RAG vs Fine-Tuning vs Prompt Engineering: Optimizing AI Models
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RAG vs Fine-Tuning vs Prompt Engineering: Optimizing AI Models
Ready to become a certified watsonx AI Assistant Engineer? Register now and use code IBMTechYT20 for 20% off of your exam → https://ibm.biz/BdndTs Learn more about RAG vs. Fine-Tuning vs. Prompt Engineering here → https://ibm.biz/BdndTi How do AI chatbots deliver better responses? 🤔 Martin Keen explains RAG ...
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IBM vice chair and former NEC director Gary Cohn said Wednesday "when we get into the quantum space, AI will go from the cost saver to the revenue creator" because the models will then be able to actually think instead of only doing what they were trained to do. Watch the full interview: cnb.cx/48OdhWw | CNBC
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