NEWSLETTER

Subscribe to the monthly newsletter below.

Publication highlights

Nickisch, H., Solin, A., Grigorevskiy, A., 2018. State Space Gaussian Processes with Non-Gaussian Likelihood.
ICML 2018.

Parviainen, P., Kaski, S., 2017. Learning structures of Bayesian networks for variable groups.
IJAR 88.

Remes, S., Heinonen, M., Kaski, S., 2017. Non-Stationary Spectral Kernels.
NIPS 2017

Holopainen, M., Sarlin, P., 2017. Toward robust early-warning models: A horse race, ensembles and model uncertainty. Quantitative Finance 17.

TECHNICAL WEBINARS

WHITE PAPERS

EXPLORE THE PRACTICAL USE OF AI AND MACHINE LEARNING TODAY

AI & RECRUITMENT - A VISION OF HOW AI IS IMPACTING RECRUITMENT TODAY

AI is becoming the de-facto technology that will augment all human driven operations in the near future. Today, the main source of AI-driven competitive advantage is by bringing an AI to work in human processes, and increasing every human operator’s efficiency by offloading low value yielding tasks to its learning automation. In this report Silo.AI will present an overview of AI’s impact to recruitment in large scale.

AI IN RETAIL - HOW TO USE AI TO IMPROVE PROFIT RETENTION AGAINST FRAUD IN THE RETAIL WORLD

The world of retail has been among the first to see AI- driven change take place in the everyday life of the consumer. Companies like Amazon and Alibaba have paved the way for changes in both the digital and the physical world. Not surprisingly, they are also considered to be among the frontrunners of Artificial Intelligence (AI). The first step into AI-driven transformation, however, is not to radically alter our shopping experiences with new digital pathways but to augment pre-existing ways of doing work with elevated levels of automation. This white paper is intended to outline how AI-augmented business produces measurable business benefit in both the digital and the physical world.

AI AND TRADITIONAL ANALYTICS – UNDERSTAND WHEN AND WHERE TO USE MACHINE LEARNING

Artificial intelligence and machine learning can complement and co-exist with the existing analytics methods based on rules, optimisation, simulation and statistical analysis. However, it is crucial to understand where and when it makes sense to implement AI solutions, and when it is better to use traditional analytics. After reading the white paper, you will understand:

  1. What AI and machine learning means in practice
  2. How using AI is different from rule-based systems, optimisation, simulation and statistical analysis
  3. How to implement data driven decision making with machine learning, and
  4. What type of use cases can be served with machine learning.

Get the white paper(s)

Stay in touch

Get expert tips on how AI delivers competitive advantage to your business. Subscribe to the monthly newsletter below.

Get expert tips on how AI delivers competitive advantage to your business. Subscribe to the monthly newsletter below.