🚨UN researchers say data centers could double power and water consumption by 2030 as AI demand accelerates.

The numbers are huge:

2024 electricity use: 448 TWh
2030 projection: 945 TWh

2024 water use: 4.5 trillion liters
2030 projection: 9.3 trillion liters

QuantMind turns every paper, news article, SEC filing, and blog post in quant finance into a queryable knowledge graph.

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🎞️ DGX Spark Super Gallery at Computex. Product breakdown 👇

Before the RTX Spark there was the DGX Spark. Not to confuse the two, one runs Windows and the other Linux. Here is a breakdown of the GB10 mini-desktops.

1. NVIDIA DGX Spark (Founders Edition)
🖤 NVIDIA Official
💰 $4,699
🧠 GB10 Grace Blackwell Superchip
💾 128GB Unified LPDDR5X
📀 4TB NVMe SSD (self-encrypting)
⚡ 1 PFLOP FP4 AI Performance
Perfect for local 200B parameter models. 🔥

2. MSI DGX Spark
💰 ~$4,599–$4,699
🧠 GB10 Superchip
💾 128GB Unified Memory
📀 4TB NVMe SSD
Compact & premium design with strong cooling. Great for developers. ⚙️

3. ASUS DGX Spark
💰 ~$3,999–$4,699
🧠 GB10 Grace Blackwell
💾 128GB LPDDR5X Unified
📀 4TB Storage
Excellent build quality and connectivity. Popular with creators. 💻

4. Acer Veriton GN100 DGX Spark
💰 ~$4,100
🧠 GB10 Grace Blackwell Superchip
💾 128GB Unified LPDDR5X
📀 4TB NVMe SSD
Strong thermal performance in a compact chassis. Excellent value option. 🟢

5. Gigabyte AI TOP ATOM DGX Spark
💰 ~$4,699
🧠 GB10 Superchip
💾 128GB Unified Memory
📀 4TB NVMe SSD + ConnectX-7 SmartNIC
Often praised for best-in-class performance and cooling. ⚡

6. HP DGX Spark
💰 ~$6,000–$6,599
🧠 GB10 Superchip
💾 128GB Unified Memory
📀 4TB NVMe
Enterprise-grade reliability with HP’s signature design. 🏢

7. Lenovo ThinkStation DGX Spark
💰 ~$6,000
🧠 GB10 Grace Blackwell
💾 128GB Unified RAM
📀 4TB Storage
Built for professional workstations and heavy AI workloads. 💼

8. Dell Pro Max DGX Spark
💰 ~$6,300 (config dependent)
🧠 GB10 Superchip
💾 128GB LPDDR5X
📀 4TB NVMe SSD
Strong enterprise integration and support. Ideal for businesses. 🏭

WHICHLLM scans your hardware and ranks the best local models from HuggingFace that will actually run on your system.

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⏰ Oh yeah super excited about this! 🚀 A new local 12B dense model from Google! You have to try this out.

💥 Google just dropped Gemma 4 12B → a powerful multimodal open model that actually runs well on laptops (and cards).

Run on 👉 ✦ RTX-4070 TI ✦ RTX-5060 TI ✦ RTX-5070 TI ✦ RTX-5080

Key Highlights:
🧠 Encoder-free architecture (35M projector + native LLM handling)
💻 Runs smoothly on 16GB VRAM / unified memory machines
📸 Strong vision + audio understanding
⚡ Excellent reasoning performance for its size
✅ Fully open source (Apache 2.0)

🔥 Finally, a capable multimodal model you can actually run locally without a datacenter. This changes the game for on-device agents.

💪Wow! New open source Computer Use model shows strong local performance on 📊 LLM Leaderboard using a single DGX Spark!

This model can handle your agents 💻 Computer Use workload fast!

🆕 Holo-3.1-35B-A3B-NVFP4 (vLLM + NVFP4)

» 101 tokens/sec at low concurrency
» Scales up to ~195 tokens/sec at higher concurrency (c10)

🎯 A 35B-class model delivering nearly 200 tokens per second on a single DGX Spark node for 💻 Computer Use is impressive. Great efficiency for a local agentic model. 🔥

🤔 how Mac/StrixHalo/RTX Card would do?

spark-arena.com/benchmark/2bf2209e-0827-4de6-9df9-8ad70ae1b618

🚨Copper just hit $14,000/ton

Goldman, Citi and HSBC all published bullish notes today.

And Codelco, the world's largest copper producer, just fired its CEO over inflated production figures.

The supply crisis just got a leadership crisis on top. ⛏️

3 things happened simultaneously today that every copper investor needs to understand:

1️⃣The banks officially joined the trade:

→ Goldman Sachs: lifted end-2026 target +10% to $13,735 cut global mine supply estimates by 350,000 tons

→ Citi: $14,500 this month. $15,000 within a year.

→ HSBC: overlaid the Hormuz "super-squeeze" thesis on top of the structural deficit

Ex-US copper deficit projected to balloon 10x to 640,000 tons. 💰

2️⃣The supply problem is structural:

→ Grasberg (world's 2nd copper mine): still recovering from September 2025 underground flood. Force majeure still active. Full capacity: not before 2028.

→ Kamoa-Kakula: cut 2026 guidance by 22% after seismic disruption. Same timeline.

2 of the world's most important copper mines simultaneously impaired for multiple years.

On the demand side: nothing has softened.

Grid expansion, EVs, AI data centers, defence all absorbing copper faster than the market can supply⚡

3️⃣CODELCO – Corporación Nacional del Cobre de Chile the world's largest copper producer just changed CEO:

Jorge Gomez named to replace Rubén Alvarado who exits amid a scandal over inflated production figures.

This is Chile's state copper giant.

397,000 tonnes in Q4 2025.

Second only to BHP globally.

When the world's largest copper producer has a production credibility problem in the middle of a structural supply squeeze that is is signal. 🌍

Alphabet is about to do the largest equity sale in history.
Bigger than SpaceX's IPO.

Bigger than Petrobras in 2010.
Nearly 3x Aramco's 2019 IPO.

$80 billion, in a single equity raise.

The previous record holders were both oil companies at the peak of their cycles.

🇧🇷Petrobras in 2010: $65 billion to drill the pre salt ultra deepwater fields off Brazil the biggest oil discovery in decades. The market couldn't get enough.

🇸🇦Aramco in 2019: $25 billion to monetise the world's largest oil reserve. The most profitable company on earth going public. Still the largest IPO ever at the time.
Both were energy. Both were oil. Both represented the dominant capital deployment thesis of their era.

Now Alphabet an AI company, is about to raise more than both combined.
Not to drill. Not to pump. To build compute.

The capital cycle has rotated completely.

2010s: the world's largest equity raises funded oil megaprojects deepwater, pre-salt, sovereign oil reserves.

2026: the world's largest equity raises fund AI infrastructure data centers, GPUs, power.

🚨Private data center construction just crossed public transportation infrastructure.

$50 billion.

It took roads and bridges 20 years.

Data centers did it in 2.

$50 billion in construction per year needs electrons.

The grid took the same 20 years to build its current capacity.

It cannot absorb a vertical demand curve on a 2 year timeline.

Grid interconnects: 5-7 year queue.

Data center construction: vertical.

That gap is where the private gas turbine market lives.

Hyperscalers aren't waiting for the grid.

They're building behind the meter mobile turbines on site in 12-18 months.

The binding constraint isn't capital.

It is gas & It's turbines.

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Broadcom is extremely undervalued and two things just happened today that make the case impossible to ignore (Save this).

Broadcom reports earnings tonight and Google just raised $85 billion to pour directly into the infrastructure Broadcom builds.

Sundar Pichai announced this morning that Alphabet's equity offering was oversubscribed and upsized from $80 billion to $84.75 billion in 48 hours.

Berkshire Hathaway put in $10 billion directly.

The stated purpose is to fund AI compute infrastructure because demand from enterprises and consumers is already exceeding available supply.

Google Cloud just posted $20 billion in quarterly revenue up 63% year over year, the fastest growth since the segment began reporting separately.

Enterprise AI solutions grew 800% in the same quarter and the backlog nearly doubled quarter over quarter to $462 billion in signed customer commitments.

Every dollar of that $462 billion backlog requires physical infrastructure to deliver, TPUs, networking silicon, custom accelerators and the design and supply chain for all of it runs through Broadcom.

Sundar Pichai just raised $85 billion to pour into the exact infrastructure Broadcom builds and services through 2031 under contract.

Now here is why Broadcom specifically is the cleanest expression of this trade.

Broadcom does not sell merchant silicon into a commoditizing market but rather it co designs proprietary custom accelerators, XPUs directly with hyperscalers who cannot source these chips anywhere else.

And their customer list reads like a directory of the most consequential AI companies on earth, Google, Meta, Anthropic, OpenAI, Fujitsu, ByteDance.

Google locked in Broadcom through 2031 for TPU design and supply and then immediately raised $85 billion to accelerate spending under that same contract.

Anthropic is receiving 1 gigawatt of TPU capacity this year, scaling to 3 gigawatts in 2027 and OpenAI's first custom XPU ships in 2027 with over 1 gigawatt of committed capacity.

The networking side of the business is just as important and even more overlooked.

AI networking revenue grew 60% year over year last quarter and represents a third of total AI revenue.

Broadcom's Tomahawk 6 switch and 200G SerDes components are the connective tissue inside every hyperscaler's GPU cluster and the order backlog for AI switches alone exceeds $10 billion.

Now here is the earnings setup for tonight.

Analysts are expecting $22 billion in revenue, 47% year over year growth and $10.7 billion in AI chip revenue alone, up 140% from a year ago.

Tonight's earnings are the moment the market catches up to what the balance sheet already knows.

Uber's CEO said it himself that they blew through their entire 2026 AI budget in a single quarter (Save this).

And today they cut 23% of the people who used to do what AI now does.

These two facts are not separate stories but rather the same story.

Earlier this year, Dara Khosrowshahi explained exactly what was happening inside Uber's engineering org.

The company introduced Anthropic's Claude Code to engineers in late 2025, adoption reached 32% by February, 84% were classified as agentic coding users by March and by April 95% of engineers were using AI tools monthly.

Roughly 70% of committed code was AI generated and round 11% of real time backend updates were being deployed by autonomous agents with no human in the loop.

The annual AI budget was gone in four months and Dara's response was not to slow down adoption but rather to slow down hiring.

When each engineer is producing materially more output per hour, you need fewer engineers to hit the same targets.

And when AI handles the work that used to require people to hire, onboard, and manage those engineers, the HR and people operations layer beneath them, that layer contracts too.

Today's announcement is that 23% of Uber's People and Places division is gone.

Uber's spokesperson said the cuts are unrelated to AI but that framing does not hold up to the sequence of events.

IBM understood this two years ago, when 94% of typical HR questions are answered by an AI agent, the HR Business Partner role collapses for everyone except the most senior strategic functions.

The budget that used to fund that team gets reallocated to engineering and sales, the two functions that remain bottlenecked by human judgment rather than human volume.

This is the pattern that will repeat across every major enterprise over the next 18 months.

Your children are leaving on a 10-year journey.

For the next decade you live alone.

You still have to earn money cook clean stay healthy manage the house and take care of yourself.

No human help allowed.
No relatives.
No friends.
No hired workers.

You can choose only one humanoid robot:

‣ Tesla Optimus for general purpose home and factory tasks

‣ Figure AI for workplace automation and physical assistance

‣ Boston Dynamics Atlas for mobility balance and demanding movement

‣ Unitree G1 for affordable humanoid robotics and experimentation

‣ 1X NEO for home support and daily care

‣ Agility Robotics Digit for warehouse work and physical tasks

‣ Apptronik Apollo for industrial labor and productivity

‣ UBTECH Walker S1 for service tasks and personal assistance

Which humanoid robot are you trusting with your life for the next 10 years?

AmpliTech Group $AMPG - customers and partnerships

These partnerships and customers are officially confirmed by $AMPG itself.

They have a partnership with $IBM which is spending billions on quantum R&D. $AMPG is the only US manufacturer that produces Cryptogenic LNA hardware which can withstand temperatures of ~4 Kelvin (lower than -270 degrees Celcius).

They have collaborations with Lockheed Martin $LMT and Northrop Grumman $NOC. Defense is quite hard to get into as a supplier since it involves years of passing qualification stages. $AMPG has passed that and has military-grade LNAs as a US-based producer.

They have a partnership with NASA and Viasat $VSAT, as their LNA hardware is also useful for SATCOM/satellite communications equipment.

For a company that trades at merely $135 million market cap, this is quite the impressive list of partnerships and customers.

Today the EU made American AI illegal in 27 countries.

The reason is ONE sentence Microsoft's own lawyer said under oath:

This morning in Brussels, EU Tech Chief Henna Virkkunen unveiled the Cloud and AI Development Act. It's the most aggressive anti-American tech move from Europe since GDPR.

The law forces EU public sector procurement in banking, healthcare, defense, and energy to apply mandatory non-price factors favoring software and hardware built inside the EU. Microsoft Azure can be cheaper, AWS can be faster, Google Cloud can have the better model, and EU governments MUST legally prefer European alternatives.

AWS, Microsoft, and Google currently control roughly 70% of the European cloud market. Brussels is now openly targeting greater independence from US providers in cloud, AI, and semiconductors.

The largest regulatory market-share transfer in tech history is being written into law right now.

But the real story is how this happened...

On June 10, 2025, a man almost no one outside Brussels had heard of walked into the French Senate. His name is Anton Carniaux, Director of Public and Legal Affairs at Microsoft France.

Senator Dany Wattebled asked him under oath whether he could guarantee that data belonging to French citizens, stored on Microsoft European servers, would never be transmitted to US authorities without explicit consent from the French government.

Carniaux answered honestly. He admitted he could not guarantee it, because Microsoft must comply with the US CLOUD Act regardless of where European data physically sits. One sentence of sworn testimony from Microsoft's own counsel killed every sovereign cloud defense Big Tech had spent five years building.

It became the legal foundation for the law unveiled today.

Then Trump accelerated the divorce.

January 2025 brought executive orders expanding US surveillance authorities. Vance went to Munich and attacked European democracies on stage.

The tariffs followed and so did the Pentagon's $200 million AI contract war that ended with OpenAI replacing Anthropic after Hegseth labeled it a supply chain risk. So did OpenAI's Stargate and yesterday's Trump AI Executive Order, whose Section 3 lets the White House pick which AI companies get 30-day early access to frontier models. American AI was officially declared a US government strategic asset.

Europe heard every word of it.

On May 12, Mistral CEO Arthur Mensch told the French National Assembly that Europe had 24 months to build sovereign AI infrastructure or become a permanent US VASSAL state.

And the response came fast:

April 24: Cohere acquired Germany's Aleph Alpha for $20 billion with both Germany's and Canada's digital ministers in the room at the Berlin announcement. May 30: SoftBank committed up to $87 BILLION for French nuclear-powered data centers, the largest AI infrastructure project in European history.
Yesterday: EU Parliament announced it's dropping Google for French search engine Qwant tomorrow. France ordered every government workstation off Windows and onto Linux.

Today the Cloud and AI Development Act made all of it law.

- Mistral is building a 1.4 gigawatt AI campus near Paris by 2028 with Nvidia, MGX, and Bpifrance
- SAP's EU AI Cloud, launched last November, runs on Cohere, Mistral, and SAP's own sovereign infrastructure
- McKinsey forecasts $600 billion in sovereign AI needs by 2030

None of that money is going to Silicon Valley.

The America First AI policy built a wall around the world's most regulated economy, and American companies are on the wrong side of it.

Microsoft's lawyer told the truth in a Senate hearing nobody watched. Trump turned that admission into a national security narrative while the EU turned that narrative into procurement law.

And one entire continent walked away from the American tech stack...

🇺🇸 The made-in-USA "picks & shovels" micro-cap ($115M market cap) riding three revolutions at once: $AMPG.

Amplitech sells the "ears" of three secular waves at the same time, space, quantum computing, and AI-RAN $NOK $NVDA.

The market still prices it like a niche component maker.

1/ Start with the engine, because it's already turning:

FY2025 closed at ~$25M in revenue (+163% YoY) and guidance is $50M+ for 2026.

But the number that actually matters is the margin: gross margin roared to 48% in Q1 2026 (vs 33% a year earlier).

This isn't a promise, it's execution.

2/ And it's not slideware.

The LOIs are already turning into invoices:

🟢 Shipments under the $100M LOI started in December 2025

🟢 The $40M LOI with a North American operator is already contributing revenue

🟢 Contracted backlog >$20M

Total LOI pipeline: $118M.

3/ 🛰️ THE SPACE ANGLE

20 years building the LNAs (the "ears") that grab a faint satellite signal 300 miles up without adding noise.

X / Ku / Ka bands, SATCOM, defense.

All designed and manufactured in the USA → a "safe" domestic supplier exactly when space and U.S. defense demand a homegrown supply chain.

4/ ⚛️ THE QUANTUM ANGLE (the hidden ace)

Their cryogenic pHEMT LNAs run at 4 Kelvin with noise figures below 0.1 dB.

The key to the business model: each qubit typically needs its own LNA.

If quantum computing scales toward 1,000+ qubits, demand for their amplifiers scales right alongside it.

AMPG is one of the only U.S. manufacturers of cryogenic LNAs at this level, already shipping to Fortune 50 companies, universities, and research institutions.

5/ 🤖 THE AI-RAN ANGLE (the hot one)

NVIDIA and Nokia are driving AI-RAN as the next big network investment cycle.

Where does AMPG fit?

At the hardware layer: its 64T64R Massive MIMO O-RAN radio was the core hardware in the first open-source AI-RAN prototype at Northeastern University (May 2026).

It's the only American company to have commercialized an O-RAN CAT B 64T64R radio unit.

6/ And the best part: it's already cleared to sell.

FCC (US) + ISED (Canada) approved its complete 5G solution. The expensive R&D / cash-burn phase is over; now it's commercial deployment into carriers, enterprises, hospitals, and schools.

7/ 🏦 THE BALANCE SHEET

For a micro-cap, it's solid: debt-free with ~$18.4M in cash. Maxim Group keeps a "Buy" with a $7 price target.

At a ~$110–130M market cap, the market still models it as a niche component maker, not as what it's starting to become.

8/ THE THESIS IN ONE LINE

They don't need to win the satellite race, the quantum race, or the AI-RAN race.

They just need to sell the hardware to whoever does.

Three secular waves, one "picks & shovels" supplier, made in USA. 🇺🇸

$MRVL/USD H2 #Indicator #Signal #Trading #GlobalOneAI

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