"The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis Data, data, everywhere - enough for AGI?
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Apr 13, 2024 Dive into the fascinating world of data and its role in achieving Artificial General Intelligence. Explore the scaling trends and quality requirements for datasets, from social media to genomic data. Discover the exponential growth of training data and the challenges it presents. Learn about the innovative 'ring attention' algorithm and its impact on language model training. Finally, tackle the balance between the sheer volume of data generated and the need for high-quality insights as the potential for synthetic data generation expands.
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Scaling Hypothesis
- The scaling hypothesis of intelligence suggests that larger brains, or models, are smarter.
- Improvements in data quality and algorithms reduce the scale needed for human-level AI.
Data Abundance
- AI leaders believe there's enough data for AGI, or that it can be created.
- They express little concern about data scarcity as a barrier.
Token Requirements
- GPT-3 used about 1 trillion tokens, GPT-4 around 10 trillion, and GPT-5 might use 100 trillion.
- Algorithmic improvements like ring attention could reduce data needs.