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repliedto ghostai1's post about 14 hours ago
# Edge AI technical challenges: A Deep Dive As we continue to push the boundaries of artificial intelligence (AI), we find ourselves at the forefront of a technological revolution. One of the most exciting areas of AI development is Edge AI, which involves processing data at the edge of the network, rather than in the cloud. This approach offers numerous benefits, such as reduced latency, improved security, and decreased reliance on expensive cloud resources. However, the implementation of Edge AI is not without its technical challenges. For instance, one major hurdle is the need for powerful edge devices capable of handling the data processing requirements of Edge AI. These devices must be able to handle real-time data analysis and decision-making, which can be quite demanding. Another challenge lies in the complexity of deploying and managing multiple edge devices. In a traditional cloud-based model, this is relatively straightforward, but with Edge AI, it becomes a much more complicated task. Developers need to ensure that these devices are properly synchronized and that data is consistently distributed across them. Despite these challenges, Edge AI has the potential to revolutionize the way we interact with technology. It offers the opportunity to create more intelligent, autonomous systems that can operate in real-time, without the need for constant communication with a centralized server. With the right approach and technical solutions, we can overcome these challenges and unlock the true power of Edge AI.
repliedto ronantakizawa's post 1 day ago
Introducing the trending-stocks-yahoo-finance dataset: a compilation of the most trending stocks on Yahoo Finance from July 2024 to October 2025. This dataset captures each trending stock's max price, max market cap, best rank on Yahoo Finance, PE ratio, and trading volume. #stocks #investing #trading https://huggingface.co/datasets/ronantakizawa/trending-stocks-yahoo-finance
repliedto tegridydev's post 3 days ago
Open-MalSec v0.1 – Open-Source Cybersecurity Dataset Evening! 🫡 📂 Just uploaded an early-stage open-source cybersecurity dataset focused on phishing, scams, and malware-related text samples. This is the base version (v0.1)—a few structured sample files. Full dataset builds will come over the next few weeks. 🔗 Dataset link: https://huggingface.co/datasets/tegridydev/open-malsec 🔍 What’s in v0.1? A few structured scam examples (text-based) Covers DeFi, crypto, phishing, and social engineering Initial labelling format for scam classification ⚠️ This is not a full dataset yet (samples are currently available). Just establishing the structure + getting feedback. 📂 Current Schema & Labelling Approach "instruction" → Task prompt (e.g., "Evaluate this message for scams") "input" → Source & message details (e.g., Telegram post, Tweet) "output" → Scam classification & risk indicators 🗂️ Current v0.1 Sample Categories Crypto Scams → Meme token pump & dumps, fake DeFi projects Phishing → Suspicious finance/social media messages Social Engineering → Manipulative messages exploiting trust 🔜 Next Steps - Expanding datasets with more phishing & malware examples - Refining schema & annotation quality - Open to feedback, contributions, and suggestions If this is something you might find useful, bookmark/follow/like the dataset repo <3 💬 Thoughts, feedback, and ideas are always welcome! Drop a comment or DMs are open 🤙
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