🇨🇭 Global One SI - Prompt
$VELO/USD H2 #Indicator #Signal #Trading #GlobalOneAI
$VELO: Velo3D and Aurelia Technologies Announce Strategic Partnership to Advance Additive Manufacturing for Next‑Generation Gas Turbine Systems
The partnership supports Aurelia's broader continuous‑improvement strategy, one centered on design consolidation, faster iteration, supply chain resilience, and long‑term cost reduction.
The collaboration is important for Velo3D as it underscores the expanding role of additive manufacturing in advanced energy and propulsion systems.
By partnering with an innovative turbine developer like Aurelia Technologies, Velo3D further demonstrates how its technology can accelerate product development, unlock greater design freedom, overcome traditional manufacturing constraints and strengthen resilient domestic supply chains.
The partnership supports Aurelia's broader continuous‑improvement strategy, one centered on design consolidation, faster iteration, supply chain resilience, and long‑term cost reduction.
The collaboration is important for Velo3D as it underscores the expanding role of additive manufacturing in advanced energy and propulsion systems.
By partnering with an innovative turbine developer like Aurelia Technologies, Velo3D further demonstrates how its technology can accelerate product development, unlock greater design freedom, overcome traditional manufacturing constraints and strengthen resilient domestic supply chains.
🇨🇭 Global One SI - Prompt
How a Trader Makes $300–$500 a Day Using the Bonding Strategy on Polymarket (Risk-Free) Found a trader who gets 80% APY simply by collecting profit on guaranteed outcomes He uses a pure bonding strategy: buys contracts at 95–99.5 cents on markets where…
Advanced Bias Correction for Polymarket Weather Trading Bots: ConvLSTM + Self-Attention + Dynamic Normalization
If you're building a serious trading bot for temperature markets, at some point simple bias correction stops being enough
I found one of the most interesting papers from 2025 that breaks down how to build a truly powerful AI bias correction system for ECMWF
Paper: "How to systematically develop an effective AI-based bias correction model" (ReSA-ConvLSTM, Zhou et al., arXiv, April 2025)
Link: arxiv.org/pdf/2504.15322
> What the Authors Built
They created a full framework called ReSA-ConvLSTM, which delivers up to 20% RMSE reduction on the 1–7 day horizon compared to raw ECMWF output.
> Architecture Breakdown
1. ConvLSTM as the main backbone
Regular convolutional networks (like U-Net) are good with images but weak at understanding temporal dynamics
ConvLSTM is a hybrid of Conv + LSTM. It analyzes both spatial features (mountains, seas, cities) and temporal evolution (how temperature changed over the past hours/days)
This makes it much stronger for meteorological data
2. Dynamic grid-wise normalization instead of standard Z-score
Standard normalization uses one global mean for the whole world - which works poorly for temperature
Here, each grid point has its own climatological mean and variance
This removes the huge difference between tropical and polar regions and significantly improves training stability
3. Strict temporal causality
The model only looks at past states and doesn’t “peek” into future forecast days. Critical for real-time trading systems.
4. Residual connections + Self-Attention
Residual connections help the network go deeper without losing information
Self-Attention allows the model to automatically focus on important areas (coastal zones, mountains, etc.)
> Results
• Raw ECMWF: RMSE 1.2°C on day 1 → 2.1°C on day 7
• ReSA-ConvLSTM: below 1.0°C on days 1–3, below 1.8°C on days 4–7
The model also transfers well to wind and pressure variables
> How to Implement It Yourself
There’s no official ReSA-ConvLSTM repo yet, but you can build a very close version using:
ndrplz/ConvLSTM_pytorch - one of the best and cleanest ConvLSTM implementations
Repo: github.com/ndrplz/ConvLSTM_pytorch
tsugumi-sys/SA-ConvLSTM-Pytorch - ConvLSTM already with Self-Attention
Repo: github.com/tsugumi-sys/SA-ConvLSTM-Pytorch
NOAA-EMC/ML4BC - real bias correction project
Repo: github.com/NOAA-EMC/ML4BC
Take ConvLSTM + Self-Attention as the base → add Residual blocks and dynamic grid-wise normalization following the paper → train on ERA5 + ECMWF data
Hybrid architectures like ConvLSTM + Attention + Residual are currently among the strongest directions in weather bias correction
Especially if you want to consistently win on tight 1°C bins on Polymarket
If you're building a serious trading bot for temperature markets, at some point simple bias correction stops being enough
I found one of the most interesting papers from 2025 that breaks down how to build a truly powerful AI bias correction system for ECMWF
Paper: "How to systematically develop an effective AI-based bias correction model" (ReSA-ConvLSTM, Zhou et al., arXiv, April 2025)
Link: arxiv.org/pdf/2504.15322
> What the Authors Built
They created a full framework called ReSA-ConvLSTM, which delivers up to 20% RMSE reduction on the 1–7 day horizon compared to raw ECMWF output.
> Architecture Breakdown
1. ConvLSTM as the main backbone
Regular convolutional networks (like U-Net) are good with images but weak at understanding temporal dynamics
ConvLSTM is a hybrid of Conv + LSTM. It analyzes both spatial features (mountains, seas, cities) and temporal evolution (how temperature changed over the past hours/days)
This makes it much stronger for meteorological data
2. Dynamic grid-wise normalization instead of standard Z-score
Standard normalization uses one global mean for the whole world - which works poorly for temperature
Here, each grid point has its own climatological mean and variance
This removes the huge difference between tropical and polar regions and significantly improves training stability
3. Strict temporal causality
The model only looks at past states and doesn’t “peek” into future forecast days. Critical for real-time trading systems.
4. Residual connections + Self-Attention
Residual connections help the network go deeper without losing information
Self-Attention allows the model to automatically focus on important areas (coastal zones, mountains, etc.)
> Results
• Raw ECMWF: RMSE 1.2°C on day 1 → 2.1°C on day 7
• ReSA-ConvLSTM: below 1.0°C on days 1–3, below 1.8°C on days 4–7
The model also transfers well to wind and pressure variables
> How to Implement It Yourself
There’s no official ReSA-ConvLSTM repo yet, but you can build a very close version using:
ndrplz/ConvLSTM_pytorch - one of the best and cleanest ConvLSTM implementations
Repo: github.com/ndrplz/ConvLSTM_pytorch
tsugumi-sys/SA-ConvLSTM-Pytorch - ConvLSTM already with Self-Attention
Repo: github.com/tsugumi-sys/SA-ConvLSTM-Pytorch
NOAA-EMC/ML4BC - real bias correction project
Repo: github.com/NOAA-EMC/ML4BC
Take ConvLSTM + Self-Attention as the base → add Residual blocks and dynamic grid-wise normalization following the paper → train on ERA5 + ECMWF data
Hybrid architectures like ConvLSTM + Attention + Residual are currently among the strongest directions in weather bias correction
Especially if you want to consistently win on tight 1°C bins on Polymarket
✍1
🇨🇭 Global One SI - Prompt
“Starship V3 is more than double the thrust of the Saturn V moon rocket By V4, we'll be pretty much three times the thrust of the Saturn V moon rocket We expect Starship to be flying more than once per hour down the road” — Elon Musk
SpaceX $SPCX Plans to build Orbital Data Centers!
Here’s what they will need:
- 1B Optimus Robots from Tesla🦾
- 10M Tons launched a year🚀
- 1 TW+ of Solar Energy☀️
Here’s what they will need:
- 1B Optimus Robots from Tesla🦾
- 10M Tons launched a year🚀
- 1 TW+ of Solar Energy☀️
🇨🇭 Global One SI - Prompt
🚨Major Scoop: The first Claude 5 model, Claude Fable 5 (Mythos-class model) is gonna release very soon! It's the same underlying model as Mythos but with increased guardrails, headed to public release
EVERYTHING we currently know about Claude Mythos.
Release is imminent.
Release is imminent.
🇨🇭 Global One SI - Prompt
EVERYTHING we currently know about Claude Mythos. Release is imminent.
Claude "Fable" spotted in Google Cloud.
Extremely likely that we get the Mythos model today.
Probably the biggest model release since the GPT-5 package.
Extremely likely that we get the Mythos model today.
Probably the biggest model release since the GPT-5 package.
🔥1
🇨🇭 Global One SI - Prompt
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…
I'm putting $100,000 on France to win the World Cup.
I win $625,000 if they do.
Am I an idiot?
I win $625,000 if they do.
Am I an idiot?
🏆1
🇨🇭 Global One SI - Prompt
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.
🇨🇭 Global One SI - Prompt
Elon is $161 billion away from becoming the first trillionaire.
Ever wonder where the Federal Reserve's $6 trillion of 2020 money printing went...
💯1
🇨🇭 Global One SI - Prompt
$KTOS/USD H2 #Indicator #Signal #Trading #GlobalOneAI
Kratos Defense $KTOS plans a major production expansion for the oil free Spartan turbojet line, targeting 3,000 completed engines next year.
The domestic manufacturing surge satisfies rising global demand for tactical missiles and loitering munitions.
The domestic manufacturing surge satisfies rising global demand for tactical missiles and loitering munitions.
🇨🇭 Global One SI - Prompt
$ABAT caught my attention Huge volume. Strong recovery off the lows. Reclaimed the 200 MA. The type of action that often appears before a much larger move. Most traders will notice it above $5. I'm noticing it now.
American Battery $ABAT wins a major federal appeal, securing the full reinstatement of a terminated DOE grant.
The restored award finances half of a $115.5 million critical mineral refinery project through 2029.
The restored award finances half of a $115.5 million critical mineral refinery project through 2029.
🇨🇭 Global One SI - Prompt
$ASTS/USD H2 #Indicator #Signal #Trading #GlobalOneAI
AST SpaceMobile $ASTS schedules a Falcon 9 launch for the next generation BlueBird 8, 9, and 10 satellites on June 17.
The Cape Canaveral mission delivers upgraded hardware capable of doubling peak cellular data speeds.
The Cape Canaveral mission delivers upgraded hardware capable of doubling peak cellular data speeds.
🇨🇭 Global One SI - Prompt
$NBIS/USD H2 #Indicator #Signal #Trading #GlobalOneAI Globalone.ch #Prompt #AI
Nebius $NBIS launches a physical AI Living Lab partnership with Nvidia $NVDA to equip British and European robotics startups with advanced tools.
The six month accelerator provides cloud scale training infrastructure ahead of a September launch.
The six month accelerator provides cloud scale training infrastructure ahead of a September launch.
🇨🇭 Global One SI - Prompt
AmpliTech Group $AMPG and its connection with quantum. $AMPG is primarily seen as an 5G O-RAN infrastructure play (and 6G in the future), next to having customers and partnerships for SATCOM and defense. But one thing that I feel the market is underestimating…
Most view $AMPG as just a lumpy 5G play. They are completely blind to the fact that AmpliTech holds an absolute monopoly on the physical nervous system enabling Quantum Computing. ❄️🤖🖥️
Here is the hard reality of deep tech: The future of supercomputing lives at absolute zero. Quantum processors place extraordinary demands on signal technology because the signals being measured are incredibly weak.
Simply put: Room temperature RF physics doesn't work here.
🥵 To prevent data corruption, quantum computers require dilution refrigerators running at 4 Kelvin (near absolute zero). But standard amplifiers generate heat—and any heat generated directly fights the cooling system, destroying quantum coherence.
⬇️ Look at the screenshots from their portal. $AMPG solves this with their proprietary Cryogenic Low-Noise Amplifiers (LNAs).
👨🔬 Because they design these chips at the silicon level in-house via their AGMDC division, they’ve achieved ultra-low noise figures with near-zero power dissipation. It’s a level of performance that off-the-shelf components literally cannot match.
📊 The Financial Translation: > Every single qubit in a superconducting quantum computer requires its own dedicated cryogenic LNA to handle signal readout. As giants like IBM scale from double-digit qubits to 1,000+ qubit systems, $AMPG's hardware footprint scales linearly.
They aren't just a telecom stock. They are an indispensable pick-and-shovel play for the global quantum computing infrastructure race. Dirt cheap at a ~$170M market cap. 💎🌐
Here is the hard reality of deep tech: The future of supercomputing lives at absolute zero. Quantum processors place extraordinary demands on signal technology because the signals being measured are incredibly weak.
Simply put: Room temperature RF physics doesn't work here.
🥵 To prevent data corruption, quantum computers require dilution refrigerators running at 4 Kelvin (near absolute zero). But standard amplifiers generate heat—and any heat generated directly fights the cooling system, destroying quantum coherence.
⬇️ Look at the screenshots from their portal. $AMPG solves this with their proprietary Cryogenic Low-Noise Amplifiers (LNAs).
👨🔬 Because they design these chips at the silicon level in-house via their AGMDC division, they’ve achieved ultra-low noise figures with near-zero power dissipation. It’s a level of performance that off-the-shelf components literally cannot match.
📊 The Financial Translation: > Every single qubit in a superconducting quantum computer requires its own dedicated cryogenic LNA to handle signal readout. As giants like IBM scale from double-digit qubits to 1,000+ qubit systems, $AMPG's hardware footprint scales linearly.
They aren't just a telecom stock. They are an indispensable pick-and-shovel play for the global quantum computing infrastructure race. Dirt cheap at a ~$170M market cap. 💎🌐
🇨🇭 Global One SI - Prompt
EVERYTHING we currently know about Claude Mythos. Release is imminent.
🚨Claude Fable pricing according to The Information
twice the price of opus 4.8 , this will be significantly cheaper than mythos preview < as it was 5 times the rate of opus >
twice the price of opus 4.8 , this will be significantly cheaper than mythos preview < as it was 5 times the rate of opus >
🇨🇭 Global One SI - Prompt
$GRML starting to look like one of those “nobody cares… until everybody does” setups. The chart is now sitting directly on a major support zone after a long multi-month compression phase. This is usually where risk/reward becomes VERY interesting. What…
$GRML
While most investors continue chasing AI software, very few are paying attention to the raw materials required to build the future.
That's where Greenland Mines becomes interesting.
🔹 25.4M oz Palladium Equivalent Resource
🔹 ~$68B estimated in-situ resource value
🔹 877 km² land package in Greenland
🔹 Active 2026 drilling & development program
🔹 Rare Earth expansion underway
🔹 Exposure to Palladium, Platinum and Gold
Meanwhile, the chart continues building a multi-month compression pattern while holding a major long-term support trendline.
Historically, every meaningful test of this support area has produced powerful upside reactions.
The world is entering a new era of:
⚡ Resource Security
⚡ Critical Minerals
⚡ Industrial Electrification
⚡ AI Infrastructure
All of these trends require strategic metals.
The chart is compressing.
The story is strengthening.
And the market cap remains surprisingly small relative to the scale of the underlying asset.
$GRML is one of the most interesting resource stories I've come across recently.
While most investors continue chasing AI software, very few are paying attention to the raw materials required to build the future.
That's where Greenland Mines becomes interesting.
🔹 25.4M oz Palladium Equivalent Resource
🔹 ~$68B estimated in-situ resource value
🔹 877 km² land package in Greenland
🔹 Active 2026 drilling & development program
🔹 Rare Earth expansion underway
🔹 Exposure to Palladium, Platinum and Gold
Meanwhile, the chart continues building a multi-month compression pattern while holding a major long-term support trendline.
Historically, every meaningful test of this support area has produced powerful upside reactions.
The world is entering a new era of:
⚡ Resource Security
⚡ Critical Minerals
⚡ Industrial Electrification
⚡ AI Infrastructure
All of these trends require strategic metals.
The chart is compressing.
The story is strengthening.
And the market cap remains surprisingly small relative to the scale of the underlying asset.
$GRML is one of the most interesting resource stories I've come across recently.