또🐐

[또🐐 @snxka12]

I just claimed some AVAIL. Time to unify web3. https://t.co/ORraeQzyO2 출처 @availproject

[또🐐 @snxka12]

I survived the bear market and claimed my $FRAME tokens!

@frame_xyz is the Layer 2 for creators and collectors. If you've traded NFTs on Ethereum and paid royalties in the past two years you're eligible! 🖼️🎄

You can check here 👇 https://t.co/Ffo1ZBzLGw

[또🐐 @snxka12]

@AvaxWixard Wen lug?

[또🐐 @snxka12]

@Rait_io Good nice

[또🐐 @snxka12]

@Pchild_NFT @Turtsat @Svarga_cc bc1qkr69k5hpqmmrkhjlaml5r8p76ppm6qfll8fmx7

[Wormhole @wormhole]

Summoning the @MadLadsNFT to the Wormhole Discord.

WAO

https://t.co/VN5uZzqXG4

[Colonel Roy Mustang @ShogunMasterRoy]

Bittensor $TAO VS Commune $COM 💻 - A comprehensive comparison

There are a lot of arguments on CT about which one is better, @bittensor_ the OG or @communeaidotorg, a heavily modified fork. After doing a deep dive on both, here is my objective analysis

FYI - I am invested in both and I believe in a world where both Pepsi & Coca-Cola exist, so why should it be one and not the other?

Meet the Pioneers of Blockchain-ML Integration -
Bittensor $TAO: Introduces a decentralised network specifically for machine learning, focusing on creating a global neural network. It emphasises incentivizing data sharing and model training across a distributed ledger.
Commune AI $COM: Presents a modular framework for ML, stressing on interoperability and reusability of ML models. It aims to create a more open and collaborative ML environment, breaking away from platform-centric models.

Technical Architecture: Building the Foundations
Bittensor $TAO: Built around a unique neural blockchain network. It utilizes specialized nodes (neurons) that communicate and collaborate for ML tasks, incentivized through a custom token system.
Commune AI $COM: Develops around the 'Modulus' framework, focusing on modular and interoperable ML components. This allows for greater flexibility and scalability in integrating various ML tools and environments.

Module/Node Structure: The Core Units
Bittensor $TAO: Each node in the network acts independently, contributing to the overall ML process. Nodes are rewarded based on their contribution, fostering a competitive yet cooperative ecosystem.
Commune AI $COM: Introduces Module Blocks as core units, which are highly versatile and support multiple inputs and outputs. This encourages the development of more adaptable and scalable ML models.

Data Management and Storage: Securing and Utilizing Information
Bittensor $TAO: Focuses on decentralised data storage and management, leveraging blockchain's inherent security features. This ensures data integrity and accessibility across the network.
Commune AI $COM: Offers a robust file-system for modules, enabling organized and efficient data management. This enhances the deployment and maintenance process of ML modules.

API and User Interaction: Bridging Users and Technology
Bittensor $TAO: Provides a unique API that interacts with the neural blockchain network, allowing users to access and contribute to the ML process easily.
Commune AI $COM: Features a comprehensive Module Manager API for overseeing module activities, offering a user-friendly and intuitive interface for managing ML operations.

Interoperability and Connectivity: Expanding the Network
Bittensor $TAO: Each neuron/node in the network can connect and communicate with others, forming a cohesive and dynamic ML network.
Commune AI $COM: Emphasizes seamless connectivity between modules, both locally and remotely, facilitating a more collaborative and interactive ML environment.

Security and Governance: Protecting the Ecosystem
Bittensor $TAO: Implements robust security measures to protect the integrity of the neural network and its data.
Commune AI $COM: Focuses on secure module access control and implements smart contracts to ensure compliance and governance in module interactions.

Tokenomics and Incentive Structures: Fueling Participation
Bittensor $TAO: The TAO token is central to the ecosystem, incentivising nodes for their contributions to the ML network. $TAO token plays a central role in its ecosystem. It incentivises nodes (neurons) for their contributions to the ML process, creating a token-based economy that rewards data sharing and model training. This approach encourages active participation but may also introduce challenges related to token distribution and value stability.
Commune AI $COM: While not relying on a native token for its core operations, it allows developers to monetize their modules and interactions in various ways, providing financial incentives for participation.
$COM's approach to tokenomics is less direct, as it does not rely on a native token for its core operations. However, it allows for the monetization of modules and interactions, which can provide financial incentives for developers and contributors. This approach focuses more on the utility and market value of individual modules rather than a centralized token economy.

Scalability and Future Prospects: Looking Ahead
Bittensor $TAO: Aims to scale up its neural network to create a truly global and decentralized ML ecosystem.
Commune AI $COM: Focuses on expanding its modular framework to accommodate a wider range of ML tools and applications, aiming for a more open and collaborative ML future.

Pros of Commune AI $COM:
Modular Framework: Offers great flexibility and scalability in ML development, enabling easier integration of various tools and methodologies.
Interoperability: Its focus on interoperability makes it easier to use and integrate with existing ML systems and tools.
User-Friendly: The platform is designed to be accessible to a broad audience, from beginners in ML to experts.
Efficient Data Management: The organised module file-system enhances the ease of deployment and maintenance.
Innovation-Friendly: The open and collaborative approach encourages innovation and sharing in the ML community.
Cons of Commune AI $COM:
Dependency on Community Engagement: The success of the platform heavily relies on active community participation and contribution.
Lack of Native Token Incentivisation: Without a native token system, the platform might lack a direct incentivisation mechanism for contributors.
New Market Player: Being relatively new, it may face challenges in gaining widespread adoption and trust.
Pros and Cons of Bittensor's $TAO Protocol

Pros of Bittensor $TAO:
Decentralised Neural Network: Creates a unique and innovative approach to ML, leveraging the power of a global neural network.
Token Incentivisation: The TAO token system incentivises participation and contribution, motivating developers and data scientists.
Data Security and Integrity: Utilizes blockchain's security features for data management, ensuring integrity and reliability.
Scalability: Aims to scale globally, potentially leading to a vast and powerful decentralized ML network.
Established Presence: As an earlier market entrant, it may benefit from greater recognition and trust in the crypto and ML communities.

Cons of Bittensor $TAO:
Complexity: The concept of a decentralized neural network may be complex for new users to grasp and engage with.
Competitive Environment: The token-based incentivisation could create a highly competitive environment, possibly leading to centralisation tendencies among more powerful nodes.
Resource Intensiveness: Operating a node might require significant computational resources, potentially limiting broader participation.

Conclusion: Trailblazers in Their Own Right
Bittensor $TAO and Commune AI $COM both represent significant advancements in integrating blockchain with machine learning.
While Bittensor focuses on creating a decentralised neural network incentivised through tokenomics, Commune AI emphasizes a more open, modular approach, offering flexibility and scalability in ML development. Both projects hold the potential to revolutionize how machine learning and blockchain technologies converge and interact.

Back to the analogy, where in an ideal world, both Pepsi and Coca-Cola can co exist. Excited to see how both scale and grow

[Wormhole @wormhole]

Wormhole has secured $225 million in funding. Read more here:

https://t.co/qRL109mNVg

[Wormhole Portal @portalbridge_]

📢The Portal redesign is live in beta!

Portal now natively embeds Wormhole Connect to offer asset bridging with Gasless Bridging and Gas Dropoff. Check out the revamped bridging UX and app design here: https://t.co/pNTqnmC9KJ.

[Algod @AlgodTrading]

The biggest question is what will trigger retail capital injection

Majority of the world already heard about crypto, if they had any interest they would have bought and gotten rekt past cycle

[Sungjae @sungjae_han]

seeing $botto, $mai, and $tao rip, i'm formulating a new thesis based upon them

"people have an unexplainable desire to take part in growing and formulating ai autonomous agents"

- this maybe due to subconsciously being exposed to ideas such as roko's basilisk/ai takeovers
- after all, we are all made in the image of God, and as God created mankind, we also have an innate desire to create intelligence that somewhat mirrors our image.

crypto allows us to do this by putting our capital onto it to grow its intelligence - all while profiting from it as well

[또🐐 @snxka12]

@Memeland GM

[또🐐 @snxka12]

@Era_Lend 40usdt?? lmao
I lost 4600usdt because of you

[또🐐 @snxka12]

@Kuma_meme_ 0xE7Ec4F8f763f6850838f24Ffed555143aB26918E

[또🐐 @snxka12]

@Kuma_meme_ 0xE7Ec4F8f763f6850838f24Ffed555143aB26918E

[또🐐 @snxka12]

@Kuma_meme_ 0xE7Ec4F8f763f6850838f24Ffed555143aB26918E

[또🐐 @snxka12]

@Kuma_meme_ 0xE7Ec4F8f763f6850838f24Ffed555143aB26918E

[또🐐 @snxka12]

@Kuma_meme_ 0xE7Ec4F8f763f6850838f24Ffed555143aB26918E

[또🐐 @snxka12]

@Kuma_meme_ 0xE7Ec4F8f763f6850838f24Ffed555143aB26918E

[또🐐 @snxka12]

@Kuma_meme_ 0xE7Ec4F8f763f6850838f24Ffed555143aB26918E