If you missed the $NVDA trade, don't worry. The next big AI trade is literally sitting right in front of you.

I just compiled 60+ AI companies currently printing multiples - all in one place.

If you want massive gains from this sector, bookmark this

First came AI models.

Then came AI assistants.

The next phase may be AI ecosystems.

OpenAI’s reported ChatGPT overhaul points toward something much bigger:

• AI agents
• Search
• Coding
• Images
• Third-party integrations

The companies that control the ecosystem may ultimately control the value.

This is no longer just a race for better models.

It’s becoming a race for distribution, engagement and daily utility.

The AI story keeps expanding.

$LFVN caught my attention.

#2 Trending on StockTwits.
Massive volume.
Major trendline breakout.
Back above the 200-day moving average.

After spending months in a downtrend, the chart suddenly looks very different.

When a stock breaks structure and traders start paying attention at the same time, things can get interesting fast.

Worth watching next week. 👀

$LFVN #Stocks #Momentum #Trading

6 Best ML Libraries Top Quant Traders Use to Exploit Model Bias on Polymarket (Full Quant Stack)

Most bots on Polymarket still operate as simple reactive systems - they treat public forecasts as the ultimate truth

Top quant traders have moved far beyond that. Instead of relying on public models and third-party forecasts, they build meta-models that actively hunt for and exploit the systematic biases and weaknesses in those forecasts

Here’s the actual list of libraries that top quants are using right now:

1. LightGBM - The Go-To Workhorse

• Extremely fast gradient boosting with leaf-wise tree growth
• Handles hundreds of features effortlessly (raw forecasts + historical bias corrections + sentiment + volume)
• Repo: github.com/lightgbm-org/LightGBM

2. XGBoost - The Reliable Veteran

• Classic gradient boosting with strong regularization
• Excellent GPU support and best-in-class SHAP explainability
• Repo: github.com/dmlc/xgboost

3. HistGradientBoosting (scikit-learn)

• Powerful histogram-based boosting built directly into sklearn
• Best choice for fast prototyping and experimentation
• Repo: github.com/scikit-learn/scikit-learn

4. RandomForest (also sklearn)

• Solid baseline to quickly check if your features actually have signal
• Repo: github.com/scikit-learn/scikit-learn

5. TabNet

• Neural network architecture designed specifically for tabular data
• Great at combining text embeddings (news/tweets) with numerical features
• Repo: github.com/dreamquark-ai/tabnet

6. River

• Best library for online/incremental learning
• The model learns and adapts in real time - essential for fast-moving events
• Repo: github.com/online-ml/river

Recommended 2026 Stack: LightGBM (main model) + XGBoost (stacking) + River (online adaptation)

All of these libraries work great with SHAP - so you don’t just get a probability, you actually see which model bias you’re currently profiting from

Bookmark this post so you don’t lose it!

$IREN $NBIS $MRVL $HUT $CRWV | Zurich Insurance expands data center underwriting offerings to major markets across Europe and South America.

The strategic move targets a projected $134 billion global digital infrastructure premium pool.

$IBM $IONQ $HON $QBTS $RGTI | Microsoft cut the quantum computing timeline in half, now targeting a scalable, commercial machine by 2029.

This leap follows the debut of the Majorana 2 chip, featuring qubits 1,000 times more reliable than predecessors.

$RDW $VOYG $RKLB $PL $FLY | Beijing approves a new innovation center to unify the entire space computing industrial chain by late June.

Across the globe, the commercial space sector is set to smash records as SpaceX targets a historic $1.75 trillion IPO valuation.

🚨 SPACEX JUST LAUNCHED TWO SECRET STARSHIELD SATELLITES.

Alongside 21 new Starlink satellites, SpaceX quietly sent two mysterious Starshield spacecraft into orbit.

Unlike Starlink, Starshield is designed for government and national security missions.

What's unusual?

• SpaceX has not revealed who ordered them
• No agency has publicly claimed them
• Their exact purpose remains classified
• Similar launches have previously been linked to intelligence and reconnaissance networks

Starshield uses the same technology that powers Starlink...

but adapted for secure communications, surveillance, and military operations in orbit.

The bigger picture:

We are witnessing the rise of a new generation of space infrastructure where commercial rockets and government satellites are becoming increasingly intertwined.

The next space race may not be about reaching the Moon.

It may be about controlling information, communications, and intelligence from orbit.

The question is:

How much of the future world's infrastructure will be operating above our heads without the public ever knowing?

I'm only on for one reason, to warn you of what's coming

People still think the AI bubble didn't pop last week.

The railroad bubble of 1873 sounds like the AI bubble of 2026, doesn't it?

Same taglines, same promises, same private credit, same Rothschilds, same result?

Donald Trump is basically describing Universal Capital Ownership.

If AI creates trillions of dollars in new wealth, normal people should not just watch a few companies and investors get insanely rich.

The public should own a piece of the upside too.

That could mean equity stakes, public dividends, or a national AI wealth fund where every citizen benefits when AI companies win.

Because if AI starts doing more of the work, wages alone won’t be enough. People need ownership.

This is how you make the AI revolution something the whole country can support.

Let Americans share in the wealth of the most important technology boom in human history.

The rumored ChatGPT superapp could be huge.

From what’s being reported, OpenAI may be moving toward one unified app that brings together:

• ChatGPT
for thinking, writing, planning, research and everyday AI assistance

• Codex
for coding, debugging, building apps and automating developer work

• Atlas browser
for browsing the web, understanding pages and taking actions online

• Computer use
where GPT-5.6 level agents are way above human baseline on real desktop tasks

If true, this is much bigger than another chatbot update.

It means ChatGPT becomes the central AI operating layer for work.

You don’t open 10 different tools anymore.

You open ChatGPT and it helps you think, browse, build, click, automate and act.

Today across the world it is estimated that a new Humanoid Robot is produced every 10 seconds. It will be every second in 3 years.

🔥 RTX Spark dethroned already?

Later this year expect to see the GMKTek Evo-X3, currently the most popular AMD Strix Halo PC, to release a follow on box w/an upgraded processor Gorgon Halo and up to 192 GB of RAM. Sorry RTX Spark 😁

$AMD believes unified memory architectures open up a "world of possibilities," will shape its product choices and roadmaps in the future.

LG Transforms Car Windshields Into Futuristic Transparent OLED Displays

ANTHROPIC JUST MADE AI AGENTS TALK TO ROBOTS

This guy connects claude to a physical robot via ROS and the robot figures out on its own how to move and find objects in a room

and anthropic just dropped managed agents that handle sessions, credentials and debugging loops automatically so building stuff like this went from days of infrastructure work to 30 minutes

The gap between “AI chatbot” and “AI that acts in the physical world” is closing faster than most people realize and we’re still in the early innings

github.com/agenticros