CERN, the world’s largest particle physics laboratory, has spent decades collecting enormous amounts of data from particle collisions. With the recent rapid growth in AI capabilities, CERN wants to develop a foundation model that can make better use of all that data.
To help it achieve this goal, the European physics laboratory has teamed up with French AI company Mistral. The two have signed a statement of intent to explore the development of foundation models for scientific research.
CERN is already using AI for particle physics. With Mistral, CERN wants to move from multiple specialized AI models to a more general foundation model that could perform several scientific tasks. Their first project is a proposed Large Physics Model, reportedly called Flare, that would be trained on billions of simulated collisions from the Large Hadron Collider (LHC).
How much data has LHC collected? According to some estimates, CERN currently holds around one exabyte of experimental data from the LHC. That is equivalent to one million terabytes. And that amount is expected to grow significantly. An upgrade to the LHC around 2030 is expected to increase the number of collisions tenfold.
The new foundation model with Mistral could handle several of these tasks together. It could help reconstruct collision events and identify particles, reducing the need for separate algorithms.
What’s in it for Mistral? The partnership provides access to one of the world’s largest scientific datasets and an opportunity to expand its work into scientific research....
The activity comes ahead of NVIDIA GTC Berlin, taking place from 20 to 22 October 2026, where founder and CEO Jensen Huang will deliver a keynote.
But beyond the conference preparations, the announcements reveal a wider strategy involving startup funding, computing infrastructure, research partnerships and the development of AI applications across European industries.
NVIDIA’s 2026 European investment trail
This week builds on an investment footprint already documented by EU-Startups throughout 2026. The company has participated in funding rounds involving French AI developers Mistral AI (€3 billion) and AMI (€890 million), alongside British companies Nscale (€1.7 billion), Wayve (€1 billion), Ineffable Intelligence (€937 million) and Orbital Industries (€43 million).
In Spain, Valencia-based iPronics secured €107.6 million with NVIDIA backing, while its venture arm, NVentures, joined a €42 million extension for Sweden’s Legora.
Together, these eight announcements represent approximately €7.72 billion in company financing, although NVIDIA’s individual contributions have not been disclosed. Earlier investments in British startup PhysicsX and France’s Scintil Photonics further illustrate its established involvement in European AI development.
Fresh bets on British and French startups
Continuing this investment commitment in Europe, NVIDIA unveiled planned investments in five startups: Boltz, Foresight, Hiverge, Prima Mente and Riverlane. Although the individual investment amounts have not been disclosed, the selection of companies provides an indication of where NVIDIA sees opportunities for technological development.
These companies join NVIDIA’s existing investment activity in the UK, where it has previously supported startups including Synthesia, Wayve, Basecamp Research and Ineffable Intelligence.
The announcement also highlighted the role of NVIDIA’s Inception programme, which now includes more than 3,100 UK companies. The programme provides eligible startups with access to technical resources, expertise and opportunities to connect with NVIDIA’s wider network.
Across the English Channel, NVIDIA announced planned minority investments in four French startups: Doctolib, Entalpic, Genesis AI and Pigment. As previously reported by EU-Startups.
On 13 October, Huang attended an AI ecosystem reception in Paris alongside founders, researchers and policymakers, including France’s Minister of the Economy, Roland Lescure. Later that evening, he met President Emmanuel Macron at the Élysée Palace to discuss AI infrastructure, investments in French technology companies, open-source development and AI safety.
Speaking at the Paris reception, Jensen Huang, founder and CEO of NVIDIA, said, “Europe is one of the great regions of industrial manufacturing,” adding, “This is the beginning of the AI journey for the EU.”
This week also saw the launch of the Startup Ireland AI Accelerator Programme, which aims to support 1,000 new startups by 2030. NVIDIA is among the technology partners associated with the initiative, further extending its involvement in Europe’s entrepreneurship networks.
Ecosia’s decision to drop French AI provider Mistral is not a move towards Chinese technology, but rather a shift towards more affordable, energy-efficient open AI models, founder and CEO Christian Kroll clarified in a conversation with EU-Startups.
“We’ll probably be using Melious.ai in future. Unlike Mistral, this is a European company that offers high-quality, affordable AI inference powered by green electricity,” shared Christian in an exclusive interview.
The Berlin-based search engine recently made headlines after POLITICO reported that it was replacing Mistral with open models, including Chinese offerings such as Alibaba’s Qwen, Z.ai’s GLM and Moonshot AI’s Kimi.
However, Christian stressed that the company’s focus is on open models rather than their country of origin. These offer lower costs, greater flexibility and reduced energy consumption, aligning with Ecosia’s environmental mission.
Addressing concerns about political censorship in Chinese AI models, Christian explained that Ecosia can switch to alternative models when dealing with sensitive subjects, such as questions about Taiwan. The company is also working to eliminate political biases from its AI-generated answers.
The models are accessed through German platform Melious, which operates on European infrastructure powered by low-carbon energy. This allows Ecosia to use internationally developed AI while keeping its infrastructure and data processing in Europe....
This was the most in-depth article on the chip venture that we saw. We'll go to Bloomberg for the large-by-large financing.
From Korea's Edaily, September 9:
Strategic Partnership Signed Suddenly to Coincide with South Korea-France Summit
DS Data and Mistral Raji Join Forces… to Build Enhanced Security
"Setting a New Standard for Semiconductor Innovation… Contributing to the Global Value System"
Samsung Electronics Chairman Jay Y. Lee and Arthur Ménch, CEO of Mistral AI, pose for
a commemorative photo on the 8th (local time) at the Élysée Palace in Paris, France, after
exchanging an investment agreement in the presence of President Lee Jae-myung and French
President Emmanuel Macron. From left: Samsung Electronics Executive Vice President Lee
Jong-myung, Samsung Electronics Chairman Jay Y. Lee, President Lee, President Macron,
and Arthur Ménch, CEO of Mistral AI. (Photo: Yonhap News)
[Edaily Reporter Han Kwangbeom ] SamsungElectronics(005930)Samsung Electronics has led a 3 billion euro (approximately 4.7 trillion won) Series D funding round for the French artificial intelligence (AI) company Mistral AI and signed a long-term technology partnership. Through this, the company has significantly expanded its influence in the global AI ecosystem.
SamsungElectronics announced on the 9th that it has entered into a strategic partnership with Mistral AI and agreed to jointly develop “semiconductor-specific AI” that combines the technology and manufacturing data from its DS (Semiconductor) Division with Mistral AI’s high-efficiency AI model technology to enhance productivity and precision across the entire semiconductor operations. SamsungElectronics plans to use this partnership as an opportunity to accelerate the AI transformation across all business divisions, including semiconductors, and strengthen its competitiveness in the global AI semiconductor market.
The signing of this partnership was timed to coincide with the South Korea-France summit. Previously, Mistral AI had officially announced a 3 billion euro investment round led by SamsungElectronics, with EQT’s Scale-Up Europe Fund and PSG Equity serving as co-leads. New investors in this round included BlackRock, Advent, and the Grand Duchy of Luxembourg, while major existing shareholders—such as NVIDIA, ASML, Andreessen Horowitz (a16z), and Salesforce Ventures—also participated in significant reinvestments.
SamsungElectronics’ investment marks the largest equity investment in the history of European tech companies, and Mistral AI has achieved a valuation of over 21 billion euros (approximately 33 trillion won) just three years after its founding. Mistral AI stated, “This investment is a significant milestone achieved under SamsungElectronics’ leadership,” adding, “The funds raised will be used to strengthen our infrastructure and product capabilities and accelerate large-scale deployment; above all, they will serve as a driving force to continue and expand our frontier research and AI model development.”
◇Mistral: Europe’s Leader in “Sovereign AI”… Unparalleled Influence in Technological Sovereignty and the Ecosystem
Mistral AI, a leading player in the European AI ecosystem, was founded by AI researchers from Google DeepMind and Meta, led by CEO Arthur Mensch. Mistral AI possesses unparalleled technical capabilities to build customized AI models in on-premises environments for industries requiring a high level of data security, such as finance, manufacturing, and energy....
Mistral AI Boosts Valuation to €21 Billion in Samsung-Led Round
Mistral AI has raised €3 billion ($3.5 billion) at a valuation of more than €21 billion from investors led by Samsung Electronics Co. to fund the development of artificial intelligence models and build computing infrastructure.
The EU’s Scaleup Europe Fund and PSG Equity co-led the round, the company said in a statement on Tuesday. The Paris-based startup has nearly doubled its €11.7 billion valuation from its last fundraising round a year ago.
The funding will give Mistral the ammunition to advance in industrial AI, which involves rolling out the tech for manufacturing processes and is emerging as one of the company’s key differentiators, Chief Executive Officer Arthur Mensch said in an interview. While Mistral is a fraction of the size of generative AI behemoths such as OpenAI and Anthropic PBC, the company has been selling itself as a sovereign alternative for Europe. It’s struck deals with large European industrial companies including Airbus SE, BMW AG and Dutch chip-machine maker ASML Holding NV, which led Mistral’s previous round.
“This fundraising is also a way for us to further expand in the US, in Asia and of course to double down on what we’ve been doing in Europe,” Mensch said. “This is a technology that requires significant infrastructure.”
That involves owning “significant assets” such as data centers, he added. Earlier this year, Mistral raised $830 million in debt for a data center project outside Paris that would use Nvidia Corp. chips. The company committed a further €1.2 billion to a data center buildout in Sweden, its first data center investment outside France.
Similar to the ASML partnership, the agreement with Samsung “opens the door for further collaboration,” Mensch said. ASML, which participated in this most recent funding round, invested €1.3 billion for an 11% stake last year. ASML CEO Christophe Fouquet said at the time he planned to “flood the entire organization” with AI.
Mistral was founded in 2023 by Mensch, an alumnus of Google’s DeepMind, and ex-Meta Platforms Inc. researchers Timothée Lacroix and Guillaume Lample. It develops open-source large language models, in contrast to the “closed” models developed by its larger American counterparts. Mensch has touted open source as more cost efficient and easier to integrate into large, complex corporate systems.
Mensch is counting on gaining traction with European governments, fearful of relying too heavily on artificial intelligence products owned by American and Chinese companies. US President Donald Trump’s administration compounded these fears this summer, when it ordered Anthropic to disable access to its most advanced AI models for all foreign nationals, citing national security concerns....
Although
we've been pitching French startups as a potential engine of growth to
supplant German dominance, and although we've made Artificial
Intelligence one of the foci of the blog since 2013 - "Why Is Machine Learning (CS 229) The Most Popular Course At Stanford" - and although we began juxtaposing
the two strands five years ago, I'm still impressed with this sort of
money going into a company that was formed in the last five weeks....
As
usual, the Nvidia earnings call was a discursive affair, touching on
many different subjects. But the only thing that mattered in the end
came right near the beginning of the call.
The stock was down
after the earnings release showed that Nvidia's vaunted 75% gross margin
would slip a bit in the second half of the year due to spiraling memory
chip costs That outlook overshadowed another stellar second quarter.
The stock was roughly flat as the call began at 5 p.m. ET.
But
moments later Chief Financial Officer Colette Kress said the magic
words: "We expect to grow revenue by approximately 70% in fiscal 2028.
This is a supply-constrained outlook." Nvidia shares instantly surged
4%.
Fiscal 2028 begins in late January, so it encompasses 11
months of calendar 2027. Wall Street was expecting 45% growth next year,
a big slowdown from what looks to be a doubling of sales this year.
Later
in the call, CEO Jensen Huang said that were the company not
supply-constrained, sales would double again next year, and that the
company was working on opening up some of the bottlenecks holding them
back.
There was another hour of talking on the call, but none of it mattered as much as those two sentences spoken by Kress.
And for those of us who are obsessive about the company and its stock, Investing.com has the fix, August 26:
NVIDIA said fiscal second-quarter revenue more than doubled from a
year earlier to $96.2 billion and adjusted earnings topped Wall Street
expectations, underscoring how the company remains at the center of the
global AI spending boom. The chip maker reported adjusted earnings of
$2.22 a share, above the $2.08 forecast, and said revenue exceeded the
$91.9 billion consensus. Shares rose 3.98% after hours to $218, after
closing the regular session at $209.66, down 1.59%.
Key Takeaways
Revenue rose to a record $96.2 billion, more than doubling from a year earlier.
Adjusted EPS of $2.22 beat expectations by 6.73%.
Data center revenue reached $89 billion, or 92.7% of total sales.
NVIDIA said demand is broadening beyond hyperscalers to sovereign AI, NeoClouds and enterprises.
The company guided for $108 billion in revenue in the current quarter, above the latest consensus.
Company Performance
NVIDIA’s latest quarter showed that the AI infrastructure build-out
remains in full force. Revenue growth accelerated for a fourth straight
quarter, driven mainly by data center demand. The company said data
center sales rose 18% from the previous quarter to $89 billion, with
hyperscale revenue at $49 billion and its ACIE business — which includes
sovereign AI, regional cloud providers and enterprises — at $40
billion.
The results reinforce NVIDIA’s position as the dominant supplier of
AI computing systems. Management said the company’s architecture now
supports the full AI life cycle, from data preparation and training to
post-training and agentic inference. That broadening use case has helped
NVIDIA expand beyond the original wave of large cloud customers into a
wider customer base.
Gross margin remained 75%, but management warned that margins are
likely to come under pressure in the near term because of memory
pricing. Even so, the company said demand remains stronger than supply
and that its products are fully utilized across every cloud it serves.
Financial Highlights
Revenue: $96.2 billion, more than double year over year.
Adjusted EPS: $2.22, up from a forecast of $2.08.
Data center revenue: $89 billion, up 18% sequentially.
Hyperscale revenue: $49 billion, up 13% sequentially.
ACIE revenue: $40 billion, up 25% sequentially and 138% year over year.
Gross margin: 75%, unchanged from the prior quarter.
Return on equity: 114%, reflecting exceptional profitability.
Market capitalization: $5.08 trillion, maintaining its position as one of the world’s most valuable companies.
Operating expenses: up 10% on a GAAP basis and 11% on a non-GAAP basis sequentially.
Inventory: $32 billion, higher as the company prepares for the Vera Rubin launch.
Days sales outstanding: 60 days, reflecting longer payment terms for large investment-grade customers.
Shareholder returns: $26 billion, including $20 billion in buybacks and $6 billion in dividends.
Earnings vs. Forecast
NVIDIA beat expectations on both earnings and revenue. Adjusted EPS
of $2.22 came in $0.14 above the $2.08 forecast, a surprise of 6.73%.
Revenue of $96.2 billion beat the $91.9 billion estimate by $4.3
billion, or 4.68%.
The size of the beat was solid, though not unusual for NVIDIA in the
current AI cycle. Investors have come to expect strong outperformance
from the company, so the market reaction likely reflected not only the
beat itself but also the strength of the outlook and the continued scale
of demand. The revenue beat was larger in dollar terms than the EPS
surprise, which suggests that sales momentum remains the main story.
Market Reaction
The stock moved higher in after-hours trading, rising 3.98% to $218,
or $8.34 above the regular-session close. The shares had finished the
day at $209.66, down 1.59% from the previous close of $213.05, so the
post-earnings move reversed part of that decline.
At $218, the stock traded near the upper end of its 52-week range of
$164.07 to $236.54. The reaction was positive, but not extreme, which
may reflect the market’s view that NVIDIA’s results were strong but
broadly in line with the company’s powerful recent run. No unusual
trading volume data was provided.
Outlook & Guidance
NVIDIA said it expects fiscal third-quarter revenue of $108 billion,
plus or minus 2%, which implies a range of about $106 billion to $110
billion. The company also guided for gross margins of 74%, plus or minus
50 basis points, and operating expenses of $9.2 billion on a GAAP basis
and $9.0 billion on a non-GAAP basis.
Management said Vera Rubin shipments began in August and that the new
platform is already seeing purchase orders from major hyperscalers, AI
cloud providers and system makers. The company said Vera Rubin should
account for about 20% of data center revenue in the current quarter.
Looking further ahead, NVIDIA said revenue growth in fiscal 2028
should be about 70%, though management stressed that demand would be
higher if supply were not constrained. The company also said CPU revenue
is expected to more than double in fiscal 2028. InvestingPro
Tips highlight that 10 analysts have revised their earnings upwards for
the upcoming period, reinforcing the bullish outlook. For investors
seeking deeper insights, NVIDIA is one of 1,400+ US equities covered by
comprehensive Pro Research Reports, which transform complex Wall Street
data into clear, actionable intelligence through intuitive visuals and
expert analysis.
Executive Commentary
Chief Executive Jensen Huang said the company is seeing a shift
toward agentic AI, which he said requires far more computing power than
human-driven use. “The amount of compute necessary for an agent versus a
human using it is probably 15 to 100 times,” he said.
Huang also argued that NVIDIA’s advantage comes from offering a
full-stack platform rather than just chips. “We are the only company in
the world that creates and builds, offers an entire AI factory platform,
a full stack system,” he said.
Chief Financial Officer Colette Kress said the company’s business is
broadening across customer groups. “Non-hyperscaler growth, our ACIE
segment spanning sovereign regional NeoClouds, enterprise edge, and air
gap data centers will represent roughly half of our data center
business,” she said.
Risks and Challenges
Margin pressure: NVIDIA said memory scarcity is pushing costs higher and could weigh on gross margins in coming quarters.
Supply
limits: Management said demand exceeds supply, which means the company
may not be able to capture all available demand immediately.
China
exposure: The company said it did not include China data center compute
revenue in forward guidance because of geopolitical uncertainty.
Heavy customer concentration: Hyperscalers remain a large share of the business, even as the customer mix broadens.
Execution risk on new products: Vera Rubin is only beginning to ramp, and any delay could affect growth expectations.
Q&A
Analysts focused on three main issues: the sustainability of 70%
growth, the scale of future demand from agentic AI, and the impact of
open-source models and custom chips.
Questions also centered on supply-chain bottlenecks, especially
memory, power and data-center capacity. Huang said the company has
supply for 70% growth but that demand is much higher. He added that the
entire supply chain is under strain and that NVIDIA is working closely
with suppliers to add capacity.
Another theme was competition from custom chips developed by major AI
labs. Huang said NVIDIA is not just selling chips, but a full platform
that can run across clouds and workloads worldwide. He said the company
expects to remain a long-term partner to those customers.
Analysts also asked about open-source models. Huang said both open
and closed models are growing quickly and that nearly all open models
run on NVIDIA’s platform. He said the rise of open models is not a
threat, but another source of demand.
Full transcript - NVIDIA Corporation (NVDA) Q2 2027....
***boilerplate***
....Colette Kress, Executive Vice President and Chief Financial Officer, NVIDIA:
Thanks, Toshiya. We delivered another outstanding quarter with record
revenue, operating income, and EPS. Total revenue of $96 billion more
than doubled year-over-year as growth accelerated for the fourth
consecutive quarter. The surge in AI demand is driving a global
infrastructure build-out, supported by an expanding and diverse set of
growth opportunities, spanning hyperscalers, AI labs, AI natives,
enterprises, and sovereign customers. We expect to grow revenue by
approximately 70% in fiscal 2028. This is a supply-constrained outlook.
Q2 data center revenue increased 18% quarter-over-quarter to $89
billion, with strong contributions from both sub-segments, hyperscale
and ACIE, which includes our NeoCloud, industrial, and enterprise
customers. Hyperscale revenue of $49 billion grew 13% sequentially,
driven by sustained strength in Blackwell.
Reinforcing that more compute drives more revenue as new GPU capacity
comes online, our hyperscale customers delivered strong financial
results in the quarter, with accelerating revenue growth and expanding
margins. With cloud industry backlog now greater than $2 trillion, CapEx
by the top five hyperscalers is expected to reach nearly $800 billion
in 2026 and $1.3 trillion in 2027. Today, we are delighted to announce
an expansion of our partnership with AWS. Building on its already vast
installed base of NVIDIA Compute, AWS is deploying an additional 2
million GPUs starting this quarter through the second quarter of fiscal
2029, along with Vera CPUs, some integrated with Rubin, others
standalone. AWS will serve NVIDIA Nemotron family of open models on
Amazon Bedrock and SageMaker. Amazon will also adopt our full physical
AI stack, Omniverse, Cosmos, Isaac, and Jetson to power its fleet of
warehouse robots.
ACIE revenue of $40 billion increased 25% sequentially and 138%
year-over-year. Growth was driven by NeoCloud capacity additions to meet
the rising demand from enterprises, AI startups, and sovereigns, as
well as hyperscalers purchasing capacity to supplement their own
build-outs. Using NVIDIA DSX reference designs, our NeoCloud partners
are bringing capacity online faster and at lower token cost. They are
expected to exit the year with 8 gigawatts in total installed capacity,
up from approximately 3 gigawatts at the end of 2025. Incredibly, we are
seeing demand acceleration even at our scale. Customers’ forecasts
point to our growth doubling next year. However, as I mentioned earlier,
we expect to grow approximately 70% as we are supply-constrained.
NVIDIA Compute is fully utilized across every cloud we serve. The
economic value it generates for our hyperscale, NeoCloud, and AI lab
partners keeps rising.
Besides building the best AI computing technologies and the most
capable supply chain, NVIDIA has three unique capabilities that are
engines powering our growth. First, NVIDIA’s architecture runs every
model, and we’re growing share as closed and open model adoption grow.
Closed and open models alike, adoption is skyrocketing. NVIDIA runs the
leading closed models, OpenAI, Anthropic, Groq, Meta, Gemini, and the
leading open models, Thinking Machines Lab, Mistral AI, Qwen, Kimi, GLM,
DeepSeek, MiniMax, and Nemotron. We’re great at small models and giant
ones, large or video, auto, regressive or diffusion, in the cloud or in
the edge. NVIDIA is great at training, great at inference, great at
agentic workloads. One platform, fungible for every model and workload.
Durable for the entire life cycle of AI. That combination of
performance, fungibility, and durability is what makes NVIDIA the
productive and financiable compute infrastructure.
Our second unique capability is our full stack AI factory platform
that is expanding our share of the data center TAM. Since Hopper, our
revenue opportunity has grown from roughly $18 billion per gigawatt to
$25 billion with Blackwell, to $40 billion with Vera Rubin, which now
spans Vera CPU, Rubin GPU, NVLink, InfiniBand or Ethernet, and Groq LPU,
announced earlier this week. Our ability to extreme co-design across
GPU, CPU, NVLink scale-up networking, scale-out networking, systems,
algorithms, and software enables us to deliver X factor performance gain
every generation. Vera Rubin exemplifies this, delivering 30x higher
throughput per megawatt and 35x lower token cost relative to Grace
Blackwell Ultra. We commenced production shipments of Vera Rubin earlier
this month. Having already received purchase orders from every major
hyperscaler, AI cloud, and system OEM, we expect Vera Rubin to mark the
fastest product ramp in NVIDIA’s history.
Our networking business had another record quarter, with revenue
growing 18% on a sequential basis. Spectrum-X Ethernet, which grew 2.6x
on a year-over-year basis, is already helping us become the largest and
fastest-growing network company in the world. Rising adoption of agentic
AI is driving an acceleration in demand for data center CPUs. Our Grace
CPU, introduced in 2021, has been a great success, with revenue on a
trailing 12-month basis exceeding $5 billion. Today, we are in full
production of our next generation Vera CPU. As a standalone product,
Vera expands our TAM even further. Vera completes agentic tasks 1.8x
faster on the spec benchmark and provides five times the bandwidth per
watt than any other data center CPU.
We expect Vera to be deployed by every major hyperscaler, NeoCloud, AI
lab, and system OEM, with shipments already underway to our lead
partners, including Oracle Cloud Infrastructure, SpaceX AI, and starting
this quarter, AWS. We continue to see demand for approximately $20
billion in total server CPUs. Based on our customer demand and improving
supply outlook, our preliminary expectation is for CPU revenue to more
than double in fiscal 2028, positioning us as one of the world’s leading
server CPU suppliers. Since the announcement of our Groq partnership
last year, we’ve been working to unite NVIDIA’s high throughput and
Groq’s high interactivity architectures. At Hot Chips earlier this week,
we announced that Groq 3 LPX, our first rack-scale LPU system, is in
full production and already setting records, demonstrating nearly 4x the
number of tokens per second against the next best alternative on our
Artificial Analysis benchmark....
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....
Samsung Electronics is in active talks to take an equity stake in Mistral AI as part of the French startup's €3 billion fundraising round targeting a €20 billion valuation. The move would shift Samsung from chip supplier to strategic investor, coming days after Microsoft announced a separate multibillion-dollar infrastructure deal with Mistral
Samsung is reportedly negotiating a much deeper bet on Mistral
AI, and the logic is plain: memory suppliers don't want to wait outside
the room while Europe's biggest AI startup decides what hardware it
needs next.
The Financial Times reported on July 22 that Samsung is in talks to
invest hundreds of millions of euros in Mistral AI as part of a funding
round that could value the French company at about €20 billion. One
person cited by the FT said Samsung could put in roughly €1 billion.
That is not a small venture check. It is Samsung trying to buy influence
in the part of the AI market where chip supply, model ambition and
national politics now meet.
You can see why the talks have substance. Mistral CEO Arthur Mensch
visited Samsung's Hwaseong semiconductor campus in Gyeonggi Province on
April 2 during French President Emmanuel Macron's state visit to South
Korea. The Korea Times, citing Yonhap, reported that Mensch met Jeon
Young-hyun, the head of Samsung's device solutions division, to discuss
possible cooperation on AI memory, chip supply chains and related
technologies. Samsung Venture Investment Corporation had already joined
Mistral's June 2024 Series B, the round that valued the startup at about
$6 billion. This relationship didn't appear from nowhere.
Samsung wants more than a customer What's changed is the size of the bill. Mistral confirmed in September 2025 that ASML led a €1.7 billion Series C at an €11.7 billion post-money valuation. The FT now says the company is seeking a new round around €20 billion. That would be a sharp step up in less than a year, but not a mysterious one. Mistral is no longer only releasing open-weight models and selling API access. It is building compute....
When your company (Mistral) is not just the national standard-bearer but the flagship for the whole continent it's amazing how many companies come knocking on your door.
From the Wall Street Journal, July 21:
Microsoft
and Mistral AI expanded their artificial intelligence partnership on
Tuesday, with a multibillion-dollar commitment from Microsoft to help
the French AI company build data centers in Europe.
The
deal is the latest attempt by both companies to reach a greater number
of European and enterprise AI clients, as the two go up against rival AI
labs and other U.S. tech giants.
“Distribution is king,” said Mistral Chief Executive and Co-founder Arthur Mensch, adding that Microsoft’s heft would facilitate the AI company’s expansion with businesses in Europe and across the world.
Mistral has touted the importance of Europe’s independence
from U.S. technology companies. At the same time, it has been ramping
up its push for enterprise clients—an area where U.S. behemoth Microsoft
offers immense reach.
For Microsoft, working with Mistral is part of the European digital commitments it made last year,
in which it pledged to increase data-center capacity in the European
Union. Its latest move comes as the European Commission, the EU’s
executive arm, is considering classifying
Microsoft’s Azure cloud platform as a gatekeeper under the bloc’s
Digital Markets Act—a designation that requires companies to take extra
steps to ensure they aren’t stifling competition.
“Our partnership with Mistral is becoming a core pillar of our broader European efforts,” Brad Smith,
Microsoft’s vice chair and president, said in an interview. “This is a
moment when European customers are especially focused on resilient
supply of AI.”
The partnership includes a “multibillion-dollar” agreement from Microsoft—which it declined to specify—to support Mistral’s data center build-out
in Europe. As the company builds a “GPU fleet” in Europe, some of those
AI chips will be used by Microsoft to serve its customers, said Mensch,
referring to the data centers that house graphics processing units.
Microsoft
expects to “get a return” when customers use its cloud platform Azure,
said Smith, while Mistral will “get a return” when customers use its AI
models.
Also
as part of the deal, two of Mistral’s top AI models—Medium 3.5 and OCR
4—will be available in Microsoft’s products, including Microsoft Foundry
and Microsoft Copilot Studio. Mistral’s models will additionally be
available on Azure Local, a Microsoft infrastructure offering that lets
customers run their information-technology systems in the cloud or their
own data centers. Smith said that option would allow customers to be
“disconnected” from the cloud.
“This
responds to what we’re hearing from customers and the market,” Smith
said. “There is a heightened need for customers to have more choice and
more control, and that’s what this gives them.”
This isn’t Microsoft’s first investment in Mistral. The two companies, which began working together in 2023,
are targeting a similar segment of European and global business
customers that are in regulated sectors such as financial services,
manufacturing and healthcare....
Total of 900 applications including ERP, CRM, and manufacturing systems going to be kept 'under European control'
Airbus is migrating its most critical applications for sensitive
workloads from AWS to French cloud provider Scaleway's under a drive to
increase digital sovereignty.
As exclusively revealed by The Register
in December, the European-based aerospace manufacturer, said it needed
to guarantee the data remained “under European control" and was
launching a tender at the start of 2026.
Catherine Jestin, head
of digital at Airbus, told us on Thursday: "The selection of Scaleway is
a combination of a very strong technical answer and a very strong
commercial offer making it competitive compared to hyperscalers' public
cloud offerings. In addition, Scaleway is committed to involving Airbus
in the definition of its future product roadmap."
"The objective is to host Airbus's most critical applications (those
required for the Minimum Viable Company). This represents 900
applications and we will start with 70 of them today hosted on AWS."
Applications
being sent to Scaleway include ERP, manufacturing execution systems,
CRM, and product lifecycle management. Finding a cloud provider to host
its most sensitive applications for defense and industrial workloads was
not a certainty when the process began, Airbus told us last year,
because European cloud providers do not have the scale of their US
rivals.
Jestin said Airbus will continue to work with AWS.
Skywise, a platform that aggregates and analyzes aviation data, and Case
Management Assistant for customers' technical queries will continue to
be hosted by AWS.
In a statement, she said: “By integrating a
trusted, high performance, cloud environment that keeps our critical
data assets shielded from foreign extraterritorial laws, we are ensuring
that our digital infrastructure keeps pace with our aerospace
innovation, while maintaining control and resilience of our industrial
operations.”
This
has heightened concern about the US Cloud Act, which allows the
American government to request data held in overseas datacenters owned
by US businesses, and only served to reinforce calls for digital
sovereignty....
AI to See ‘Major Second Wave,’ NVIDIA CEO Says in Fireside Chat With iliad Group Exec NVIDIA’s
Jensen Huang says sovereign AI a growing need for countries to reflect
unique cultural, linguistic, industrial characteristics European
startups will get a massive boost from a new generation of AI
infrastructure, NVIDIA founder and CEO Jensen Huang said Friday in a
fireside chat with iliad Group Deputy CEO Aude Durand — and it’s coming
just in time.
.... This is terrible. I now have Jensen Huang speaking in Dr. Martin
Luther King's cadences as he repurposes the penultimate paragraph of "I have a Dream":
Let AI ring from Stone Mountain of Georgia. Let AI ring from Lookout Mountain of Tennessee. Let AI ring from every hill and molehill of Mississippi. From every mountainside, let AI ring.
Palantir's Alex Karp and Mistral's Arthur Mensch are making the same case from different angles: Don't let closed AI providers control your data and deployment.
Palantir CEO Alex Karp went on CNBC’s Squawk Box last
week to discuss a new partnership with Nvidia to deploy open-weight AI
models in sovereign government environments. But viewers got a nearly
20-minute broadside against the entire frontier AI model industry,
calling it “effing insane” and accusing companies like OpenAI and
Anthropic of overcharging enterprises while harvesting their proprietary
data.
Days later, Mistral CEO Arthur Mensch made a strikingly similar case on LinkedIn,
warning that closed AI providers are gaining “immense leverage” over
enterprise customers as organizations connect proprietary workflows to
hosted models. He suggests open-weight models, open data systems, and
enterprises building their own training flywheels.
The two executives are approaching this from opposite ends of the
market, yet their convergence on the same message within the same week
underscores architectural control.
Two pitches, one argument Karp runs a company that sells an application and ontology layer designed to sit between enterprises and the models. The Palantir-Nvidia deal pairs Nvidia’s open Nemotron models with Palantir’s Sovereign AI Operating System, built on AIP, Foundry, Ontology, and Apollo, enabling government agencies and critical infrastructure operators to deploy, fine-tune, and audit AI models within their own air-gapped environments.
When CNBC’s Becky Quick told Karp he sounded angry, he pushed back,
saying, “This is the voice of American business that is being channeled
through me,” and urged the panelists to call any CEO privately to
verify....
Not exactly Churchill and the British Lion's roar but you take what you get.
The humble and lovable Winston addressing the houses of Parliament that had gathered to honor his eightieth birthday:
‘I was very glad that Mr Attlee described my speeches in the war as expressing the will not only of Parliament but of the whole nation. Their will was resolute and remorseless and, as it proved, unconquerable. It fell to me to express it, and if I found the right words you must remember that I have always earned my living by my pen and by my tongue. It was a nation and race dwelling all round the globe that had the lion heart. I had the luck to be called upon to give the roar.’
Abu Dhabi’s MGX Weighs DayOne Buyout as GDS Spin-Off Pursues $20B IPO
Artificial intelligence investor MGX is exploring a
multibillion-dollar acquisition of data centre operator DayOne,
according to a media report, in a potential twist for the
Singapore-based operator after the overseas spin-off of China’s GDS
Holdings had appeared headed for a $20 billion public listing.
Abu Dhabi-owned MGX is working with an investment bank in preparation for a potential transaction, Reuters said Friday, citing sources familiar with the matter. The deal would mark the firm’s first Asia acquisition if it proceeds.
DayOne has been preparing for a US initial public offering targeting a
valuation of $20 billion, though Reuters reported that MGX may not be
willing to match that price. The takeover chatter comes two weeks after
DayOne closed a $4.5 billion Series C equity round led by existing investors Coatue Management and Hillhouse Investment.
“The sources cautioned that a deal may not proceed and that the firm may still opt to pursue an IPO,” the news agency said.
Potential Pivot DayOne’s final Series C close more than doubled the size of the fundraising from its initial close in January, with new investors including the Indonesia Investment Authority and Achi Capital Partners joining the pre-IPO round.
The June fundraising brought total equity secured by DayOne since its
2022 inception to around $6.4 billion, according to Mingtiandi
calculations. The company said the capital would support expansion in
Singapore, Malaysia, Indonesia, Thailand, Japan, Hong Kong, Finland and
Spain.
DayOne had selected JP Morgan, Morgan Stanley, Bank of America and Citigroup to work on the planned US listing, which Bloomberg reported in February could raise as much as $5 billion. The operator was also said to be considering a dual listing in the US and Singapore.
DayOne Data Centers was established in 2022 as the overseas arm of Shanghai-based GDS under the GDS International name before rebranding in January 2025.
Analysts described the relaunch as a move to distance the platform from
its Chinese parent amid geopolitical tensions and position it for a
public listing.
GDS founder William Huang stepped down as executive chairman of
DayOne in April, with former Olam Group chairman Lim Ah Doo now serving
as non-executive chairman after having been named co-chairman during the
rebrand.
GDS has been paring its exposure to DayOne. The mainland data centre
giant held 19.9 percent of the platform as of late April after DayOne repurchased $385 million in ordinary shares
from its former parent at the Series C new issue price. Originally, it
wholly owned the company, reducing its stake to 52.7 percent at the
Series A funding, then to 35.6 percent at the Series B.
DayOne said earlier this month that it had secured more than 1.5
gigawatts of total bookings across Asia Pacific and Europe, up from
around 1GW of customer commitments reported at the initial close of the
Series C in January.
Gulf AI Push MGX was established in March 2024 with Abu Dhabi sovereign fund Mubadala Investment Company and Abu Dhabi-based tech firm G42 as foundational partners, with a mandate to invest across AI infrastructure, semiconductors and AI-enabled technologies.
The firm is chaired by Tahnoon bin Zayed Al-Nahyan, deputy ruler of
Abu Dhabi and national security advisor of the United Arab Emirates.
Tahnoon, a brother of UAE President Mohamed bin Zayed Al-Nahyan, also
chairs the Abu Dhabi Investment Authority, the emirate’s trillion-dollar
sovereign fund....
Probably the reason OpenAI's Sam Altman was in the UAE talking about raising $7 trillion for chips and cheese or something. A big ask in anybody's book.
Here's
hoping it doesn't become another SoftBank Vision Fund which was the
same $100 billion size and for the first few years of its life mainly
succeeded in jacking up the price of speculative private investments
before roller-coastering into a profitable position this year.
Abu Dhabi had a hand in that one and went on one heck of a ride with Mr. Son....
Euronews will be at the tech conference, which is now in its 10th edition.
Paris officially opens its doors to the tech elite and striving startups as the VivaTech conference kicks off on Wednesday.
From Jeff Bezos and Yann LeCun making appearances to artificial
intelligence and tech sovereignty being high on the agenda, here is
everything to watch out for at the 2026 edition.
10-year anniversary VivaTech this year is making a big deal of turning 10, with a free event open to all on Sunday that turned the Champs-Élysées into a walkway of robots, the mobility of the future and all types of innovation.
The public event is not the only one as Saturday, 20 June, is also
dedicated to the general public to explore the exhibition space.
To mark the anniversary, VivaTech also changed its name, which was previously Viva Technology.
The organisers say the name change reflects that, over the past 10
years, the event has become “much more than just a gathering: a true
“VivaTech Generation” has emerged, a global community of entrepreneurs,
startups, investors, thought leaders, countries and students, all united
by a shared desire to innovate, collaborate and build the world of
tomorrow”.
Key speakers Some of the biggest names in technology and business will be attending, including the Co-CEO of Prometheus, Jeff Bezos, one of the so–called godfathers of AI, Yann LeCun, Mistral AI CEO Arthur Mensch, OpenClaw founder Peter Steinberger, and LVMH boss Bernard Arnault.
There will also be a slew of politicians, including French President
Emmanuel Macron, Germany’s digital minister Karsten Wildberger, India’s
Prime Minister Narendra Modi and the European Commission’s tech
executive Henna Virkkunen....
Tech sovereignty dominates G7 and VivaTech discussions as Europe confronts U.S. AI dominance
U.S. export controls on advanced AI models underscore European vulnerability to foreign policy shifts
European AI firms remain dependent on U.S. cloud infrastructure, chips, and models
Europe's
quest for technological sovereignty will dominate discussions at the
G7 in France and the VivaTech conference in Paris this week, as
policymakers and technology executives fret about American AI, with
alternatives remaining scarce.
The gatherings come days after the United States tightened restrictions
on Anthropic's most advanced AI models for foreign nationals,
underscoring Europe's vulnerability that political whims could derail
its race to build domestic AI champions.
"Tech sovereignty will be top of mind this week at VivaTech," Ana Paula Assis, senior vice president at IBM told Reuters.
"For
European organisations to get this right, it is vital to understand
sovereignty is about having control where it matters — not where the
technology is from."
The
debate reflects a broader dilemma facing Europe: how to maintain
strategic autonomy while remaining dependent on American technology
companies that dominate cloud computing, semiconductor design, and
cutting-edge AI research.
The Group of Seven (G7) nations have gathered in Evian, France, where they are meeting top executives
from the biggest AI companies including Anthropic, OpenAI, Alphabet's
Google, and Mistral to discuss AI competitiveness, regulation, and reliance on China for critical minerals.
In Paris, over 180,000 visitors, startups, investors, policymakers and executives including Amazon's
Jeff
Bezos are expected to attend VivaTech, where discussions are likely to
focus as much on geopolitics and policy as on the actual tech.
French startup Mistral, seen as Europe's leading AI contender, is doubling down on partnerships with European firms, particularly in industries where the region says it has an edge.
Despite
billions of euros of investment, European AI firms continue to rely
heavily on U.S.-controlled cloud infrastructure, chips, and foundational
AI models....
