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# TOKEN
7.91M
77AY777
#RAVE
⚠️ CRITICAL STRUCTURE
• 1 wallet: 79.6% supply (ETH)
• 1 wallet: 27.19% supply (BNB)
• Top 2 wallets combined: ~85%+ dominance
👉 This is no longer a "coin" — it is a fully centralized asset
💡 Bottom line (REAL TALK):
Such coins never achieve long-term success.
This model is classic:
• First, they accumulate
• Then they create hype
• Retail buys in
• Owners dump and exit
👉 In plain language:
They set traps, sit back, and wait for the crowd to buy in.
❌ Risks
• 1-2 wallets can dump everything
• Liquidity is artificially manage
⚠️ CRITICAL STRUCTURE
• 1 wallet: 79.6% supply (ETH)
• 1 wallet: 27.19% supply (BNB)
• Top 2 wallets combined: ~85%+ dominance
👉 This is no longer a "coin" — it is a fully centralized asset
💡 Bottom line (REAL TALK):
Such coins never achieve long-term success.
This model is classic:
• First, they accumulate
• Then they create hype
• Retail buys in
• Owners dump and exit
👉 In plain language:
They set traps, sit back, and wait for the crowd to buy in.
❌ Risks
• 1-2 wallets can dump everything
• Liquidity is artificially manage
- Reward
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- 4
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SheenCrypto
:
To The Moon 🌕:View More
$TOKEN, Added a spot bag here incase we get a RWA narrative + the chart looks good.
• Price holding 1D support and showing a clean deviation + reclaim around the daily BOS level, triggering this entry.
Invalidation comes on a close below the 1D BOS level.
Let's see if we get some rotations from BTC.
#TOKEN TOKENUSDT
• Price holding 1D support and showing a clean deviation + reclaim around the daily BOS level, triggering this entry.
Invalidation comes on a close below the 1D BOS level.
Let's see if we get some rotations from BTC.
#TOKEN TOKENUSDT
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GateUser-b476c76c:
Is there still hope for this coin? Every day I see no movement, and even the roadmap that came out is just so-so.:Starting from first principles: Why #AI Trading should not predict price movements
1. Breaking down AI: What are large models really doing?
Many people consider large models as "thinking black boxes," but from a computational perspective, they do only one thing:
Calculate similarity in high-dimensional vector space.
All inputs (#token , images, time series) are mapped into vectors;
All "understanding" and "reasoning" are essentially vector dot products + nonlinear transformations.
The core of Transformer is not "intelligence," but:
Compress inputs into vectors
Compute similarities between vect
View Original1. Breaking down AI: What are large models really doing?
Many people consider large models as "thinking black boxes," but from a computational perspective, they do only one thing:
Calculate similarity in high-dimensional vector space.
All inputs (#token , images, time series) are mapped into vectors;
All "understanding" and "reasoning" are essentially vector dot products + nonlinear transformations.
The core of Transformer is not "intelligence," but:
Compress inputs into vectors
Compute similarities between vect
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Chapter10
:
Lost 700,000 from v5 to v0?:- Reward
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vinay_nandishettar:
#AMR##AMR# big pump breakout buy quick👆🔥🙈🔥😍😅#CryptoMarketMildlyRebounds##GateChristmasVibes##2025GateYearEndSummary#:View More
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