腾讯研究院：大模型时代的AI十大趋势观察-人机共生_54页_4mb

AI Industry Development Phase Overview

Section 1: Historical Timeline (2010-2024)

• 2010: AI concept萌芽 (weak AI tools appear)
• 2017: Transformer architectures dominate (Yoshua Bengio, Radford et al.)
• 2018: GPT-3 emergence in ChatGPT
• 2023: ChatGPT's global explosion breaks limits
• 2024: Emerging models approach AGI potential

Section 2: Key Technology Modules

1. Natural Language Processing (NLP):

   • Baseline: CNN/RNN
   • Transformer architecture disruption (2017)
   • Pretraining strategies (BERT etc.)

2. System Architecture:

   • Data RTL -> Transformer
   • Versatile training platforms
   • Establishment of Huge Model Centres

3. Productization:

   • API ecosystem development
   • MaaS platforms evolution
   • Specialized industry applications

4. Hardware-Acceleration:

   • GPU-CPU combination used for model running
   • Utilization of specialized chips

5. Commercialization:

   • Chatbot applications (ChatGPT 2018, 2023)
   • Code generation (GitHub Copilot)
   • Multimodal AI (DALL-E etc.)

Section 3: Major Technology Nodes

1. Engine Innovations:

   • Pal: 2018 LTP released
   • GPTs: Scale from 350M to 2B parameters
   • Hardware-demand evolution

2. Architecture Revolution:

   • Transformer architecture (2017)
   • System development (MoE-multi-expert model)
   • Language Modeling training evolution

3. Platform Building:

   • OpenAI MLO platform establishment
   • Microsoft AI ecosystem of GPUs
   • Hardware-cloud integrated development

4. Commercial Transformation:

   • Plugin ecosystem (2023)
   • Enterprise applications
   • Multi-agency model development