Towards Data Science
Why AI Is Training on Its Own Garbage (and How to Fix It)
•1 min read•
#rag#deployment#llm#compute
Level:Intermediate
For:Data Scientists, ML Engineers, AI Researchers
✦TL;DR
The article discusses the issue of AI models being trained on low-quality or irrelevant data, often referred to as "garbage", which can significantly impact their performance and accuracy. The post highlights the importance of accessing high-quality deep web data, which is currently out of reach, and explores potential solutions to address this problem.
⚡ Key Takeaways
- AI models are being trained on low-quality data, leading to suboptimal performance
- Deep web data has the potential to greatly improve AI model accuracy, but is currently inaccessible
- New approaches and technologies are needed to tap into this valuable data source
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