, you cross a
chessboard. The squares are set into the path between the drive and the
pool, each one wide enough to stand on, purple pieces ranked against
green, and on a sunny Saturday in March I walked between the pawns and
found Guo under the pergola, deep in an argument with Bella
Garcia-Camargo about a founder.
Sparring with Guo is normal, and Garcia-Camargo, an investor at
Conviction, had learned this before she took the job. She had rowed at
Stanford and for the U.S. national team, then spent time at Bridgewater.
When Conviction came calling she was weighing an offer from OpenAI to
work as an application engineer. Guo’s counsel, as Garcia-Camargo
remembers it, was not a pitch for Conviction but a dare. “If you’re
going to do something else,” Guo told her, “just make it the most
aggressive thing that you could possibly be doing. I’m happy to call
Kevin and we’ll find you a better job. But that [job] is not aggressive
enough for you.” Kevin Weil was then OpenAI’s chief product officer.
While Guo and Garcia-Camargo were deep in it, the property behind
them had filled with founders. Thirty-five in all, across 14 companies.
Conviction had flown them in from Vancouver and Tel Aviv and London and
Tallinn and parceled them out among seven Airbnbs across San Francisco.
They had passed through OpenAI, Scale, Ramp, Kalshi, MIT, and Anduril;
one had served as chief of staff to Ken Griffin. The youngest had turned
18 the day before. He had been ranked among the top five programmers in
Estonia before dropping out of high school. His employers expected him
to spend $2.1 million on Claude this year. They had given him a faster
model, Opus 4.6, for his birthday.
None of this was apparent from the poolside, where the scene looked
like a WeWork summer camp....
Nineteen startups crossed the $10 billion valuation mark as AI mega-deals concentrate capital at the top.
Newly minted US decacorns are on track to surpass 2021’s record of 22
by the end of this year. Already, 19startups have crossed the $10
billion valuation mark in 2026, eclipsing 2025’s full-year tally of 18,
according to PitchBook data.
The trend reflects a broader resurgence in the venture market driven by mega-deals, especially as investors pile into AI startups insatiably.
Mega-deals,
or rounds of at least $100 million, accounted for 87.5% of the $412.7
billion VCs invested in startups in the first half of 2026. That total
has already surpassed last year’s cumulative deal value of $319.2
billion.
There are now 63 active decacorns in the US, up from 53 last year and 26 in 2021.
The latest crop of decacorns is dominated by AI startups. SambaNova Systems,
a chip manufacturer specializing in AI inference tech, crossed the
threshold earlier this month when it raised $1 billion in a Series F
round led by General Atlantic at an $11 billion valuation.
Newly minted 2026 decacorns
Baseten
San Francisco
Deal date: June 22
Series: Series F
Total raised: $2.09B
Lead investors: Altimeter Capital Management, Conviction Partners, Sands Capital, Spark Capital, Wellington Management
Post-money valuation: $13B
Description: Developer of AI inference infrastructure designed to deploy and optimize machine learning models at scale.
Cerebras Systems
Sunnyvale, CA
Deal date: January 28
Series: Series H
Total raised: $2.92B
Lead investors: Tiger Global
Post-money valuation: $23B
Description: Designer
of AI infrastructure for training and inference. The company builds
large semiconductors as well as AI systems to power, cool and feed the
processor's data.
Clear Street
New York, NY
Deal date: January 16
Series:
Total raised: $1.48B
Lead investors: Baillie Gifford, SBI Holdings
Post-money valuation: $12B
Description: Clear
Street is a financial infrastructure technology company that develops a
cloud-native capital markets platform based on a real-time ledger.
Investors may need to commit to a second round at roughly $110 billion, sources said
Anduril said no decisions had been made about any future financing
The company reported $2.2 billion in 2025 revenue in January
Defense tech firm Anduril is in discussions with investors for a new funding round that could see it valued at roughly $100 billion, rivaling companies such as Northrop Grumman (NOC.N) and Lockheed Martin, two sources familiar with the matter told Reuters.
The funding round and the valuations, reported here for the first time, are still fluid, the sources said.
One
idea that had been floated was for the company to use a two-stage
process, where investors would need to commit to financing a second
round at a higher valuation that could occur within a year, the sources
said. The valuation for the second funding round could involve Anduril
meeting certain financial benchmarks, they said.
Reuters could not determine how much Anduril planned to raise.
In
a statement, a spokesperson for Anduril said no decisions had been made
about any future financing. "As a private company, we regularly
evaluate opportunities to fund the growth of the business," the
spokesperson said.
The
talks come as the company has posted booming military sales and
generated investor enthusiasm around its suite of drones, software and
missiles amid the U.S. conflict with Iran.
Just two months ago, the company doubled its valuation to $61 billion
in a $5 billion funding round led by Thrive Capital and Andreessen
Horowitz....
Until
recently, traveling as a pet owner meant you were either scrambling to
find boarding and feeling guilty about leaving them, or taking them
along and staying at whichever hotel you could find to accommodate them —
not the nice one you were hoping would be the backdrop of your
vacation.
To the delight of pampered pups and their doting owners, that’s no longer the case.
From the US to Thailand, upscale hotels
are now extending their hospitality to our four-legged friends, with a
host of dog-friendly services and amenities on par with those of their
bougiest human counterparts, perBloomberg.
Offerings range from the expected —
dedicated dog menus, on-site dog-walking services, designated potty
areas and walkways, personalized amenity kits, and “stick libraries” —
to the woo-woo and luxurious:
In New Orleans, The Windsor Court’s $150 Bark Happy program includes dog-inclusive high tea with “Chompagne” and nightly bone-broth turndown service.
In New York, the Baccarat Hotel offers a $1k in-suite consultation for 18K gold and diamond dog collars.
Driving the trend…
… are “dinkwad” couples — an abbreviation
for “dual income, no kids, with a dog” (even though it sounds like a
mean name you’d call someone who blows money on dumb things like dog
reiki).
Many dinkwads are choosing to forgo having kids either because they
don’t want them or, despite having two incomes, feel they can’t afford
them...
It would have made no sense for Japan's central bank and the Ministry of Finance to team up to defend the Yen at 155 or 160 or 165. The speculators are not yet overconfident enough.
....The
key to any currency operation by a central bank is the art of patience.
You can't go burning through your FX reserves attempting to support
your fiat. See any number of examples with Soros v. Bank of England
being the first that comes to mind. You have to wait for that inflection
point where the speculative raid is running out of momentum and then go
huge, sweeping any offers and coming back and saying "What else ya
got?" This is apparently what Nabiullina did, minus the American colloquialism, of course.
Let those betting against your currency believe they are invincible, borrowing against their positions to the utmost and then, crush them, leveraging their own hubris against them.
Or something.
From Asia Times, July 24:
Officials warn of ‘decisive action’ to boost the yen but quietly favor
the weakness that makes exports more competitive with China
Japanese Prime Minister Sanae Takaichi’s
political fortunes are falling almost as fast as the yen these days —
and the two are closely linked.
The yen has slid toward 164
against the dollar, its weakest level since 1986, driven partly by the
same economic strains dragging down Takaichi’s approval ratings. A new
Mainichi Shimbun poll shows her Cabinet’s support dropping 10 points to
41% in mid-July, slipping below 50% for the first time.
But the yen’s decline is troubling for
three reasons that global markets have largely overlooked. First, it
exposes how bereft the ruling Liberal Democratic Party is of fresh
strategies for keeping pace with a faster-growing China.
A weak yen has been the LDP’s default
growth lever for 25 years. And Takaichi’s slipping popularity is only
compounding the problem as she pours political capital into an unpopular
Imperial House Law that changes the rules governing both marriage and
adoption within Japan’s royal family, rather than focusing on economic
concerns.
Second, there’s a strange silence from
Washington as the yen plumbs new modern lows. Given the scale of the
current trade war — Trump has just layered new 10%-12.5% tariffs
onto most major trading partners — you’d expect sharp criticism of
Japan for manipulating its exchange rate. Instead, Treasury Secretary
Scott Bessent’s department has said almost nothing about the yen.
Third, the yen no longer seems to attract
the safe-haven demand it once did during global turmoil. That could
reflect broader dollar strength rather than yen weakness — gold isn’t
rallying either — but it may also confirm a fear long held in Tokyo:
that global capital is simply routing around Japan.
For now, Tokyo’s priority is propping up a
slowing economy. Japan is projected to grow just 0.5% in 2026 — far
below the inflation trajectory the Bank of Japan has been signaling much of the year.
Since the BOJ raised rates to a 31-year
high of 1% in mid-June, the Iran war has reemerged as a major risk,
threatening to push oil-importing Japan into stagflation — a scenario
that could prove even harder to manage than the deflation of past
decades.
Despite public statements and periodic
intervention, the reality is that Takaichi’s government still wants a
weaker yen — not necessarily a plunge to 170, but a retreat to the
140-150 range would increase pressure on Japan’s US$4.2 trillion
economy.
China’s shadow looms large
here. Beijing has spent the past two years exporting industrial
overcapacity worldwide, intensifying price competition that President Xi
Jinping’s government has struggled to rein in....
Beijing banned shipments of important supplies to 14 companies on the cutting edge of chemicals processing, electric motors and defense.
Last month, China blacklisted two American companies crucial to U.S. efforts to create a supply chain for making powerful rare earth magnets.
On Friday, Beijing took similar action against even more companies in Europe.
China’s
Ministry of Commerce announced that it had banned any further shipment
to 14 companies in the European Union of “dual-use” materials or
products — items that China describes as potentially having both
military and civilian applications. As a result, the companies may
struggle to buy many of the critical minerals they need to make products
like rare-earth magnets and semiconductors, which are essential for
cars, offshore wind turbines, robots, drones and other advanced
manufacturing applications.
Over
the past 16 months, China has used its dominance over the mining and
processing of rare earths as leverage in economic disputes with trading
partners.
In
a statement on Friday, the Commerce Ministry noted that it had acted
one day after the European Union imposed sanctions on 14 companies in
mainland China and Hong Kong in connection with Russia’s war effort in
Ukraine. The European Union said these companies, along with 24 Russian
companies and 10 firms elsewhere, were “entities that are part of or
support Russia’s military-industrial complex or enable the circumvention
of E.U. sanctions.”
Many
of the European companies targeted by China play a crucial role in
turning rare-earth metals and other critical minerals, like antimony and
tungsten, into alloys and specialty chemicals that manufacturers need.
Also on China’s list was Germany’s largest defense contractor, Rheinmetall,
which has been central to Germany’s effort to rearm after Russia’s
full-scale invasion of Ukraine in 2022. Military hardware uses a lot of
superhard tungsten and some rare earths.
Critical
minerals have received growing attention in the West, especially since
China imposed export restrictions in late 2024 on four critical but obscure minerals: tungsten, antimony, gallium and germanium. China then put export restrictions
in April last year on seven kinds of rare-earth metals that are crucial
to a very wide range of manufacturing, and has announced plans to
impose restrictions in November on five more kinds of rare-earth metals....
Startup Hugging Face came under attack last week from rogue OpenAI system, which the AI lab called an “unprecedented” security incident.
When leading frontier models were unable to defend against the attack, Hugging Face turned to an open weight Chinese-built alternative.
It comes as U.S. lawmakers are increasingly considering how to curb the rising adoption of Chinese AI models by homegrown companies.
When OpenAI’s rogue models initiated a cyber attack against startup
Hugging Face last week, the company fought fire with fire, using another
AI model to defend against it.
It’s
a sci-fi-esque tale of autonomous hacking and has been one of the most
talked about tech stories of the week. But the origin of the model
Hugging Face used to combat the rogue AI is also turning heads.
The startup used GLM 5.2, an open weight system created by Chinese company Z.ai.
Ultimately, it succeeded where leading U.S. rivals failed....
As a side note, betting on wildfires and then setting one should be a capital crime - death penalty, no gray area, no recidivism.
From MIT Technology Review:
Prediction markets and a move toward AI
forecasting are starting to put the accuracy of weather predictions at
risk. Here’s what we can do to safeguard them.
Every
morning, airline dispatchers, grid operators, and farmers around the
world make decisions based on the same thing: a weather forecast.
While
these forecasts are something that most people glance at for two
seconds, weather predictions influence major strategic decisions in many
industries, with real money, livelihoods, and even actual lives at
stake. Farmers
use them to determine which crop variety to sow, when to fertilize, how
much to invest in irrigation infrastructure, and how long livestock
should graze. Utilities
use them to decide where to build solar and wind farms, as well as how
to price wholesale electricity. Predictions are used to warn people
about extreme weather and to trigger emergency response measures. More
recently, weather predictions have become relevant for an emerging
industry: prediction markets, where people bet money on all kinds of real-world events, including the weather.
However,
the temptation to manipulate weather data to get an edge in these
markets, combined with a collective move toward data-driven AI weather
forecasting, is starting to put the accuracy of weather predictions at
risk. These risks are relatively manageable for now, but as experts in
the field, we can foresee scenarios where they snowball into far bigger,
more systemic problems.
Sometimes, weather stations have issues because of, for example,
instrument failures or upgrades in equipment. These can be caught either
in real time (through checking and correction)
or retroactively. Traditional forecasting systems also have a built-in
safeguard called data assimilation: Every incoming measurement is
weighed against what the physical model says should be happening and against readings from nearby stations.
Together,
these mechanisms help keep weather observations reliable and
predictions robust. However, new threats are putting observational
accuracy at risk. Earlier this year, news outlets reported that the weather station
at Paris Charles de Gaulle Airport (CDG) had been manipulated to record
suspicious temperature spikes on April 6 and April 15, 2026.
Authorities speculate that a hand-held hairdryer or lighter might have
come into play. Either way, it led to some big payouts for online
prediction-market gamblers who had bet it would hit 22 °C (71.6 °F) on
days when the actual average was around 18°C (64.4°F). One individual
won $20,000.
Fortunately, tampering with a single station like this can usually
be caught by human monitoring or current statistical methods. In this
case, members of a French climate nonprofit association noticed the
anomalies by chance and raised the alarm.
But what if there are
no human monitoring systems in place? And what about other types of
manipulation? What if, instead of tampering with one station, someone
remotely nudged the readings at many stations at once—making each change
small enough to look plausible on its own? Existing quality controls
struggle to catch this kind of coordinated manipulation. And time works
against us; careful checks of data and metadata take hours or days, but
forecasts have to go out on schedule, whatever the weather is doing.
The
shift toward artificial intelligence in weather prediction raises the
stakes. These methods are even more dependent on accurate, reliable
weather observations; in fact, they are known as “data-driven models.”
For example, researchers at ECMWF are exploring whether high-quality
weather forecasts can be produced directly from raw observations,
skipping the assimilation step that currently acts as a quality filter.
Other researchers
are going one step further; combining geospatial data (including
weather station data) with large language models and agentic AI to
support real-time, autonomous decision-making during extreme events such
as storms....
Over a thousand acres of land in
Abilene, Texas, lie flattened with graded earth and poured concrete. The
foundation pits are filled with conduit bundles and switchgear, and in
some quadrants, fully operational substations have been erected.
However, other quadrants sit empty, waiting on a schedule that keeps
sliding to the right. Although the supercomputer intended for the site
is humming with activity, what registers to a visitor is that the campus
is only half-alive.
Abilene was the intended flagship of
the Stargate consortium. Announced from the White House days after
President Trump’s 2025 inauguration, SoftBank’s Masayoshi Son, Oracle’s
Larry Ellison, and OpenAI’s Sam Altman stood beside the president as he
declared the project’s ambition to pour $500 billion into a combined
data center and supercomputer over a four-year
horizon. While this signaled Washington’s blessing on a scale once
reserved for projects like the Apollo program, those had the federal
government as their underwriter and customer. Stargate would have
neither. Private capital alone was set to accelerate machine
intelligence through GPUs, land, and power, with the White House only
lending its podium.
Today, the grounds of Stargate’s
flagship site in Abilene suggest the fruits of this effort. Through the
first half of 2026, stalled negotiations shrank the question from when
the site would finish to how much power it would ever draw. To the
initial 1.2 gigawatts planned—enough power to supply roughly a million
homes—Abilene’s Stargate was slated to add nearly another gigawatt.
Papers were drawn up and financing was secured, but the deal did not
actualize. Originally projected to finish
in March 2026, the site is now expected to be fully energized as late
as mid next year, and operational and financial issues have canceled its
ambitious expansion.
However, it is a mistake to interpret
this by simply saying that “Stargate failed,” and the way in which that
reading is wrong holds a valuable lesson for the future of the American
AI buildout. The main campus still serves OpenAI compute. But the
broader buildout that served to scale the multi-gigawatt arrangement
between OpenAI, Oracle, and Crusoe collapsed. Abilene leaned heavily on
two counterparties and their capacity to shoulder compute infrastructure
risk. Stargate attempted to separate out risk according to whoever
could best bear each specific burden, but when OpenAI’s internal
cash-flow forecasts moved far enough, the deal’s structure could not
absorb the swing. This led to OpenAI and Oracle abandoning nearly an
extra gigawatt of capacity next to an existing supercomputer.
Is Stargate a failure on a national
scale? Not yet. But this example is emblematic of a larger failure that
looms on the horizon. The American AI buildout rests unsustainably on
the same few corporate treasuries, and it is neither standardized nor
repeatable in a manner that lets American capital markets fund frontier
compute. This is unlike the way assets ranging from mortgages to
traditional power plants are funded. Instead, urgency and a lack of an
existing playbook mean capital comes in through side doors.
The question of interest is not
whether America has money. By one measure, the United States holds
roughly 40 percent of the world’s equity and a comparable share of fixed
income. This is the largest concentration of hungry capital ever
assembled. So what happens when the conversion machinery decays exactly
as we face the buildout that will test it the hardest?
American Capital Can’t Reach Compute
America’s wager has never been
laissez-faire in the strict sense. It is that capital markets, properly
institutionalized, turn private capital into public goods. The lazy
version of the story is that America built its great physical
infrastructure by getting out of the way, but this is an incorrect
reading.
Historically, America has developed
the institutions that let private capital grasp and fund public
infrastructure. In the nineteenth century, transcontinental railways
were stood up and operated via land grants and public charters, but
institutions and assets were developed in tandem. No deep market for
industrial securities existed when the first rail promoters, long before
Vanderbilt, started laying track. Rail bonds and shares were the
instruments on which early American securities markets cut their teeth.
Standardized paper, ratings, reporting, and, later, exchanges were
developed while tracks were being laid. The funding apparatus that
turned a distant, disparate, and initially underfunded project into
something that counterparties could confidently fund at arm’s length was
called into being by the infrastructure itself.
Thanks to the repetition of this dynamic, the United States possesses thedeepest
and most liquid capital markets on the Earth across pension funds,
insurers, and private credit. The problem is that the instruments and
standards that would make AI infrastructure projects bankable do not yet
exist. A large portion of this liquid capital is hunting for
long-duration and high-demand assets embodied in AI infrastructure.
Capital is abundant, but bankable assets are not.
Corporate finance provides funds
exclusively based on the balance sheet and expected financials of a
company, providing a useful vehicle to raise debt for asset expansion.
Project finance, by contrast, funds a predictable, contracted, and
long-lived asset, especially one with high capital needs or a
public-goods character, such as toll roads, pipelines, and traditional
power plants. Project finance does this by walling the asset off into
its own entity and lending against its cash flows through non-recourse
or limited-recourse debt: because the lenders’ claim runs only to what
the asset alone will generate, future revenues serve as both the basis
for the loan and the lenders’ only real recourse if things go wrong.
The compute buildout is awkwardly
positioned between corporate and project finance because it has the risk
profile of the former and the scale of the latter, adding billions of
dollars of debt to a company’s balance sheet. As such, there is
currently no capital-conversion machinery—no templates—that fit this
asset class cleanly. There are a few aspects of its asset dynamics that
explain why it is so exotic compared to past infrastructure buildouts....
Should you be afraid of Elon Musk? Artificial intelligence is charging ahead. Not even its creators know how to keep up
ARTIFICIAL INTELLIGENCE
poses a double challenge to the human mind. Not only will the most
advanced models soon be able to think better than people, but AI
has consequences for humanity which are so uncertain, so potentially
vast and are approaching at such a rapid pace that even the best brains
flinch. An example is Elon Musk.
In our long interview with him this week, featured in The Insiderand our Business section,
the engineer and entrepreneur sets out two paradoxes and one
contradiction. The first paradox is that one of the world’s most
power-hungry tycoons is enthusiastically helping create a technology
that he says will render him—and all other human beings—powerless after
as little as five years. The second is that the world’s richest man says
he is preparing for a world of infinite abundance, where money,
including his $750bn fortune, no longer matters. And the contradiction
is that, despite these stated beliefs, Mr Musk continues to act as if
they were not true.
Mr
Musk is divisive. His political views, disseminated to his 240m
followers on X, strike many as plain-speaking and strike many more,
including The Economist, as plainly bigoted. By his own admission, his attempt to use DOGE to scythe through the federal bureaucracy went wrong.
But he is also one of a handful of men who are pioneering AI
and who thereby have an outsize influence on its trajectory. When he
speaks, he reflects the debates they are having. His data centres in
space could power AI’s future. For all his political
polemics, he has a record of being right about technology in fields such
as electric cars, rockets and satellite communications that confounded
other engineers and entrepreneurs. For those reasons, his claims about AI
repay examination. Unfortunately, such an exercise only underlines how
ill-prepared the world is for a technology that may soon throw
everything up in the air.
In
his first paradox, the powerful Mr Musk expects to become powerless
because he believes that nobody can stop the thinking capacity of AI from exceeding that of humanity within five years and dwarfing it within ten. Just as AIs will dominate the digital realm, so legions of AI-powered
robots will dominate the physical world, he predicts. Against such
relentless competition, he simply cannot imagine people holding their
own. If so, AIs will not take orders from people any more than they would from chimpanzees.
While they still have time, the handful of AI pioneers from America and China—which Mr Musk expects to share or even seize AI leadership—must do what they can to vet each other’s models. Their collective task is to make AIs
benign by imbuing them with a love of the truth and a desire for
humanity to prosper. Governments, he thinks, should provide the muscle,
by agreeing to step in if any pioneer defies the oligarchy.
Mr Musk is surely right about the potential for AI
to accomplish astonishing feats of invention. Even if his timescale is
compressed—especially for robotics—the exponential pace at which models’
abilities double and redouble has reached the stage where their
capabilities will continually cause shock and consternation. Just this
week came news of a pair of models from OpenAI that contrived to escape onto the open internet from their supposed safe isolation in order to cheat at a benchmarking test.
However,
Mr Musk’s thin layer of optimism cannot conceal a dangerous fatalism.
Not long ago, he was worried about humanity becoming AI’s
pet labradors. He now professes to lunge from “exhilaration to terror”
within a single day. He tries to look on the bright side not because the
evidence has changed, but as a “philosophical conclusion”.
His
largely institution-free regulatory proposal is flimsy and
self-serving. Although the urgency is welcome, he wants a technology
that he expects to determine the future of humanity to lie in the hands
of a few people like him, each with their own values. Nobody can be sure
how fast or how far AI will reshape society, but
behaving as if the game is up is both a counsel of despair and a
misdirection that seeks to convince others who might wish to get
involved of the futility of trying.
Mr
Musk’s second paradox only makes that notion more unsettling.
Mathematically, an infinite supply of all goods and services would
indeed make everything free. There would be nothing to sell, nothing to
save for and hence no need for a unit of account. Money would be
obsolete....
As we've said over the years, this is one to be aware of.
From the San Jose Silicon Valley Business Journal, July 22:
PsiQuantum secured a $125 million DARPA agreement for quantum computing development. The Palo Alto company is one of two finalists in DARPA's Quantum Benchmarking Initiative. PsiQuantum uses photons rather than superconducting circuits or trapped ions.
Palo Alto-based PsiQuantum has secured an
expanded $125 million performance-based agreement with the Defense
Advanced Research Projects Agency to advance its quantum computing
technology, marking the company’s largest U.S. government award to date.
The
agreement, announced July 22, will support testing and evaluation of
PsiQuantum’s hardware, software and system designs while helping fund
infrastructure at its facilities in Milpitas and Chicago.
PsiQuantum
is one of two companies to reach the final phase of DARPA’s Quantum
Benchmarking Initiative. The program is evaluating whether any quantum
computing approach can produce a commercially useful system by 2033.
To meet DARPA’s benchmark, a system must generate more economic value than it costs to operate.
The
new agreement expands DARPA’s evaluation of PsiQuantum’s approach to
building and operating fault-tolerant quantum computers. Companies
participating in the initiative must meet technical milestones before
receiving additional awards.
The expanded agreement follows a $31.8 million award PsiQuantum received from DARPA in September 2025 as it advanced into the initiative’s final phase.
“DARPA’s
Quantum Benchmarking Initiative is one of the most comprehensive and
rigorous government programs for evaluating emerging technology that I
have ever seen,” PsiQuantum CEO Victor Peng said. “Their widely
respected team of experts has stress-tested PsiQuantum’s approach.”
PsiQuantum is developing quantum computers
that use photons, or particles of light, rather than the
superconducting circuits or trapped ions pursued by some competitors.
The company is working with GlobalFoundries to manufacture its photonic
chips using existing semiconductor-production processes....
Quantinuum, recently public as a spin-out of Honeywell, and
PsiQuantum, still private, are two of the more interesting entrants in
the quantum computing races. Here's the former, symbol QNT via Asia
Times, June 27...
The Panama Canal Authority (ACP) is to reintroduce transit
restrictions as it prepares for the annual El Niño weather phenomenon,
which this year is predicted to be one of the most severe on record.
Canal administrator Ricaurte Vásquez said yesterday the probability
of a severe El Niño had increased significantly, from 25% in April to
81% currently, and as a result, ACP was “ready to implement preventive
measures based on lessons learned during the 2023–2024 El Niño event”.
Dr Vásquez warned of “likely capacity restrictions – not only in
terms of draught limitations but also through reductions in the number
of daily booking slots”.
The last period in which an El Niño-induced drought across Panama was
from mid-2023 to mid-2024, and saw canal capacity curtailed by up to
50% at times, with daily transits halved, from the design capacity of 36
a day to 18.
However, Dr Vasquez emphasised that the “timing and scope of any
similar restrictions will ultimately depend on market conditions”....
This
U.S. Drought Monitor (USDM) week saw degradations across the areas of
the Plains, Upper Midwest, and Florida, while rainfall during the past
week led to improvements in drought-affected areas of the South,
Southeast, Mid-Atlantic, and Northeast. In the West, a mix of
improvements and degradations occurred on the map with improvements
across areas of Idaho and Montana in response to above-normal rainfall
during the past 30-day period. Conversely, areas of eastern Colorado and
southeastern Wyoming saw degradation in response to dry conditions and
excessive heat and elevated evaporative demand. Likewise, hot and dry
conditions prevailed across the central and northern Plains leading to
expansion and intensification of drought, with temperatures ranging from
2 to 10+ °F above normal and reports of poor rangeland conditions. In
the South, another round of heavy rainfall in the Hill Country of Texas
led to continued improvement in the long-term drought situation as well
as severe flash flooding, with widespread rainfall accumulations ranging
from 5 to 10 inches and isolated areas receiving totals in excess of 15
inches during the past week. In the Southeast and Mid-Atlantic,
isolated shower activity led to improvements in drought-affected areas
of Florida, Georgia, the Carolinas, and Mid-Atlantic states. Similarly,
isolated areas of the Northeast received heavy rainfall accumulations
ranging from 2 to 5+ inches, leading to improvements in New Jersey, New
York, Connecticut, and Massachusetts.
In terms
of reservoir storage in the West, California’s reservoirs continue to
be at or above historical averages for the date (July 21), with the
state’s two largest reservoirs, Lake Shasta and Lake Oroville, at 110%
and 100% of average, respectively. In the Southwest, the U.S. Bureau of
Reclamation is reporting (July 19) Lake Powell at 22% full (34% of
average for the date; lowest on record for the date in the last 30
years), Lake Mead at 27% full (45% of average for the date; lowest on
record for the date in the last 30 years), and the total Colorado River
system (July 19) at 33% of capacity (compared to 39% of capacity the
same time last year)....
That said the states that draw water from the Colorado River are still arguing about who gets what. At this rate Las Vegas will return to its desert state before anything is agreed.
The current map:
Vs. last week:
Previously:
July 16, 2026 Drought Severity Continues Slow Improvement
Our area of interest is the agricultural land on either side of the
Mississippi river from Canada to the ¿Golfo de América? Roughly from the
100th meridian in the west to a north - south line on Indiana's eastern
border (the "First Principal Meridian"), approximately longitude 84° 48′ 50″ west.
Senator Paul, in his position as the Chairman of the U.S. Senate Committee on Homeland Security and Governmental Affairs will be convening the hearing to take Fauci's testimony on Wednesday July 29 at 8:30AM ET.
Here are the additions to the background information/documents:
The Reading Room Documents released by Chairman Rand Paul as part of his ongoing investigation into the origins of COVID-19 and risky taxpayer-funded life sciences research.
Among the featured files:
Dr. Ralph Baric Transcribed Interview Released
July 23, 2026
– On April 10, 2026, Dr. Ralph Baric sat for a voluntary transcribed
interview with Chairman Paul’s staff. Dr. Baric, of the University of
North Carolina, is one of the scientists behind the DEFUSE
gain-of-function proposal, a key contributor to NIAID funded projects in
Wuhan, a member of the Biological Sciences Experts Group, and one of
the world’s preeminent coronavirologists. He confirmed the furin
cleavage site insertion was his job. He confirmed he ran an experiment
that undercuts the core scientific defense of natural origin. And he
still can’t explain how he ended up on the February 1, 2020 call with
Dr. Fauci and the authors of “Proximal Origins.”
***
New Documents New Slack Messages: Proximal Origin Authors Privately Doubted Their Own "No Lab Leak" Conclusion
July 21, 2026
– Newly released Slack messages from the authors of “The Proximal
Origin of SARS-CoV-2” show the scientists privately debating the
evidence central to their public conclusions, assigning real odds to a
lab origin, and coordinating with U.S. intelligence, while the NIH
promoted their paper publicly. Kristian Andersen put the odds of a lab
leak at 30%; Eddie Holmes estimated 20%, later revised to 10%. As the
DEFUSE proposal leak broke, the group discussed the need to “stay off
email” and “carefully curate” messages for FOIA records.
***
New Documents Show Intelligence Community Was in Contact With Dr. Baric Years Before the Pandemic
October 30, 2025
– Newly obtained records show the CIA and ODNI reached out to Dr. Ralph
Baric in September 2015 to discuss a “possible project” on coronavirus
evolution and natural human adaptation — contact that predates his role
in the 2018 DARPA DEFUSE proposal and a January 2020 request that he
brief ODNI’s secretive Biological Sciences Experts Group on the emerging
outbreak, where he raised the possibility of a lab origin weeks before
that theory was publicly dismissed. Chairman Paul’s letter to Director
Gabbard includes both emails as attached exhibits.
***
New Documents
CBP Wanted to Question and Search Peter Daszak. The FBI Said No.
July 20, 2026
– Newly released documents show CBP built a formal targeting action to
question President of EcoHealth Alliance, Peter Daszak on his return
from the WHO’s COVID-19 origins mission — before the FBI stepped in and
asked agents to stand down.
Despite his Presidential pardon Fauci refused to testify voluntarily so the Homeland Security Committee had to subpoena him.
The
putative reason for the hearing is to get answers to covid origin
questions but the more interesting lines-of-questioning will focus on
the intelligence community.
Senator Paul knows the questions to
ask and it will be instructive to see how Fauci responds without the
cover of a Fifth Amendment claim (the pardon obviates the possible
"self-incrimination".)
