Learn Bittensor (@learnbittensor) 's Twitter Profile
Learn Bittensor

@learnbittensor

Empowering the Bittensor community through accessible knowledge sharing. Explore, learn, and master $TAO with guides, articles, and other resources. 🧠🌐

ID: 1776031405941706752

linkhttps://learnbittensor.org calendar_today04-04-2024 23:38:11

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2,2K Followers

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Did you know that Bittensor's Halving works different than Bitcoin's? Unlike Bitcoin's fixed schedule, $TAO's halving gets delayed through "Recycling"! ♻️ Halving: TAO halving occurs when half of the remaining supply is mined (starting from 21M tokens). When this happens, mining

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In December 2024 alone, Subnet 51 processed approx. $282,834.39 (~ 564.54 TAO) in rental fees, distributed among 21 validators! But what is Subnet 51/Celium? 💻 Subnet 51 on #Bittensor is a marketplace where people can rent GPU computing power. Miners provide their

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🚨 Dynamic TAO (dTAO) launches on testnet today! The revolutionary update to #Bittensor's staking system is getting closer. Here's what you need to know 👇: Dynamic TAO puts YOU in control of network emissions. Instead of validators deciding where your stake goes, you directly

🚨 Dynamic TAO (dTAO) launches on testnet today!

The revolutionary update to #Bittensor's staking system is getting closer. Here's what you need to know 👇:

Dynamic TAO puts YOU in control of network emissions. Instead of validators deciding where your stake goes, you directly
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🔥 Experience Dynamic TAO Yourself! There's no better way to learn about dTAO than testing it right now! We've prepared a comprehensive guide to get you started on #Bittensor testnet. Two simple ways to participate: - BTCLI (Terminal-Based) - Polkadot.JS (Browser-Based) The

🔥 Experience Dynamic TAO Yourself!

There's no better way to learn about dTAO than testing it right now! We've prepared a comprehensive guide to get you started on #Bittensor testnet.

Two simple ways to participate:
- BTCLI (Terminal-Based)
- Polkadot.JS (Browser-Based)

The
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✨ Subnet Directory Just Got Better! Discover Bittensor subnets easier than ever with our redesigned directory: 🏷️ New Features: - New intuitive layout, with more information - Filter subnets by tags (e.g Text, Audio, Training) - Find all subnets developed by a team Looking

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⏰ Dynamic TAO could launch on mainnet in ~2 weeks! We want to ensure everyone understands dTAO clearly before the big update. What's still unclear to YOU about Dynamic TAO? - Subnet tokens? - Staking mechanics? - Root staking? - Price impact? - Something else? Drop your

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📉 What is Root Proportion in Dynamic TAO? Root Proportion determines how validator rewards are split between TAO staked to root and ALPHA staked to subnets. Early on, root nominators earn the majority of rewards, but as subnets grow and more ALPHA enters circulation, rewards

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🌱 Understanding Emissions in Dynamic TAO Emissions are distributing new TAO and ALPHA tokens every block. Here's the breakdown how its done: TAO Emissions Each subnet earns TAO proportional to its pool’s share of total staked TAO. More TAO in a subnet’s pool = larger slice of

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What would make 'Learn Bittensor' more valuable to YOU? Is there something you'd like to learn, explore, or do on the platform? Let us know your thoughts below!👇 Your feedback helps us improve: learnbittensor.org

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🗞️🗞️🗞️ Exciting announcement (they just keep coming): Today we are thrilled to share that @LatentHoldings has acquired @LearnBittensor, while retaining Maciej Kula's leadership and vision. As our "Head of Education", Maciej will continue driving Learn Bittensor's mission to

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✨ Learn Bittensor Got a Complete Makeover! Our platform just received a major redesign to make Bittensor more accessible than ever. 🎨 What's New: - Clean, modern interface with improved navigation - Enhanced search functionality across all resources - Better content

✨ Learn Bittensor Got a Complete Makeover!

Our platform just received a major redesign to make Bittensor more accessible than ever.

🎨 What's New:
- Clean, modern interface with improved navigation
- Enhanced search functionality across all resources
- Better content
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📉 Templar (SN3): Incentivizing Loss Reduction The miners on subnet 3 just completed training a 1.2 billion parameter model through competitive loss reduction. Every 84 seconds, miners perform real training work on assigned data pages, measuring the model's mistakes (called

📉 Templar (SN3): Incentivizing Loss Reduction

The miners on subnet 3 just completed training a 1.2 billion parameter model through competitive loss reduction.

Every 84 seconds, miners perform real training work on assigned data pages, measuring the model's mistakes (called