🇨🇭 Global One SI - Prompt
5 Different Methodologies That Currently Generate Sustainable Edge on Polymarket Weather Markets I analyzed more than 30 weather bots through Parity Terminal and identified 5 fundamentally different approaches From deterministic NWP-based systems to ML-driven…
The Complete Map of ECMWF and GFS Biases Across Major Cities on Polymarket Weather Markets
I’ve thoroughly reviewed a detailed analysis of systematic errors in the major weather models (ECMWF, GFS, UKMO, CMC)
This isn’t just some theory - it’s based on real data from many years of observations
Most regular traders and simple bots do the following: they open a forecast from a single model, check the expected temperature, and place bets on 1-degree binary options for London, Paris, NYC, Houston, and other cities
But the systematic deviation of the model eats away at the entire edge
> What is systematic bias in simple terms?
It’s when a model consistently lies in the same direction in certain situations - either underestimating or overestimating temperature. Not randomly, but almost predictably
> Here are the most important biases smart traders exploit:
• ECMWF (the most popular “best” model) - frequently underestimates daytime heat. It often shows 1–2°C lower than reality, especially during sunny weather and high pressure in Europe and the southwestern US. High-temperature bins on London and Paris are often cheaper than they should be
• GFS (American model) - regularly overestimates temperature. In the southeastern US it frequently shows 0.5–1°C warmer than actual. Low-temperature bins in NYC or Houston sometimes offer very attractive prices
• UKMO - often underestimates temperature by 1–2°C in northern regions
• CMC/GEM (Canadian model) - tends to overestimate temperature in northern US due to poor snow cover handling
Even the best models in the world are not perfect and have their own permanent weaknesses
Ensemble runs (50+ slight variations of the same model) partially smooth these errors. But the real fat edge belongs to those who know each model’s blind spots and apply station-specific, season-specific corrections
If you trade without this correction, you are every day fighting against a built-in 0.5–2°C systematic error. On markets where the step is just one degree, this is a massive difference in money
I’ve thoroughly reviewed a detailed analysis of systematic errors in the major weather models (ECMWF, GFS, UKMO, CMC)
This isn’t just some theory - it’s based on real data from many years of observations
Most regular traders and simple bots do the following: they open a forecast from a single model, check the expected temperature, and place bets on 1-degree binary options for London, Paris, NYC, Houston, and other cities
But the systematic deviation of the model eats away at the entire edge
> What is systematic bias in simple terms?
It’s when a model consistently lies in the same direction in certain situations - either underestimating or overestimating temperature. Not randomly, but almost predictably
> Here are the most important biases smart traders exploit:
• ECMWF (the most popular “best” model) - frequently underestimates daytime heat. It often shows 1–2°C lower than reality, especially during sunny weather and high pressure in Europe and the southwestern US. High-temperature bins on London and Paris are often cheaper than they should be
• GFS (American model) - regularly overestimates temperature. In the southeastern US it frequently shows 0.5–1°C warmer than actual. Low-temperature bins in NYC or Houston sometimes offer very attractive prices
• UKMO - often underestimates temperature by 1–2°C in northern regions
• CMC/GEM (Canadian model) - tends to overestimate temperature in northern US due to poor snow cover handling
Even the best models in the world are not perfect and have their own permanent weaknesses
Ensemble runs (50+ slight variations of the same model) partially smooth these errors. But the real fat edge belongs to those who know each model’s blind spots and apply station-specific, season-specific corrections
If you trade without this correction, you are every day fighting against a built-in 0.5–2°C systematic error. On markets where the step is just one degree, this is a massive difference in money
✍1
🇺🇸 Trump officials reportedly want a $250 bill featuring the president’s portrait.
It would be the first appearance of a living person on U.S. currency in 150+ years.
Last year, two political appointees at the Treasury “repeatedly urged staff” at the Bureau of Engraving and Printing to prepare prototypes.
The artist who claimed to design the mock-up of the note also said he had spoken to Trump about it.
The $250 note would be a nod to America’s 250th birthday, coming July 4.
Anything like this would almost certainly need to pass through Congress, and U.S. law currently prohibits depicting living individuals on currency.
Source: Washington Post
It would be the first appearance of a living person on U.S. currency in 150+ years.
Last year, two political appointees at the Treasury “repeatedly urged staff” at the Bureau of Engraving and Printing to prepare prototypes.
The artist who claimed to design the mock-up of the note also said he had spoken to Trump about it.
The $250 note would be a nod to America’s 250th birthday, coming July 4.
Anything like this would almost certainly need to pass through Congress, and U.S. law currently prohibits depicting living individuals on currency.
Source: Washington Post
After months of aggressive downside pressure, $ASBP is finally attempting to stabilize near the lows.
Technical structure developing:
- Holding key support near $4
- Reclaim attempt vs descending trend resistance
- TTM Squeeze building momentum
- Large historical volatility profile
- Speculative volume returning
- Possible breakout trigger over $6 → $6.91
The chart is beginning to transition from:
flush → stabilization → reversal attempt.
And with only ~1.2M float shares outstanding, this is exactly the type of low-float biotech setup capable of moving FAST once momentum traders pile in.
Definitely one to keep on watch.
Peers: $SPRC $YCBD $SXTP $SXTC $SNES $ENVB $JUNS $JAGX $SNOA $INM
Technical structure developing:
- Holding key support near $4
- Reclaim attempt vs descending trend resistance
- TTM Squeeze building momentum
- Large historical volatility profile
- Speculative volume returning
- Possible breakout trigger over $6 → $6.91
The chart is beginning to transition from:
flush → stabilization → reversal attempt.
And with only ~1.2M float shares outstanding, this is exactly the type of low-float biotech setup capable of moving FAST once momentum traders pile in.
Definitely one to keep on watch.
Peers: $SPRC $YCBD $SXTP $SXTC $SNES $ENVB $JUNS $JAGX $SNOA $INM
U.S. drones are now a national security priority.
Military & Defense
$ONDS Ondas
$AVEX AEVEX
$KTOS Kratos
$RCAT Red Cat
$AVAV AeroVironment
$AIRO AIRO
$PRZO ParaZero
Commercial
$UMAC Unusual Machines
Sensors
$TDY Teledyne
$ZENA ZenaTech
$HON Honeywell
Software
$PDYN Palladyne
$SWMR Swarmer
Delivery
$AMZN Amazon
eVTOL
$ACHR Archer
$JOBY Joby
Agriculture
$TRMB Trimble
$UAVS AgEagle
Industrial Aerospace and Defense
$LMT Lockheed Martin
$NOC Northrop Grumman
$BA Boeing
$RTX Raytheon
$LHX L3Harris
$HO Thales
$LDO Leonardo
$TXT Textron
Military & Defense
$ONDS Ondas
$AVEX AEVEX
$KTOS Kratos
$RCAT Red Cat
$AVAV AeroVironment
$AIRO AIRO
$PRZO ParaZero
Commercial
$UMAC Unusual Machines
Sensors
$TDY Teledyne
$ZENA ZenaTech
$HON Honeywell
Software
$PDYN Palladyne
$SWMR Swarmer
Delivery
$AMZN Amazon
eVTOL
$ACHR Archer
$JOBY Joby
Agriculture
$TRMB Trimble
$UAVS AgEagle
Industrial Aerospace and Defense
$LMT Lockheed Martin
$NOC Northrop Grumman
$BA Boeing
$RTX Raytheon
$LHX L3Harris
$HO Thales
$LDO Leonardo
$TXT Textron
🇨🇭 Global One SI - Prompt
After months of aggressive downside pressure, $ASBP is finally attempting to stabilize near the lows. Technical structure developing: - Holding key support near $4 - Reclaim attempt vs descending trend resistance - TTM Squeeze building momentum - …
$ASBP very nice start today with price now testing the downtrend resistance line while volume starts building again 👀
- holding the base
- momentum slowly returning
- squeeze setup developing
- low float biotech structure
A clean break over $5.80 could trigger a strong momentum squeeze very quickly.
Definitely keeping this one close on watch today.
- holding the base
- momentum slowly returning
- squeeze setup developing
- low float biotech structure
A clean break over $5.80 could trigger a strong momentum squeeze very quickly.
Definitely keeping this one close on watch today.
🔥2
🇨🇭 Global One SI - Prompt
Anthropic's has dropped its latest model Claude Opus 4.8 with Mythos dropping soon.
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Claude Opus 4.8 is now available for Max subscribers on Perplexity and Computer.
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🇨🇭 Global One SI - Prompt
Claude plugins will change how you use AI forever. It's literally like Claude Skills but on steroids. You'll want to save this quickstart guide
Anthropic just released dynamic workflows, and it's insane.
You can now spin up HUNDREDS of Claude subagents in seconds.
This quickstart guide is everything you need to deploy 100+ Claude agents
You can now spin up HUNDREDS of Claude subagents in seconds.
This quickstart guide is everything you need to deploy 100+ Claude agents
✍1
OpenAI’s Compute Buildout Is Going Vertical🚀
Estimated OpenAI compute capacity has gone from:
2023: 200MW
2024: 600MW
2025: 1,900MW
And the chip mix is shifting fast:
Ampere → Hopper → Blackwell.
That means more power, more data centers, more cooling, more networking, and more demand across the entire AI infrastructure stack.
AI is no longer just a software story.
It’s a capex supercycle.
Estimated OpenAI compute capacity has gone from:
2023: 200MW
2024: 600MW
2025: 1,900MW
And the chip mix is shifting fast:
Ampere → Hopper → Blackwell.
That means more power, more data centers, more cooling, more networking, and more demand across the entire AI infrastructure stack.
AI is no longer just a software story.
It’s a capex supercycle.
🇨🇭 Global One SI - Prompt
Anthropic's has dropped its latest model Claude Opus 4.8 with Mythos dropping soon.
99% of people just missed this in the new Opus 4.8 release notes.
In the coming weeks, Anthropic is releasing a MYTHOS-level model to the public.
The same model that found hundreds of critical vulnerabilities in top companies' software.
Is this even legal to make public?
In the coming weeks, Anthropic is releasing a MYTHOS-level model to the public.
The same model that found hundreds of critical vulnerabilities in top companies' software.
Is this even legal to make public?
🔥1
🇨🇭 Global One SI - Prompt
Anthropic just released dynamic workflows, and it's insane. You can now spin up HUNDREDS of Claude subagents in seconds. This quickstart guide is everything you need to deploy 100+ Claude agents
You can now spin up HUNDREDS of Claude subagents?
This new feature is the most powerful feature Anthropic has ever shipped.
Dynamic workflows run scripts that can deploy tens to hundreds of parallel subagents in a single session.
Here's how to deploy these new dynamic workflows (explained in 60 seconds):
1. Open Claude Code CLI, Desktop, or VS Code extension
(must be on Max, Team, or Enterprise plan)
2. Turn on Auto Mode
This is required for the best experience with dynamic workflows.
(shift + tab to cycle)
3. Pick your starting method:
Option A: Ask Claude directly
"Create a workflow for [your task]."
Option B: Turn on Ultracode
Found in the effort menu. Sets effort to xhigh and lets Claude decide automatically when to spin up a workflow.
4. Confirm the run
The first time a workflow triggers, Claude shows you exactly what's about to run and asks you to confirm before anything starts.
5. Let it run
Claude breaks your task into subtasks, fans them out across parallel subagents, checks every result before folding it in, and hands you back a single
The best use cases right now:
- Codebase-wide bug hunts and security audits
- Large migrations touching hundreds of files
- Any critical work needs to be independently verified before it reaches you
Work you'd normally plan in quarters now finishes in days.
Save this and deploy your first workflow now.
This new feature is the most powerful feature Anthropic has ever shipped.
Dynamic workflows run scripts that can deploy tens to hundreds of parallel subagents in a single session.
Here's how to deploy these new dynamic workflows (explained in 60 seconds):
1. Open Claude Code CLI, Desktop, or VS Code extension
(must be on Max, Team, or Enterprise plan)
2. Turn on Auto Mode
This is required for the best experience with dynamic workflows.
(shift + tab to cycle)
3. Pick your starting method:
Option A: Ask Claude directly
"Create a workflow for [your task]."
Option B: Turn on Ultracode
Found in the effort menu. Sets effort to xhigh and lets Claude decide automatically when to spin up a workflow.
4. Confirm the run
The first time a workflow triggers, Claude shows you exactly what's about to run and asks you to confirm before anything starts.
5. Let it run
Claude breaks your task into subtasks, fans them out across parallel subagents, checks every result before folding it in, and hands you back a single
The best use cases right now:
- Codebase-wide bug hunts and security audits
- Large migrations touching hundreds of files
- Any critical work needs to be independently verified before it reaches you
Work you'd normally plan in quarters now finishes in days.
Save this and deploy your first workflow now.
✍1
🇨🇭 Global One SI - Prompt
ONDS — This may be one of the BIGGEST growth stories in the autonomous systems sector right now 👀 The company just posted: - Q1 revenue up MORE THAN 10X YoY - Raised full-year revenue guidance to at least $390M - EBITDA positive SIX MONTHS ahead of schedule…
Question:
How many companies are growing revenue more than 10x YoY while building exposure to:
→ autonomous systems
→ defense technology
→ AI infrastructure
Now add a bullish pennant directly under breakout levels.
That's why $ONDS keeps showing up on my radar.
How many companies are growing revenue more than 10x YoY while building exposure to:
→ autonomous systems
→ defense technology
→ AI infrastructure
Now add a bullish pennant directly under breakout levels.
That's why $ONDS keeps showing up on my radar.
🇨🇭 Global One SI - Prompt
$NBIS/USD H2 #Indicator #Signal #Trading #GlobalOneAI Globalone.ch #Prompt #AI
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Jensen Huang admitted that he missed Anthropic, and today it just closed at a $965 billion valuation (Save this).
As Jensen put it, he didn't deeply internalize how difficult it would be to build a foundation AI lab like Anthropic.
He assumed they could just raise from VCs like any other company.
"A VC would never put in five, ten billion dollars of investment into an AI lab with the hopes of it turning out to be Anthropic. And so that was my miss."
That miss is now a $965 billion company.
Today, Anthropic closed a $65 billion Series H round, the largest private funding round in history with strategic infrastructure partners including Samsung, SK Hynix, and Micron, and institutional investors including Altimeter, Sequoia, Blackstone, and Baillie Gifford all piling in.
Just three months ago Anthropic was valued at $380 billion, and before that $61 billion, the same company Jensen couldn't write the check for when it mattered.
What makes Jensen's admission so striking is why the capital was needed in the first place.
Anthropic was not raising to hire salespeople or run marketing campaigns, it was raising to buy compute at the scale required to train foundation models.
The compute suppliers Google, AWS, and now NVIDIA itself had to become investors because there was no other mechanism to guarantee the level of spend these labs required.
"I'm not going to make that same mistake again," Jensen said.
NVIDIA is now an investor in both OpenAI and Anthropic.
And it's also important to Claude's run-rate revenue crossed $47 billion today, up from $9 billion just six months ago, which means they are going to need massive amount of compute.
And who will they go to, it's to the Neoclouds and I expect a deal between Anthropic and Nebius soon.
As Jensen put it, he didn't deeply internalize how difficult it would be to build a foundation AI lab like Anthropic.
He assumed they could just raise from VCs like any other company.
"A VC would never put in five, ten billion dollars of investment into an AI lab with the hopes of it turning out to be Anthropic. And so that was my miss."
That miss is now a $965 billion company.
Today, Anthropic closed a $65 billion Series H round, the largest private funding round in history with strategic infrastructure partners including Samsung, SK Hynix, and Micron, and institutional investors including Altimeter, Sequoia, Blackstone, and Baillie Gifford all piling in.
Just three months ago Anthropic was valued at $380 billion, and before that $61 billion, the same company Jensen couldn't write the check for when it mattered.
What makes Jensen's admission so striking is why the capital was needed in the first place.
Anthropic was not raising to hire salespeople or run marketing campaigns, it was raising to buy compute at the scale required to train foundation models.
The compute suppliers Google, AWS, and now NVIDIA itself had to become investors because there was no other mechanism to guarantee the level of spend these labs required.
"I'm not going to make that same mistake again," Jensen said.
NVIDIA is now an investor in both OpenAI and Anthropic.
And it's also important to Claude's run-rate revenue crossed $47 billion today, up from $9 billion just six months ago, which means they are going to need massive amount of compute.
And who will they go to, it's to the Neoclouds and I expect a deal between Anthropic and Nebius soon.
This is Nvidia’s list of partners for next-gen 800V power architecture.
$NVTS Navitas
Mediatek
Delta Electronics
$STM STMicroelectronics
$AOSL Alpha & Omega Semiconductors
$FLEX Flex
$POWI Power Integrations
$ON onsemi
$IFX Infineon
$VRT Vertiv
$TXN Texas Instruments
$MPWR Monolithic Power
$GEV GE Vernova
$ADI Analog Devices
LITE-ON Technology
$ABBN ABB
BizLink
$ETN Eaton
$SU Schneider Electric
$SIE Siemens
Innoscience
$NVTS Navitas
Mediatek
Delta Electronics
$STM STMicroelectronics
$AOSL Alpha & Omega Semiconductors
$FLEX Flex
$POWI Power Integrations
$ON onsemi
$IFX Infineon
$VRT Vertiv
$TXN Texas Instruments
$MPWR Monolithic Power
$GEV GE Vernova
$ADI Analog Devices
LITE-ON Technology
$ABBN ABB
BizLink
$ETN Eaton
$SU Schneider Electric
$SIE Siemens
Innoscience