Zum Inhalt springen
AI Learning

Sources & Further Reading

iSources checked: September 2026

Sources reviewed in September 2026: links checked for availability and extended with references for the current state. As the AI landscape evolves quickly, some details may have changed since then.

Sources

  1. McCarthy, J., Minsky, M. L., Rochester, N. & Shannon, C. E. (1956). A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence. http://jmc.stanford.edu/articles/dartmouth/dartmouth.pdf

  2. Vaswani, A. et al. (2017). Attention Is All You Need. arXiv:1706.03762. https://arxiv.org/abs/1706.03762

  3. Hu, K. (2023). ChatGPT sets record for fastest-growing user base. Reuters. https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/

  4. METR (2025). Measuring AI Ability to Complete Long Tasks. https://metr.org/blog/2025-03-19-measuring-ai-ability-to-complete-long-tasks/

  5. Stanford HAI (2025). AI Index Report 2025. https://aiindex.stanford.edu/report/

  6. OpenAI – Model Overview. https://openai.com/

  7. Anthropic – Claude Model Overview. https://claude.com/product/overview

  8. Google DeepMind – Gemini. https://deepmind.google/technologies/gemini/

  9. Meta AI – LLaMA. https://ai.meta.com/llama/

  10. Anthropic (2026). Claude – pricing and model overview. https://claude.com/pricing · https://platform.claude.com/docs/en/about-claude/pricing

  11. OpenAI (2026). Models – API documentation. https://developers.openai.com/api/docs/models/

  12. Google (2026). Gemini API pricing. https://ai.google.dev/gemini-api/docs/pricing

Further Reading

Reports & Reference Works

Accessible Explanations

Videos