Trump and the US government just handed China the easiest win in the AI race.

60% of companies are already rerouting their AI spend toward cheaper, open-source models - and most of the best ones are Chinese (Qwen, DeepSeek, GLM, Kimi).

US frontier models are now being gatekept by the government AND priced at a premium for only marginal gains in intelligence.

To be fair, this is a genuinely hard spot for the US:

On one hand, you want America to lead AI innovation (especially so that you, as the government, can have access).

But you also want the most powerful models secured and controlled for national security reasons.

The problem is that those two goals are now directly at odds.

Every restriction placed on US frontier models makes the open-source alternative more attractive.

And for now, the best open-source alternatives aren't American.

Going to be very interesting to watch things play out from here.

🇺🇸 Fed's Kashkari says ‘I am concerned about inflation, especially in services.’

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

I keep wondering what happens to money in a post labor world.

If AI and robots can produce almost everything cheaper, faster and better than humans ever could, does money slowly lose its power?

At some point, scarcity is the only thing keeping the whole game alive.

$MU $SNDK $WDC $INTC $ASML | Apple lobbies the Trump administration for political clearance to purchase consumer memory chips from Chinese manufacturer CXMT.

The move seeks to ease supply chain constraints after soaring component costs forced recent MacBook and iPad price hikes.

$GEV $CEG $OKLO $LEU $UEC | Microsoft partners with Chevron on a twenty year agreement to power a massive West Texas data center using natural gas.

The colocated Project Kilby plant secures seven GE Vernova turbines to deliver 2.67 gigawatts (GW) of independent electricity.

"The share of tokens used for US models on OpenRouter has collapsed" Bloomberg

On OpenRouter, US model token share fell from around 70% to around 30% in a year.

A clean warning signal.

open-weight Chinese models are becoming capable enough for routine work, cheaper to run, easier to customize, and less dependent on permission from a frontier lab.

AI revenue has crossed its first serious accounting test: $25B in quarterly sales now exceeds $21B in estimated chip and data-center depreciation.

i.e. AI infrastructure is starting to pay for itself before power, labor, financing, and leases are counted.

I don’t think AI takes all jobs overnight.

That’s the cartoon version.

The real transition will be slower and much weirder: AI takes tasks first, then teams shrink, hiring slows, entry-level jobs disappear, and companies quietly realize they need fewer humans every year.

McKinsey already estimates that up to 30% of US work hours could be automated by 2030. The World Economic Forum expects 92 million jobs to be displaced by 2030, even while new jobs are created.

So no, everyone won’t be jobless next Monday.

But over the next 15 years, the pressure keeps building.

The obvious transition isn’t “no work.”

It’s 5 days becoming 4.

Then maybe 3.

Then the real question begins.

$IBM unveils world's first publicly announced sub-1nm chip technology 👀

They just unveiled NanoStack, a breakthrough 3D transistor architecture designed for the 7 Å (~0.7 nm) technology node, making it the world's first publicly announced chip technology below 1 nanometer.

Instead of placing transistors side by side, NanoStack stacks them vertically, allowing nearly 100 billion transistors to fit on a silicon chip about the size of a fingernail while dramatically increasing transistor density.

IBM says its prototype delivers up to 50% higher performance or up to 70% lower power consumption compared with its 2 nm research chip introduced in 2021.

Acceleration is everywhere!

$IBM/USD H2 #Indicator #Signal #Trading #GlobalOneAI
Globalone.ch #Prompt #AI

I knew the government was playing 4D chess when they restricted Mythos/Fable...

Trump Administration just partially lifted the ban.

Two weeks of standoff, now released to a controlled set of ~100 trusted US companies and agencies.

The government wasn't perma restricting AI capabilities... they were establishing control first (and possibly private placement deals).

Now we wait for the full Fable 5 release, equity stake announcements, and clearer plans for their IPO.

You can turn Hermes & Claude Code into your personal crypto trading assistants.

It can execute real market orders, manage live positions, and more.

Most traders have no idea this is even possible.

Send this prompt to Claude Code, and you'll be able to automate your trading

🔥 INSANE: Robotics Investments hit an ATH of $16B, per a16z.

How to Build Agent Skills for Claude (Step-by-Step)

When you come back to check on your old job and it's even worse than you expected

The smartest thing you can do with Hermes right now:

Create a self-evolving loop that trains Hermes on your data - so every session is smarter than the last.

Session 1 → learns → logs it → Session 2 is smarter → logs that → repeat

Here's exactly how to set it up:

1. Create a Memory.md file on your desktop

Structure it like this:

## Preferences
## Corrections
## Patterns
## Lessons learned

2. Attach it to Hermes

Paste this prompt once:

"At the start of every session, read Memory.md and apply everything in it.

After every task, do three things:

• Log what worked and why
• Log what failed and why
• Analyse and write rules you'd apply next time

Never duplicate entries. Rewrite existing rules when you learn something better."

3. Once a week, run this prompt:

"Review everything in Memory.md. Identify patterns across all your logged lessons. Distill them into sharper, more general rules. Delete anything that's been superseded. The goal: fewer, better rules every week."

4. Archive before every cleanup

Copy Memory.md into a dated backup before your agent rewrites anything.

(In case of any mistakes, this is how you secure previous data)

That's the self-evolution loop that everyone should be running with Hermes right now.

Super simple, but it makes Hermes 10x more powerful.

Make sure to bookmark this so you actually maximise your agentic workflows.

It's hard to fathom that in ~12 months, we'll likely have access to a model 2x more powerful than Fable 5.

And that might be the conservative estimate, & model costs will likely be way cheaper at that point, too.

Here's why:

The best single measure of AI capability is Epoch's Capabilities Index (ECI)

(a composite score across 40+ benchmarks - math, coding,
science, reasoning).

Think of it like an IQ test for frontier models.

When Fable was released, it hit a new high of 161 on the ECI.

Now here's the part that matters:

The rate of frontier improvement nearly doubled around April 2024, from about 8 points per year to 15.

That faster pace has now held across every single quarterly measurement cycle since then, and is the new trend.

So, in theory, the trend that's held since 2024 just needs to continue in post-Fable 5 model releases, and the floor in 12 months is a 2-3x improvement in model capability.

But the wildest stat isn't even the capability curve.

It's the cost curve:

The cost to run an AI model at a fixed level of performance is halving every 2 months.

Put it together:

In 12 months, you won't just have a model 2x more capable than Fable 5.

You'll have it cheaper, faster, and possibly running on hardware you already own.

We're so early.

$CRWV – AI GPU Cloud Specialist Pulling Back

Weekly chart: Big prior run then sharp -18%+ candle testing support. $43B mkt cap player in the exploding AI infrastructure space.

CoreWeave runs specialized data centers packed with NVIDIA GPUs for AI training & inference. High-demand niche as everyone from startups to enterprises needs massive compute power.
Fits the broader AI cloud theme (see $NBIS): Capacity constraints + surging workloads = opportunity for specialists. But capex intense and competitive.

Watch support levels. Sector momentum strong if AI spend continues.

$16B Robotics Investments in 2026 — ATH per a16z

This isn’t hype. It’s the moment AI gets a body.
Software intelligence exploded first (ChatGPT moment). Now capital is flooding the physical layer — humanoids, autonomous systems, and embodied AI.
Why this matters:
• Record funding = validation that robots are moving from demos to real deployment.
• AI brains + robotics bodies = the next multi-trillion TAM (industry forecasts already talking hundreds of billions to trillions long-term).
• Compute, power, and data infrastructure just became even more critical.
This follows the exact AI infrastructure boom we’ve been tracking.
The companies powering the training (massive GPU clouds) and the future deployment (space, mobility, factories) are positioned right at the center.
Robotics isn’t replacing AI — it’s the next chapter.
What do you think — is 2026 the year physical AI goes mainstream, or still early?

$JOBY eVTOL Air Taxi Thesis

Consolidating after moves, holding trendline support near $8–9 with volume. Mid-cap play in the next frontier of transportation.

Joby Aviation leading eVTOL race: Quiet electric air taxis for cities, bypassing traffic. FAA progress, Toyota manufacturing tie-up, Delta/Uber partnerships. Targeting commercial launch soon.
Industry Boom Setup: Urban air mobility = massive TAM. Congestion + sustainability driving adoption. Batteries improving, regs advancing, vertiports coming. Joby among frontrunners in US.

Risks: Certification delays, cash burn, infrastructure buildout, competition. Classic high-upside disruptive play.

Chart looks constructive if holds support. Bullish on AAM sector long-term?