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🚨 WormGPT To Launch Attacks!

Latest Midjourney and DALL-E Prompts for creating stunning images

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👀 AI Happenings...

  • 🔫 Israel Quietly Embeds AI Systems in Deadly Military Operations (link)

  • 😎 Google expands AI service to 59 countries (link)

  • 😲WormGPT: New AI Tool Allows Cybercriminals to Launch Sophisticated Cyber Attacks (link)

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  • Noty AI: Meeting transcription software for Google Meet and Zoom meetings. (link)

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  • Voicemod: Best free voice-changing software for gamers, content creators, and vtubers. (link)

⚙️ Best ChatGPT Plugins

  • Avian: Access your business data from Google Analytics, Google Ads, Facebook Ads and more. (link)

  • Polarr: Discover a vast user-generated filter library for flawless photos and videos. (link)

  • UK Politics: Gain access to UK political documents: speeches, press releases, voting records and candidate profiles. (link)

  • Wolfram: Unleash Wolfram|Alpha and Wolfram Language - Compute, Math, Knowledge and Data. (link)

  • NASA Media Explorer: Leverage NASA’s vast media library for an enlightening experience on space exploration. (link)

🖌️ Today’s Best New DALL-E Prompts

 🎨 Today’s Best New Midjourney Prompts

🤯 Insight: The Use Of Synthetic Data In AI

Synthetic data is generated from data designed to mimic real-world datasets statistically. However, it comes with several challenges and limitations. The problem lies in the ambiguity of "real data" and the statement that synthetic data replicates "some or all of the statistical properties."

The use of "real data" raises questions about data adequacy and the truthfulness of the generated data. Crafting models for generating synthetic data is an art, making it prone to spurious relationships and biases introduced by the modeller's variable selection.

While synthetic data can be useful for certain purposes, relying solely on it may undermine the value of human data. It can also artificially inflate confidence in analyses and distort the representation of under-represented groups.

Despite some claims, synthetic data has promising applications, especially in privacy protection, where it can help resolve privacy-utility trade-offs of legacy anonymization techniques.

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