Artificial Intelligence
Description of Artificial Intelligence
We are specialists in the development and application of artificial intelligence to solve complex problems, with a particular emphasis on the use of generative AI models for content creation, data analysis and process optimisation.
We develop proofs of concept to explore the potential and feasibility of all these technologies in different application areas.
- Generative AI: use of advanced models for the generation of text, images, voice, code and other types of digital content.
- Language Models (LLM and SLM): working with Large Language Models (LLM) and Small Language Models (SLM) to adapt AI to different use cases, optimising efficiency and responsiveness.
- Multimodal Models: development and application of models that combine text, images, audio and other information sources to provide richer, more contextualised solutions.
- Fine-tuning of language and computer vision models: adapting pre-trained models to specific use cases to improve their accuracy and relevance.
- Natural Language Processing (NLP): text analysis and generation, machine translation, automatic summarisation, sentiment analysis and virtual assistants.
- RAG (Retrieval-Augmented Generation): a combination of information retrieval and text generation to improve the accuracy and reliability of AI-generated responses.
- Extraction of information from complex documents: use of advanced models to interpret, structure and analyse information from extensive and technical documents.
- Computer Vision: image and video recognition, object detection, image synthesis and scene enhancement using generative AI.
- Process optimisation and automation: use of AI to improve efficiency in areas such as logistics, resource planning or automated decision-making.
- Optimització i automatització de processos: ús d’IA per millorar l’eficiència en àmbits com la logística, la planificació de recursos o la presa de decisions automatitzada.
- Ethics and explainability in AI: developing transparent and responsible models, ensuring the interpretability and reliability of intelligent systems.
Artificial Intelligence Success Stories
In this project, the company, together with the participation of inLab FIB, aims to make the daily work of Help Desk staff easier, as well as that of employees who need to report requests or incidents, by automating form filling.
The main propose of AgriLogistics is the creation of a collaborative data space that facilitates access to information for all stakeholders in the agri-food supply chain, with the aim of strengthening logistics and improving its efficiency.
inLab FIB and Qorvo Inc. are collaborating on a research project exploring artificial intelligence-based approaches to accelerate microelectronic circuit design, with a focus on design automation and performance prediction.
The project “Developement of automation technology” is an initiative led by Supertronic with the participation of TECNIO inLab FIB center, focused on the automation of the selection and creation process of plastic envelopes for printed circuit boards (PCB’s).
The inLab FIB participates in a innovative project to develop an interactive assistant based in Artificial Intelligence (AI), designed to help solve quality issues.
In today’s digital age, mobile applications have become an integral part of our daily lives, but they have also increased the risks of cybersecurity. Companies face the challenge of protecting their applications and user data in an environment of constantly evolving threats.