Syed Sabeel(@syedsabeelahmad) meglátásai

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#BTCBreaks100K? #SOLHitsATH #ETHPriceSurge 

Felelősségkorlátozó nyilatkozat: Harmadik felek véleményét tartalmazza. Nem minősül pénzügyi tanácsnak. Szponzorált elemet tartalmazhat. Lásd a Feltételeket.

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Which cryptocurrencies are expected to perform well in the next bull market ?

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Best Crypto Asset Allocation 👍

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$BTC 🔥 100K this Year❓ #BTC☀

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$XRP Predict XRP Price End Of The Year ?#XRPGoal

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Here's how blockchain plays a role in shaping the future of AI: 🤖 1. Data Integrity and Trust* - *Challenge*: AI systems rely on massive datasets, but data integrity, authenticity, and security are critical challenges. - *Blockchain's Role*: - Ensures data provenance and immutability, preventing tampering or manipulation of training data. - Provides an auditable record of how data has been collected, shared, and used, fostering trust in AI models and their outcomes. 2. Decentralized AI* -*Challenge*: Centralized AI systems are controlled by large corporations, raising concerns about transparency and monopolization. - *Blockchain's Role*: - Enables decentralized AI marketplaces where developers, organizations, and individuals can share or monetize AI models and data securely. - Facilitates collaborative AI training across decentralized nodes without compromising data privacy. 3. Data Privacy and Ownership* - *Challenge*: AI often requires access to personal or sensitive data, leading to privacy concerns. - *Blockchain's Role*: - Empowers individuals to retain ownership of their data using blockchain-based identity systems. - Implements secure, permissioned access to data for AI training while protecting privacy through encryption or zero-knowledge proofs. -The Deep Interest Network (DIN) :- 1. *Adaptive, Context-Aware Processing*: DIN's modular pre-processing layer dynamically generates features based on real-time user behavior and contextual relevance, ensuring highly personalized and accurate insights. 2. *Scalability and Flexibility*: Its modular design supports diverse data types, seamless customization, and efficient handling of large-scale datasets, making it applicable across industries and use cases. 3. *Optimised Data Quality*: By automating data cleaning, enrichment, and noise reduction, it ensures high-quality inputs for downstream models, enhancing predictive performance and decision-making accuracy. Thanks for Reading 📖 #GODINDataForAI #DIN #BinanceWeb3Airdrop

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Report: 9 New Bitcoin Spot ETFs Acquire 826,792 BTC Since Launch in the U.S

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Farcaster Co-Founder Highlights Influence Of Banks On Fintech And Crypto Policies

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