✨ Introducing DataGemma, open models that enhance LLM factuality by grounding them with real-world data from Google’s Data Commons. → https://goo.gle/4dWFyKn Learn how DataGemma uses two distinct RIG and RAG approaches to: 📖 Harness the knowledge of Data Commons 🧠 Fact check numeric data against trusted sources 🛠️ Lead the way in developing responsible AI And more for the #Gemmaverse!
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DataGemma looks like a groundbreaking initiative! Grounding LLMs with real-world data through RIG and RAG approaches can massively improve factual accuracy and reliability. Integrating Google's Data Commons is a smart move, especially for fact-checking numeric data against trusted sources. Excited to see how this will advance responsible AI development. Looking forward to exploring the #Gemmaverse
Grounding AI models with real-world data, as DataGemma is doing, is a brilliant step forward. In sectors where accuracy and real-time data are essential, this kind of innovation makes a significant impact. The integration of RIG and RAG approaches to fact-check and enhance AI's factuality is key to building more responsible and trustworthy AI systems. Looking forward to seeing how this technology continues to evolve and shape the future of AI!
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Interesting
It will definitely help developers in improving accuracy of models.
🤔 While DataGemma's intention is commendable, grounding AI in real-world data from a controlled source like Google's Data Commons could risk creating an echo chamber, reinforcing dominant narratives without a true diversity of perspectives. Are we sacrificing creativity and broad understanding for the sake of 'accuracy'? #ThinkDifferent #DataBias #AIChallenges
So exciting to see this launch