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University of applied sciences

Bern University of Applied Sciences

BFH is a university of applied sciences. In addition to teaching, our core competencies include continuing education, research and development and consulting services.

4 School 5 Institute 8 Groups 3 Services 9 Projects 19 People 2 News

School of Engineering and Computer Science

School of Social Work

School of Agricultural, Forest and Food Sciences

Business School

Institute for Medical Informatics

Institute for Data Applications and Security IDAS

Institut für Soziale Sicherheit und Sozialpolitik

Consumer-focused Food Production

Institute for Public Sector Transformation

Applied Machine Intelligence, School of Engineering and Computer Science

Measures taken by social security institutions and their effects, School of Social Work

Interaction of the institutions of the social security system, School of Social Work

Social security in the context of social change, School of Social Work

Consumer-focused Food Production, School of Agricultural, Forest and Food Sciences

Data science applications in healthcare, School of Engineering and Computer Science

Digital Sustainabilty Lab, Business School

BFH Generative AI Lab, School of Engineering and Computer Science

CAS Datenanalyse

CAS Practical Machine Learning

Data Science continuous education

BFH

NLP

PSO

HMI

Automation of Legal Document Discovery

BFH

Gov-ELSI

PPML-Health: A Privacy-Preserving Machine Learning...

BFH

NLP

Diversifier-NLP - Automated Text Analysis for more...

BFH

Automated battery database

BFH

NLP

PSO

HMI

NLP Unterstützung der radiologischen Befundung

BFH

NLP

Mitigating Diversity Biases of AI in the Labor Market

BFH

Gov-ELSI

A future that works: Cobotics, digital skills and the...

BFH

NLP

HMI

Towards Burnout Risk Detection using Word Embeddings

BFH

Probabilistic Intraday Forecasting of Photovoltaic...

Prof.Sebastian Wörwag

Prof.Lukas Rohr

Prof.Anna Maria Riedi

Prof.Ute Seeling

Prof.Annett Laube

Prof.Tobias Fritschi

Axel Fuerst

Prof.Kerstin Denecke

Prof.Erik Graf

Prof.Mascha Kurpicz-Briki

Prof.Raoul Waldburger

Jasmin Nussbaumer

Dominic Jonas Schweizer

Ulrich Fiedler

Matthias Stürmer

Prof.Oliver Hümbelin

Prof.Marcel Gygli

Prof.Julia Mia Stirnemann

Prof.Souhir Ben Souissi

Artificial intelligence in SMEs: from hype to real help

Whether customer support, marketing or production - AI can become a success factor for small and medium-sized companies. However, without acceptance, clear rules and the right technology, the promises remain empty.

How external data makes AI more reliable - Retrieval augmented generation explained

Artificial intelligence (AI) is changing the world of work - but many companies are faced with the challenge of incomplete or unreliable answers from language models. Retrieval Augmented Generation (RAG) offers a solution: the method combines AI systems with external, verifiable data sources to create comprehensible, up-to-date and fact-based results.

Last updated: 10.02.2025

supervised learning, unsupervised learning, written text, regulations & law, ethical or societal implications, reliability of AI & computing, recognition, speech generation, images, reinforcement learning, explainability, transfer Learning

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Artificial intelligence in SMEs: from hype to real help

How external data makes AI more reliable - Retrieval augmented generation explained