🐹 Chinchilla Scaling Law – Smarter AI Training 🚀 Bigger isn’t always better in AI. Balance is everything. DeepMind’s Chinchilla showed that balancing model size and data is the real key: 📏 20 training tokens per parameter = optimal performance. Why this matters: ✅ More data can beat just more parameters ✅ Smaller, well-trained models are cheaper & faster ✅ Better efficiency → better results 💡 The future of AI isn’t just about going bigger - it’s about going smarter. #AI #MachineLearning #ChinchillaScalingLaw #DeepMind #LLM #AIInnovation
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VP System Integration and Deployments at Afiniti
1moFun fact: Chinchilla’s 70B parameters + 1.4 trillion tokens beat Gopher’s 280B parameters on nearly every benchmark. More data, fewer parameters and still better results!