2,428 Photos and videos
New AI signal arrived at 72k mc
$DRUNKEY, Drunk Monkey
ca: 2UFnJmiiB3M24ZqgC4XYgzPoDhsTH2vyJS7zysPQpump
gmgn.ai/sol/token/2UFnJmiiB3…
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🤖 AI Update
MLM is now trained on 44,154 training records and has learned 7,375 unique patterns and signals.
The model analyzes and learns from:
• Telegram group activity
• Group density and timing (Δ patterns)
• Smart wallet activity
• DEX promotions (Dex Paid)
• Structure / Stack formations
• Entry market cap ranges
• Route formations between groups
• Interactions between all of the above
Rather than evaluating signals independently, the latest version learns combinations such as:
Smart Wallet Group Formation
DEX Promotion Group Density
Structure Smart Wallet
Route Pattern Market Conditions
Current performance:
✅ 29 of 55 AI-selected coins reached at least 2x from entry
📈 52.73% hit rate
The model continues to learn from historical data, AI Paper Trader outcomes, MLM self-feedback, and MLM watch-feedback, allowing it to adapt to changing market conditions over time.
The image below is the latest signal just reached 4.1x from 89.5k mc
$dih, Dog in helmet
ca: Gh5tgNMDbWTMsUZa1YVoocz5Q2URzFMtzGp3WKfGpump
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New Hype Radar AI signal
solana:2qEHjDLDLbuBgRYvsxhc5D6uDWAivNFZGan56P1tpump
ca: 6p3Y3WBXcVwMbYNoVsU4EuVb3gdMmzSKhkEfo8Vcpump
Sent at 79.5k mc
gmgn.ai/sol/token/6p3Y3WBXcV…
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We are currently testing the new Machine Learning Model (MLM) PICK SIGNAL and have not yet released it to Premium members.
The reason is simple: MLM still needs more time to learn from AI Paper Trading results and MLM self-feedback data. While the current results are encouraging, we believe the model will continue to improve as more training data becomes available.
At the moment, Hype Radar Bot already includes AI Paper Trading signals, but MLM Pick Signals are not yet part of the bot. We want to ensure the model has sufficient real-world outcome data before making its picks available to Premium members.
The MLM is continuously learning from historical market data, AI Paper Trading outcomes, group formations, signal convergence, and feedback records. As the dataset grows, the model becomes better at identifying the patterns and conditions that historically led to stronger outcomes.
Once we have collected enough additional data and are satisfied with the model's performance, MLM Pick Signals will be integrated into Hype Radar Bot for Premium members.
Our goal is not to release it quickly, but to release it when it is ready.
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🧠 AI Development Update
Current stats:
📊 612,000 feature samples
📝 1,200 trading decisions
📈 150 completed paper trades
💰 Positive realized PnL
One of the most encouraging developments is that the AI is no longer just generating scores.
It's starting to adapt its behavior based on actual trade outcomes.
Recent paper trades show increasing use of:
✅ Trailing profit protection
✅ Profit floor protection
✅ Peak-based exit management
Rather than relying solely on fixed take-profit and stop-loss rules, the system continuously evaluates how different exit behaviors perform and feeds those results back into the learning process.
Every BUY, PASS, win, loss, and exit outcome becomes additional training data.
As a result, the model isn't simply collecting more samples.
It's continuously refining:
• Feature weights
• Pattern confidence
• Buy thresholds
• Exit decisions
The model sample count keeps increasing because every new signal, decision, and outcome expands the training dataset.
The goal has never been to build a bot that follows static rules.
The goal is to build a system that learns which signal combinations and trade management decisions consistently perform best under real market conditions.
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🚀 AI Development Update
Over the past few months, I've been building and testing a self-learning AI engine using both historical signal data and live paper-trading results.
The system was not started from zero.
Before making any paper-trading decisions, the AI was pre-trained using approximately 6 months of historical market data collected from:
• aggregated.json (signal history)
• coin-outcomes.json (final coin performance data)
This gave the AI access to tens of thousands of historical signal and outcome examples before it ever entered the live paper-trading phase.
Current dataset:
📊 600,000 feature samples analyzed
📈 6 months of historical signal/outcome data
🎯 90 completed paper trades
📝 900 ML training records collected and growing daily
The current AI uses a self-learning scoring engine.
Every signal is broken down into features such as:
• Signal family
• Signal stage
• Group formations
• Market cap ranges
• DEX paid status
• Market conditions
• Smart wallet activity
• Structure patterns
The AI continuously tracks which features and feature combinations perform well and which ones fail.
Successful patterns receive higher weights over time, while underperforming patterns receive lower weights and penalties based on actual results.
In addition, every BUY, PASS, and final trade outcome is stored in a growing machine-learning dataset.
This means the system is already learning from both:
Historical data (6 months of archived signals and outcomes)
Live paper-trading experience
🧠 What's Next?
The current version uses a self-learning statistical engine.
The next milestone is training true Machine Learning models (XGBoost / LightGBM) using the growing dataset being generated right now.
The goal is to move from:
"We think these signals work."
to
"The model has statistically learned which signal combinations historically produce the highest probability of success."
We're not building a bot that follows fixed rules.
We're building a system that learns which rules actually work.
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One additional note:
The "Model Samples" count keeps increasing because the AI is continuously learning from new signals, decisions, and outcomes in real time.
Every new signal it observes becomes additional training data, allowing the system to refine its understanding of which patterns work and which don't.
In other words, the AI is not static. It continues to learn and expand its knowledge base as more market data flows through the system.
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🔥 STRUCTURE MEGA EDGE
Not every Expansion becomes a runner.
STRUCTURE MEGA EDGE is designed to identify the rare expansions where multiple high-quality factors align at the same time.
Requirements:
🚀 Structure Expansion
🧬 Strong Core Formation
🏆 Quality Core Detected
⚡ Edge Candidate
In other words:
Multiple quality groups appear early,
core groups begin clustering,
and the structure continues expanding instead of fading.
━━━━━━━━━━━━
What makes it special?
Most expansions stop after the initial move.
MEGA EDGE looks for expansions that continue attracting quality attention AFTER the structure is already formed.
Think:
Structure Expansion
➡️ Core Formation
➡️ Quality Core
➡️ Edge Candidate
➡️ Potential Runner
━━━━━━━━━━━━
Example:
🔥 Strong Core Formation 3/4
🏆 Quality Core Detected
⚡ Structure Edge Candidate
🚀 Structure Expansion
When all four conditions align, the probability of a sustained move increases significantly.
Not every MEGA EDGE becomes a moonshot.
But most large runners start with multiple quality groups reaching consensus before the market fully reacts.
$GOLEM
CA: 4t7WWuMmGbLzmUCHwjchtFW6DMNASLTJh3YRMBfppump
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🚀 STACK Signal Update
STACK no longer follows a fixed route or specific call sequence.
Instead, it detects when high-quality groups converge on the same mint using:
⚡ Edge Quality Score
⚡ Strong / Core Group Overlap
⚡ Fast Quality-Set Clustering
When multiple strong/core groups converge within a short time window, market attention often follows quickly. STACK is now focused on quality-group convergence rather than noisy call chains.
📌 Premium Member Note
STACK is designed to identify high-quality momentum formation, not necessarily the perfect entry.
In many cases, a pullback or dip occurs shortly after the signal appears as early buyers take profits.
Avoid chasing green candles. Be patient, wait for a favorable entry, and manage risk accordingly.
The signal identifies opportunity. The entry is still your job.
$RETARD, Retard Coin
CA: ACuZX4asxyqcRd6BTgGBKXJjViUP3kZQuDUQawBapump
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Why do ppl buy this? $Orange 15K mc
ca: 3MhmXovYu5rbkzS7jf9UxcLWVUUrZuVbU6NfpgitLqNG
My bot says many wallets bought and are holding this
gmgn.ai/sol/token/3MhmXovYu5…
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