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🔥 Shiba Inu: What’s SHIB’s Price If 99% of Tokens Are Burnt? 😱
👀 Shiba Inu’s (SHIB) massive supply is one of the most significant barriers to its price. There are about 589 trillion SHIB tokens in circulation right now. If the asset’s price goes too high, the project’s market cap will reach unrealistic figures.
👀 If 99% of all SHIB tokens are burnt, the project will have about 5.89 trillion tokens. Let’s consider that the project’s market cap remains at $14.68 billion. In such a scenario, the price of each token will be $0.00249 ($14.68 billion / 5.89 trillion). Reaching $0.00249 from current price levels will translate to a growth of about 9883.9%.
📢 What are your thought on the pullback?
👀 The Bitcoin pullback is a healthy correction after a strong rally. It's an opportunity for buyers to accumulate and for the market to consolidate before potentially resuming its upward trend.
#MarketBuyOrHold? $BTC $BNB
🔥🔥🔥 Let's Learn & Earn Together!
👀 DIN: REVOLUTIONIZING AI DATA PRE-PROCESSING WITH MODULAR INNOVATION
The Data Intelligence Network (DIN) is setting a new standard in AI data pre-processing as the first modular AI-native solution. This groundbreaking approach addresses one of the most critical yet often overlooked aspects of artificial intelligence development: the preparation and transformation of raw data into structured formats suitable for machine learning models.
Traditionally, data pre-processing has been a complex, time-consuming, and resource-intensive process. DIN disrupts this paradigm by introducing a modular architecture that allows seamless integration with various AI pipelines. Its plug-and-play design empowers developers and data scientists to select and customize modules tailored to specific tasks such as data cleaning, normalization, augmentation, and feature engineering.
The AI-native nature of DIN enables it to leverage machine learning models within its framework, optimizing data pre-processing workflows dynamically. By analyzing data in real-time, DIN identifies inconsistencies, highlights anomalies, and suggests appropriate transformations, significantly reducing manual intervention. This results in faster project turnarounds and enhances the quality of input data, leading to more accurate and robust AI model performance.
Moreover, DIN’s modularity promotes scalability and flexibility, making it adaptable for diverse industries, from healthcare to finance and beyond. By breaking down traditional silos and streamlining data workflows, DIN is democratizing access to high-quality AI solutions, even for organizations with limited technical expertise.
As AI continues to shape the future, DIN’s innovation in pre-processing is pivotal, bridging the gap between raw data and actionable insights while redefining efficiency, accuracy, and accessibility in the AI landscape. #GODINDataForAI
#BinanceWeb3Airdrop #DIN @DIN Data Intelligence Network
👀 If 99% of all SHIB tokens are burnt, the project will have about 5.89 trillion tokens. Let’s consider that the project’s market cap remains at $14.68 billion. In such a scenario, the price of each token will be $0.00249 ($14.68 billion / 5.89 trillion). Reaching $0.00249 from current price levels will translate to a growth of about 9883.9%.
📢 What are your thought on the pullback?
👀 The Bitcoin pullback is a healthy correction after a strong rally. It's an opportunity for buyers to accumulate and for the market to consolidate before potentially resuming its upward trend.
#MarketBuyOrHold? $BTC $BNB
🔥🔥🔥 Let's Learn & Earn Together!
👀 DIN: REVOLUTIONIZING AI DATA PRE-PROCESSING WITH MODULAR INNOVATION
The Data Intelligence Network (DIN) is setting a new standard in AI data pre-processing as the first modular AI-native solution. This groundbreaking approach addresses one of the most critical yet often overlooked aspects of artificial intelligence development: the preparation and transformation of raw data into structured formats suitable for machine learning models.
Traditionally, data pre-processing has been a complex, time-consuming, and resource-intensive process. DIN disrupts this paradigm by introducing a modular architecture that allows seamless integration with various AI pipelines. Its plug-and-play design empowers developers and data scientists to select and customize modules tailored to specific tasks such as data cleaning, normalization, augmentation, and feature engineering.
The AI-native nature of DIN enables it to leverage machine learning models within its framework, optimizing data pre-processing workflows dynamically. By analyzing data in real-time, DIN identifies inconsistencies, highlights anomalies, and suggests appropriate transformations, significantly reducing manual intervention. This results in faster project turnarounds and enhances the quality of input data, leading to more accurate and robust AI model performance.
Moreover, DIN’s modularity promotes scalability and flexibility, making it adaptable for diverse industries, from healthcare to finance and beyond. By breaking down traditional silos and streamlining data workflows, DIN is democratizing access to high-quality AI solutions, even for organizations with limited technical expertise.
As AI continues to shape the future, DIN’s innovation in pre-processing is pivotal, bridging the gap between raw data and actionable insights while redefining efficiency, accuracy, and accessibility in the AI landscape. #GODINDataForAI
#BinanceWeb3Airdrop #DIN @DIN Data Intelligence Network
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