Getting Valueout of Data with
Large Language Models

digitalgovernment

Andrejs VasiļjevsDr.Sc.comp, Co-Founder and Board Member
Tilde

Data Spaces Symposium
Darmstadt, March 12, 2024

Retrieval-augmentedgeneration use cases▪ Retrieval-Augmented Generation (RAG)
combines information retrieval andgenerative AI to enhance the quality andrelevance of generated responses.
▪ It leverages vast databases or knowledge
bases, retrieving information that is mostrelevant to a query before generating ananswer.

RAG Use Case:

StairwAI VirtualAssistant▪ StairwayAI: Ease the Engagement ofLow-Tech Users to the AI-on-DemandPlatform through AI▪ Matchmaking to provide necessary AI
tools, resources, computing power▪ A virtual assistant that helps low techusers to navigate through the StairwAIplatform

https://stairwai.nws.cs.unibo.it/▪ Uses RAG to answer questions about
the StairwAI platform and general
topics on AI

RAG Use Case:
ESASky Virtual Assistant▪ ESASky – online platform for finding,visualizing and downloading public
astronomical data

▪ Virtual assistant finds the necessary data
based on the natural language dialog▪ Helps navigating through the ESA Skysystem▪ Answers questions on how to use theESA Sky system using RAG

RAG Use Case:
Virtual assistant for
academic courses• Virtual assistant trained onuniversity course materials• The first virtual assistant in Latvia
implementing retrievalaugmented generation• Can answer almost any question
about the course in question

https://estudijas.lu.lv/

RAG Use Case:
Virtual Assistant forEnterprise Data
▪ An employee's query is analyzed tounderstand its intent▪ The RAG system searches an enterprise's
databases, documents, and other data
sources for relevant information▪ Can use the context of a single document or
the whole archive▪ Generative AI is used to synthesize theretrieved information and generate acoherent, contextually relevant response

Use case:
Meeting notes andsummaries▪

Transformation of spoken language
into written language▪

Automatic post-processing ofspeech transcripts▪

Automatic generation of meetingtranscripts and summaries▪

AI generated outline of the key
points discussed, opinions
expressed, decisions made inmeeting minutes

Language disparity in Large Language Models

Credits: Marta Villegas, BSC-CNS

Creating Large Language Models forLess Supported EU Languages• Language Technology Initiative project in Latvia - creating synergy between
higherANONYMIZATION
education, science and industry to promote LARGE
innovationin language technology:
LANGUAGE
MODELS• Preparing specialists in language technology• Creating Large Language Models for Latvian and other advanced language technologies

MACHINE
TRANSLATION• Preparatory work on a comprehensive, open-source LLM specifically designed for
CHATBOTS

Balto-Slavic languages, with over 30 billion parameters, tailored for the unique
NATIONAL LANGUAGE
linguistic features of Balto-Slavic languages
TECHNOLOGY PLATFORM

Objective
Develop and deploy a European platform and marketplace for the collection, creation, sharing and re-use ofmultilingual and multimodal language data
Salient features
Governance framework, technical architecture and infrastructure, openness, promotion

Stakeholders
Industry, research, public administration, cultural associations, NGOs and citizens
Sustainability
Towards long-term sustainability: ongoing work on supporting EU Member States in creating
ALT-EDIC (Alliance for Language Technology European Data Infrastructure Consortium)Thank you!

Andrejs Vasiļjevs
Co-Founder and Board Member, Tilde
andrejs@tilde.com