NILG.AI

At NILG.AI, we worked hard to become an active member of the Data Science community in Portugal, which has played a fundamental role in our initial growth by building an ever-growing network of people and ideas. This AI blog is a new way of giving back to the community by creating a space for continuous discussion and exchanging ideas. Here, you will find diverse content about AI and its impact on multiple industries. The content will range from theory to applications, AI to business, and machine to human. While the content structure 

will evolve with time, we anticipate that we will cover the following formats:

• Formal and personal opinion about an AI concept.
• Brainstorming on how to solve an AI use case.
• A showcase of our projects.
• Interviews with members of the community.
• Any other content that would make this your AI blog of preference.

Our AI blog: A knowledge-sharing initiative

This AI blog aims to diversify our channels to share knowledge with others. In 2019, we promoted multiple initiatives. Namely:

• We had an active role in the research community, building partnerships with major research centers in the region. This allowed us to create value beyond the existing knowledge frontiers. So, we published eight papers in scientific conferences and journals*, submitted two patents with our clients, and co-supervised multiple MSc students.
• We made learning and brainstorming new ideas part of our daily routines. We organized +25 learning sessions in the second semester only, ranging from fundamental topics (e.g., transductive and semi-supervised learning) to very applied sessions where we discuss roadmaps for applying AI to new use cases.
• We participated in local events such as meetups (DSPT e ML Porto) and regional conferences (Semana Informatica, VISUM, IbPRIA, e RecPad).

Besides these initiatives, we forecast that 2020 will be the year where:

• We focus on expanding our range of action to other industries and countries.
• We go beyond consulting and work on internal products.
• We pave the path to becoming a global reference in AI & DS.

About the future

The future is uncertain -yes, even for a company that focuses on predictions– and, while we don’t know for sure the success of this and other initiatives, we know that as long as we can help others to sail beyond the AI hype, we will keep working to fulfill our vision.

As long as we can help others to sail beyond the AI hype, we will keep working to fulfill our vision

We hope you enjoy the result as much as we enjoy the process.

Stay tuned!

References

• Silva, Wilson, Kelwin Fernandes, and Jaime S. Cardoso. “How to produce complementary explanations using an ensemble model.” IJCNN. IEEE, 2019.
• Rio-Torto, Isabel, Kelwin Fernandes, and Luís F. Teixeira. “Towards a Joint Approach to Produce Decisions and Explanations Using CNNs.” IbPRIA. Springer, Cham, 2019.Pernes, Diogo, Kelwin Fernandes, and Jaime S. Cardoso. “Directional Support Vector Machines.” Applied Sciences 9.4 (2019): 725.

  Araújo, Ricardo J., Kelwin Fernandes, and Jaime S. Cardoso. “Sparse Multi-Bending Snakes.” IEEE Transactions on Image Processing 28.8 (2019): 3898-3909.

  Rebelo, José, Kelwin Fernandes, and Jaime S. Cardoso. “Quality-based Regularization for Iterative Deep Image Segmentation.” EMBC. IEEE, 2019.

  Almeida, Eduardo Nuno, et al. “A Machine Learning-Based Quality of Service Estimator for Aerial Wireless Networks.” 2019 WiMob. IEEE, 2019.

  Silva, Wilson, et al. “Interpretable Ensemble Model for the Aesthetic Evaluation of Breast Cancer Treatments.” RecPad, 2019.

  Rio-Torto, Isabel, Kelwin Fernandes, and Luís F. Teixeira. “Producing Decisions and Explanations: A Joint Approach Towards Explainable CNNs.” RecPad, 2019.