Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
139 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
46 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

FhGenie: A Custom, Confidentiality-preserving Chat AI for Corporate and Scientific Use (2403.00039v1)

Published 29 Feb 2024 in cs.SE, cs.AI, and cs.HC

Abstract: Since OpenAI's release of ChatGPT, generative AI has received significant attention across various domains. These AI-based chat systems have the potential to enhance the productivity of knowledge workers in diverse tasks. However, the use of free public services poses a risk of data leakage, as service providers may exploit user input for additional training and optimization without clear boundaries. Even subscription-based alternatives sometimes lack transparency in handling user data. To address these concerns and enable Fraunhofer staff to leverage this technology while ensuring confidentiality, we have designed and developed a customized chat AI called FhGenie (genie being a reference to a helpful spirit). Within few days of its release, thousands of Fraunhofer employees started using this service. As pioneers in implementing such a system, many other organizations have followed suit. Our solution builds upon commercial LLMs, which we have carefully integrated into our system to meet our specific requirements and compliance constraints, including confidentiality and GDPR. In this paper, we share detailed insights into the architectural considerations, design, implementation, and subsequent updates of FhGenie. Additionally, we discuss challenges, observations, and the core lessons learned from its productive usage.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (13)
  1. Longbench: A bilingual, multitask benchmark for long context understanding, 2023.
  2. Deutsche Forschungsgemeinschaft (DFG German Research Foundation). Data tracking in research: aggregation and use or sale of usage data by academic publishers. Briefing paper of the Committee on Scientific Library Services and Information Systems of the DFG, https://www.dfg.de/resource/blob/174924/d99b797724796bc1a137fe3d6858f326/datentracking-papier-en-data.pdf, accessed 2024-02-18, May 2021.
  3. Fraunhofer. FhGenie: The Fraunhofer-Gesellschaft launches an internal AI chatbot. Press Release, https://www.fraunhofer.de/en/press/research-news/2023/august-2023/fhgenie-the-fraunhofer-gesellschaft-launches-an-internal-ai-chatbot.html, accessed 2024-02-18, August 2023.
  4. LongLLMLingua: Accelerating and enhancing LLMs in long context scenarios via prompt compression. ArXiv preprint, abs/2310.06839, 2023.
  5. LLMLingua: Compressing prompts for accelerated inference of large language models. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 13358–13376. Association for Computational Linguistics, December 2023.
  6. Fabrizio Le. How ChatGPT is transforming the postdoc experience. Nature, 622:655, 2023.
  7. Retrieval-augmented generation for knowledge-intensive NLP tasks. In Proceedings of the 34th International Conference on Neural Information Processing Systems, NIPS’20, Red Hook, NY, USA, 2020. Curran Associates Inc.
  8. Responsible AI: Best Practices for Creating Trustworthy AI Systems. Addison Wesley, February 2024.
  9. LLMs for science: Usage for code generation and data analysis. Journal of Software Evolution and Process (JSEP), January 2024. In press, accepted.
  10. The impact of AI on developer productivity: Evidence from GitHub Copilot. arXiv preprint arXiv:2302.06590, 2023.
  11. Generative AI for programming education: Benchmarking ChatGPT, GPT-4, and human tutors, 2023.
  12. Hallucination or confabulation? Neuroanatomy as metaphor in large language models. PLOS Digital Health, 2(11):1–3, 11 2023.
  13. Toby Walsh. 2062: The world that AI made. Black Inc., 2018.
Citations (1)

Summary

We haven't generated a summary for this paper yet.