Research is to see what everybody else has seen
- but to think what nobody else has thought.
AI Research
Researching new scientific methodologies
Interpretable AI
Really understanding “black box” AI models
Scientific Resources
Sharing our development with the AI community
Applying real science
Research and apllication of new Artificial Intelligence algorithms
Apollo Labs’ focus is on research.
Artificial Intelligence has become popular and helped solve many problems that were considered unsolveable. However, its popularity doesn’t mean that innovation is as frequent as it can be, as “more of the same” methods are usually applied by many practitioners.
Researching new algorithmic methods allows to extract information unreachable by existing methods, gaining a competative advantage.
Four easy steps
Data Science methodology
- ProblemBusiness Understanding01Understanding the problem by all parties involved is key. This step is not scientific, but "soft".
- DataData Exploration02Scientific tools will be used to understand hidden structures in the data.
- AlgorithmsApplying Science03Using cutting edge algorithms, fresh out of academic research, the algorithmic solution is created.
- SolutionMeasurement & Integration04After mathematical solutions are applied, results can be integrated: as Product, Insights or Research.
Deep Learning should expand from “System 1” to “System 2”.
– System 1 represents what current deep learning is very good at — intuitive, fast, automatic, anchored in sensory perception. System 2 meanwhile represents rational, sequential, slow, logical, conscious, and expressible with language.
Innovative AI Projects
AI Projects with a real scientific core
AI has various levels of execution. The term “data science” is lucrative. Our focus is on problems that MUST use AI as a solution, not on problems that could benefit from a simpler solution.
Data Science – AI – Machine Learning
Knowledge
Do you face a real data-driven challenge? See if the power of artificial intelligence can help.