With gemini 2.5 pro pricing and results, Google has fixed the biggest unknown/weakest link in their lineup
and we can now confirm that @GoogleDeepMind completely owns the pareto frontier down to 1220 elo
(at least until o4-mini and gpt5?)
😎 10,000,000 USERS IN 3 DAYS 😎
Don't miss this next NOT coin project.
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Join the DOGS movement and send it to 100M. #DOGS#DOGScommunity
💻 Run a ZKsync Node Locally 🧵
The ZKsync node is a read replica of the main (centralized) node that anyone can run. It fetches data from the ZKsync API and re-applies transactions from the Genesis block.
🔥 Treasure Hunt Time! Stake on Holdstation, Earn Bonus Mainnet #GoatTech Points!
Goats Assemble! The wait is over, @GoatxTech 's Mainnet is live!
Earn bonus Mainnet Points and 5 exclusive Treasure Chests with #Holdstation.
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👉 Download Holdstation Wallet (IOS|Android)
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The more you stake between May 15th and June 6th, the more Mainnet Points you'll earn!
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→ Open #Holdstation Wallet app
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📢 #zkStarter Announcement
We're thrilled to unveil our upcoming launchpad: @AutoAirAI, a revolutionary force in #airdrop hunting, powered by #AI 🔥
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🚄 New Fat Cat's Coming to #Holdstation's Train
Holdstation is thrilled to announce our partnership with @zkzorro! We've integrated $ZORRO, a community-driven native memecoin of #zkSync Era into our Paymaster feature.
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#GECKOINUAVAX
🔥 #Holdstation is now partnering with @GeckoInuAvax for an exclusive event!
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Principled Instructions for LLMs
Nice set of guiding principles to improve and enhance the quality and reliability of LLM responses.
Shows the effectiveness of the principled instructions and prompt designs across model sizes and scenarios.
Tested on Llama 1/2 (7B, 13B, and 70B) and GPT-3.5/4. (see examples in the figure)
It's well known that prompt optimization can lead to significant performance gains. If you are building or researching with LLMs, this is a great read.
https://t.co/4c4VBI6llk
I just uploaded a 90 minute tutorial, which is designed to be the one place I point coders at when they ask "hey, tell me everything I need to know about LLMs!"
It starts at the basics: the 3-step pre-training / fine-tuning / classifier ULMFiT approach used in all modern LLMs.
While large language models appear to have a rich understanding of the world, how do we know they’re not simply regurgitating from training data? Check out the latest AI Explorable on a phenomenon called grokking to learn more about how models learn. → https://t.co/Okc9GvJjuN