Deep Learning, Machine Learning, and GPT Progress (2010-2025) | Generated by AI

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Here’s a detailed timeline of the major breakthroughs in deep learning, machine learning, and GPT from 2010 to my knowledge cutoff in October 2024:

Early 2010s: Foundations

Mid 2010s: Foundation Models Emerge

Late 2010s: Transformer Revolution

Early 2020s: Scaling and Multimodality

2023-2024: Multimodal LLMs and Reasoning

  1. Scaling Laws: Consistent performance improvements by increasing model size, dataset size, and computation.

  2. Emergent Abilities: Capabilities like in-context learning appearing unexpectedly at certain scale thresholds.

  3. Multimodality: Integration of text, images, audio, and video in unified models.

  4. Reinforcement Learning from Human Feedback (RLHF): Aligning models with human preferences.

  5. Democratization: Growth of open-source models and accessible frameworks lowering barriers to ML development.

This period represents perhaps the fastest technological progress in any field in human history, transforming ML from a specialized academic discipline to a general-purpose technology with global impact.


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