Nvidia just cleared the memory bottleneck significantly for Vera Rubin by qualifying HBM4 from Samsung, SK Hynix, and Micron & moving those parts into full production.
per news, Vera Rubin HBM4 share: SK Hynix 60–70%, Samsung 25–30%, Micron rest.

American AI startups are routing far more app traffic to Chinese LLMs.

Through OpenRouter, weekly token consumption was mostly driven by U.S. models through much of 2025. But from early 2026, Chinese models suddenly became the main growth engine.

AI model market is becoming less about brand loyalty and more about raw utility.

$BB QNX appears to be pursuing a role analogous to what Linux became for the internet era: the invisible operating system beneath the infrastructure.

$NVDA signed with $BB in April.

QNX real-time OS for safety-critical edge AI, robotics, autonomous systems, and platforms like NVIDIA IGX Thor / DRIVE.

Now doosan? they are telling you Physical AI is going to be key in the next 5 years of your life.

$BB Blackberry valuation ladder:

$10B Market Cap ($17/share)
QNX turnaround proven. Software revenue growing consistently. Market stops viewing BlackBerry as a legacy turnaround story.

$25B Market Cap ($43/share)
QNX becomes a clear winner in Software Defined Vehicles. Investors begin pricing in automotive dominance rather than automotive participation.

$50B Market Cap ($85/share)
QNX expands beyond automotive into industrial automation, robotics, medical devices, and edge AI. Physical AI narrative starts gaining traction.

$100B Market Cap ($171/share)
QNX recognized as the leading safety-certified operating system for autonomous systems. Comparable to what Android became for smartphones.

$250B Market Cap ($427/share)
Robotics adoption accelerates globally. QNX becomes the default software foundation for robots, autonomous vehicles, industrial machines, and intelligent infrastructure.

$500B Market Cap ($853/share)
Physical AI becomes a major technology platform. QNX sits underneath a meaningful percentage of the world’s autonomous systems. Network effects emerge around certification, middleware, and developer ecosystem.

$1T Market Cap ($1,706/share)
QNX becomes mission-critical infrastructure for the physical world. Investors view it similarly to AWS for cloud computing or Windows during the PC era. Replacing QNX becomes economically and operationally impractical.

The progression is:

Turnaround → Automotive Leader → Physical AI Platform → Global Infrastructure.

See you guys at $1706

Who wins the AI race, USA or China?

My bet is still on the USA.

China has a massive energy advantage. Cheap, abundant power will matter more and more once AI scaling becomes limited by electricity, grids and data center buildout.

But right now, frontier AI is still mostly a compute race. Chips, clusters, capital, talent, tooling and iteration speed matter more than raw energy.

And on that board, the US is still ahead.

China will absolutely catch up in efficiency and deployment. Maybe even faster than people expect. But for the frontier model race itself, I’m still betting America.

$BB at $9.41 today.

Roadmap:

• $17/share ($10B) = +81%
• $43/share ($25B) = +357%
• $85/share ($50B) = +803%
• $171/share ($100B) = +1,717%
• $427/share ($250B) = +4,438%
• $853/share ($500B) = +8,966%
• $1,706/share ($1T) = +18,033%

Happy monday everyone 🫡

A 23-person company now runs on 1 founder and a team of AI agents that never ask for a raise.

He gave them names. Meet Nolan, head of content.

1 human types a task into a chatbot. Nolan reads it. He hands it to 1 of his 7 sub-agents to finish.

That’s the whole team.

Above Nolan sits a chief agent. The executives prompt the chief. He splits the job across every department head, then merges the answers into 1 reply.

Employees skip the chief. They talk straight to their department head by chatbot, or by voice. You can call Nolan and he answers like a person.

The onboarding doc shows 7 example use cases. A new hire is running the whole system in 1 afternoon.

No salaries. No PTO. No 1:1s. No Slack drama.

The entire company fits on 1 screen.

This is what an org chart looks like when the staff never sleep.

3 levels separate the people typing prompts from the ones who make AI work while they sleep.

Level 1 is ChatGPT. You ask, it answers. It can’t see your calendar, your inbox, your money. It waits for you. That’s 99% of people.

Level 2 is the workflow. You tell it: pull these 10 articles, summarize them, draft the post, run at 8 AM. It follows your path every day. No hands.

But it’s still dumb. Ask 1 thing off-script and it breaks. A human writes every rule.

Level 3 is the agent. The jump is 1 sentence:

You delete yourself.

The AI stops following your steps and starts choosing them. It reasons. It picks the tool. It grades its own work. It rewrites the bad draft 6 times until it’s good. While you sleep.

That’s the whole game. Workflow means you still work. Agent means the work works.

The people quietly pulling $10,000 a month online didn’t learn to code. They learned to remove themselves from the loop.

A workflow needs a boss. An agent is the boss.

🚨 NOW: Coinbase CEO Brian Armstrong predicts demand for AI is near infinite, but expects 80% of workloads to run on 99% cheaper models within 12–18 months.

He adds that energy and compute will be the limiting factor.

Evolution Toward a Multi-Planetary Civilization

Everyone is talking about AI.

Very few understand where AI is actually heading.

The future isn't chatbots.

It's Agentic AI. 🚀

Systems that can:

👀 Perceive information
🧠 Reason through problems
📋 Plan multi-step tasks
⚡ Take actions autonomously
📚 Learn from feedback
🔄 Improve over time

The evolution looks like this:
AI Models → GenAI → AI Agents → Agentic AI

And each step adds a new layer of capability:
• Memory
• Tool use
• Planning
• Orchestration
• Multi-agent collaboration
• Self-improvement
• Long-term autonomy

The biggest shift happening right now:

We're moving from AI that answers questions...

to AI that completes objectives.

The winners of the next decade won't be the people with the best prompts.

They'll be the people who know how to design systems that can:
→ Think
→ Act
→ Learn
→ Scale

That's the foundation behind the next generation of AI products, copilots, and autonomous businesses.

Coming soon: one of history’s most complex missions

As a reminder, this will be a demonstration mission of docking in low Earth orbit between Orion and the HLS of SpaceX and Blue Origin.

The Goldman Sachs prediction model for the FIFA World Cup is out:

🇪🇸 Spain: 26%
🇫🇷 France: 19%
🇦🇷 Argentina: 14%
🇧🇷 Brazil: 8%
🏴󠁧󠁢󠁥󠁮󠁧󠁿England: 5%

Goldman Sachs has predicted Spain to win the 2026 World Cup using probabilities.

github.com/ddm7018/Elo

Goldman Sachs' World Cup prediction is based on an ELO model using nearly 20,000 international matches since 1978, plus factors like scoring ability, recent form, geography, and historical performance.

github.com/ModelOriented/EloML

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

Nebius $NBIS commits £1.7B to expand the UK AI cloud infrastructure footprint across four distinct data center sites.

Powered by Nvidia $NVDA Blackwell Ultra systems, the full stack facilities scale capacity to 65MW by 2027 to serve clients like Revolut.

$AMD just announced plans to invest up to £2 Billion in the United Kingdom 🇬🇧 over the next 5 years

"to accelerate AI innovation and research and expand access to the compute resources needed for long-term economic growth and scientific leadership across the country."

Physicists found a mathematical exit inside a black hole — and the math says it leads somewhere else. 🕳️

Elon Musk:

“In ten years, we'll have a mass driver on the Moon”