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Synthetic data – The Missing Link to AGI
- Training AI models with synthetic data that simulate human-like reasoning can fill the 'thought process' gap in achieving AGI advancements.
- Current Artificial Intelligence models lack structured and conscious reasoning, which is rooted in their training models that mostly consist of diverse and unstructured data from the internet.
- Synthetic data has emerged as a promising solution, as it creates iterative and recursive improvements to simulate structured thought.
- Other leaders in AI industry such as Anthropic and Hugging Face are also exploring the potential of synthetic data.
- Anthropic is generating 'infinite' training data to bypass the limitations of real-world data while scaling AI models effectively.
- Microsoft AI CEO Mustafa Suleyman predicts recursive improvements driven by synthetic data could accelerate the AGI timeline to three to five years.
- Recursive improvements are grounded on training models on synthetic data to mimic human-like thought processes, which lets AI systems exhibit intelligence that can rival human cognition.
- Predictive models would evolve iteratively, contributing to the improvement of the next model.
- An AGI that generates outputs so profound that it surpasses human capabilities could emerge.
- Synthetic data aims to cultivate novelty and creativity, and the datasets might bridge the gap between current AI limitations and desired AGI capabilities.
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