LAP - Language and Personalization
Language and Personalization
This work package is a new construct, made up by the combination of the previous work packages on personalization (PERS) and natural language processing (LANG). The work in the work package will initially follow these two directions somewhat separately, for later to be tighter combined.
The purpose for this work package is to develop personalization techniques and Scandinavian language processing capabilities to provide personalized content generation and:
- Develop truly explainable, fair and transparent personalization techniques
- Enable proactivity in customer relations
- Provide an individualized experience that provably respects privacy concerns
- Develop individualized content
- Develop large-scale Scandinavian language models
- Enable human-like content creation and conversations
Personalization and contextualization have been successfully employed in diverse applications over the past decade, and currently see an extended usage, for instance in proactive interaction with customers and individualization of news stories. LAP will contribute to developing such systems while ensuring that the system usage will be ethical and respecting users’ requirements for privacy, fairness and accountability.
Building Scandinavian language models requires the compilation of large-scale reusable language resources, including general-purpose corpora from public sources (e.g., news and social media) as well as industry- and domain-specific text collections. We will address the scarcity of the latter by pre-training on the former and developing transfer learning methods. These large-scale language models will then be utilized in real-life scenarios by formulating a number of specific summarization, explanation, and conversational tasks based on our partners’ use-cases. LAP will develop appropriate evaluation methodology with user-oriented evaluation measures and objectives. It will thus contribute to providing measurable quantification of the amount of domain-specific training material needed in order to provide a language service that is of sufficiently high quality.
WP Leader
Upgrading infrastucture is critical to meet AI demands
Upgrading the national infrastructures are critical steppingstones to be prepared for the quantum leap technology now is facing.
Photo: Kai TY. Dragland, NTNU
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Amerikanske språkmodeller påvirker ChatGPT. Det er problematisk.
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A national call for cooperation Media to contribute to NorwAI’s LLM
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Academic coordinator
Schibsted Products & Technology
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Due to the enormous amounts of data, compute and brain power required, these important platforms are now mostly developed and controlled by a few very large private technology companies in the US. This is problematic, because along with all the interesting new functionality, large language models also suffer from serious and complicated challenges such as bias, hallucinations and toxicity. Private companies will invariably balance mitigating these issues with the need for profit. They are likely to do the bare minimum required to avoid regulatory retribution and public relations backlash.
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Photo: Kai T. Dragland, NTNU
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Language experts to report on speech and text to the Storting
project manager
in the Norwegian Board
of Technology
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Norway may take a world-leading AI role
professors Kjetil Nørvaag, NTNU (left)
and Krisztian Balog, UiS, headed the ECIR forum
for Information Retrieval in April. Photo: NorwAI
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Photo: Kai T Dragland, NTNU
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