General Language Models
Multimodal Large Models
Industry-Specific Models
Open-Source Models
According to the AI (ChatGPT) planning and fully automated process design, the following AI large models or AI tools may be used to help us quickly build the platform and achieve the product as planned.
Category | Examples | Purpose | Possible Usage Scenarios |
---|---|---|---|
AI Large Models | 1. ChatGPT/GPT-4.5 (OpenAI) | Natural language understanding, multimodal generation, conversational AI | Idea brainstorming, automated document generation, multimodal interaction |
2. Claude (Anthropic) | |||
3. Gemini (Google) | |||
4. Llama 2 (Meta) | |||
5. Stable Diffusion | |||
Image Models | 1. DALL·E 3 (OpenAI) | Image generation, image-to-text, and visual content creation | UI design, visual asset generation, multimodal input analysis |
2. Runway ML | |||
3. DeepArt | |||
Voice Models | 1. Whisper (OpenAI) | Speech-to-text and text-to-speech, voice interaction | Always-on voice interaction, transcription, real-time conversation |
2. Google Speech-to-Text | |||
3. AssemblyAI | |||
Frameworks | 1. LangChain | Model deployment, task orchestration | Workflow automation, AI pipeline management |
2. Transformers (Hugging Face) | |||
3. PyTorch | |||
4. TensorFlow | |||
APIs | 1. OpenAI API | Access to pre-trained AI models and scalable cloud services | Model integration, processing multimodal data, deploying serverless solutions |
2. Google Cloud AI APIs | |||
3. AWS AI Services | |||
4. Hugging Face API | |||
UI/UX Design Tools | 1. Figma | Prototyping and user interface design | Mockup generation, interactive design testing |
2. Adobe XD | |||
3. Canva Pro | |||
Automation Tools | 1. Zapier | Automating repetitive workflows | Linking tasks across platforms, scheduling task execution |
2. Make (Integromat) | |||
3. Airflow | |||
Testing Tools | 1. Selenium | Automated testing of front-end and back-end systems | Functional testing, performance evaluation, identifying bugs |
2. Cypress | |||
3. PyTest | |||
Data Resources | 1. Public datasets (e.g., Common Crawl, Kaggle Datasets) | Training and fine-tuning models | Improving domain-specific tasks, creating robust AI models |
2. Private structured databases | |||
Collaboration Tools | 1. Notion | Enabling team collaboration and communication | Managing project workflows, tracking progress |
2. Slack | |||
3. Microsoft Teams | |||
Analytics Tools | 1. Tableau | Real-time analytics and insights gathering | User behavior analysis, feedback loop optimization |
2. Power BI | |||
3. Google Analytics |