Echo

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Echo

@0xEcho0

artist chronically online degenerate

online Katılım Kasım 2025
12 Takip Edilen48 Takipçiler
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Echo
Echo@0xEcho0·
I've recently switched to Axiom for all my trading on memes @solana @bnbchain If you are not already signed up and want to support, feel free to use my Referral link, thanks! 👉 @0xecho" target="_blank" rel="nofollow noopener">axiom.trade/@0xecho
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skill
skill@skillnsol·
GIF
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Echo
Echo@0xEcho0·
@_bolivian why fees?? are we this slow?? great narrative send the cashback
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Echo
Echo@0xEcho0·
@morphgenz Got a comm, have a dex credit as well that im gonna use hang tight
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Echo
Echo@0xEcho0·
@morphgenz we need to start sending actual memes like this again. whos got the xcomm? i'll ask around.
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Echo
Echo@0xEcho0·
@fiveclawapp W dev. No tech exists like this, and we're hot on @printr Let's see what you have in store for us.
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fiveclaw
fiveclaw@fiveclawapp·
Wrong X was added on DEX, now fixed. If it still shows the old one, clear your cache or check from another browser. The correct X is already updated.
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Echo
Echo@0xEcho0·
No matter the chain. Lock in.
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Echo
Echo@0xEcho0·
@Aejo 3cchZ5dHPj8Ao7JMWJz142LddpPnqfab1PxZekK9pump ape this and keep endorsing it, it will send
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Aejo
Aejo@Aejo·
trying to recompile my soul into something less on-fire
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Echo
Echo@0xEcho0·
@DantePickss Yeah I’m confused, I’m not selling
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Echo
Echo@0xEcho0·
@br6xs Which wallet have you locked fees too?
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Brax
Brax@br6xs·
CLOSE FRIEND OF ELON JUST TWEETED NEW VERSION OF AGI??? ELON LITERALLY REPLIED HIM YESTERDAY ISNT THIS INSANE? NEW AGI - MSA
Mark Kretschmann@mark_k

MSA: A Breakthrough in Native AI Long-Term Memory EverMind, a Chinese AI startup focused on agent memory, has released a major new paper and open-source project called MSA - Memory Sparse Attention. This innovative system embeds true long-term memory directly into the attention mechanism, allowing large language models to remember natively without external retrieval hacks or brute-force context windows. Previous approaches have notable shortcomings. Traditional RAG works like an open-book exam where the model must constantly retrieve information and often fails to connect scattered details across documents, while linear attention and KV-cache methods simply compress memory and become increasingly fuzzy as context grows longer. MSA takes a different approach. It uses a scalable sparse attention architecture with linear complexity so the model efficiently learns to focus on what matters, and it adds document-wise RoPE plus a Memory Interleaving mechanism for natural boundary understanding and true multi-hop reasoning across fragments. The results are outstanding. Context length scales from 16K to 100 million tokens with less than 9% accuracy drop, and a compact 4B-parameter MSA model outperforms much larger 235B-parameter RAG systems on long-context benchmarks. via @elliotchen100

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Echo
Echo@0xEcho0·
@loggdev this is the only ca worth bidding, the rest are larps E2Y3Ze4xD6fZzmUc4xsyzbapeNXs8cvz3GiSYm1ypump
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Echo
Echo@0xEcho0·
@bil0090 I'd recommend making a tweet about the coin, it will perform much better.
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Echo@0xEcho0·
@VARDUSAI1 @Junaidatta0 github looks good but did you post wrong wallet? can't find this on solscan
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Echo
Echo@0xEcho0·
@realDonaldTrump just posted the chart of Illegal Immigration into the U.S in his Telegram channel and truth social. He called it THE GREATEST CHART OF ALL TIME Lets send Immigrate on USD1 $Immigrate @realDonaldTrump/posts/116155707171801027" target="_blank" rel="nofollow noopener">truthsocial.com/@realDonaldTru…
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Keşfet

@koopatroopwa @skillnsol @_bolivian @morphgenz @fiveclawapp @printr @Aejo @0xthembi