Two closely related aspects of artificial intelligence that have received comparatively little attention in the recent literature are research methodology, and the analysis of computational techniques that span multiple application areas. We believe both issues to be increasingly significant as Artificial Intelligence matures into a science and spins off major application efforts. Similarly, awareness of research methodology issues can help plan future research buy learning from past successes and failures. We view the study of research methodology to be similar to the analysis of operational AI techniques, but at a meta-level; that is, research methodology analyzes the techniques and methods used by the researchers themselves, rather than their programs, to resolve issues of selecting interesting and tractable problems to investigate, and of deciding how to proceed with their investigations.
The constructionist design methodology (CDM) -- so called because it advocates modular building blocks and incorporation of prior work -- addresses factors that we see as key to future advances in AI, including support for interdisciplinary collaboration, coordination of teams, and large-scale systems integration. We test the methodology by building an interactive multifunctional system with a real-time perception- action loop. The system, whose construction relied entirely on the methodology, consists of an embodied virtual agent that can perceive both real and virtual objects in an augmented-reality room and interact with a user through coordinated gestures and speech. Wireless tracking technologies give the agent awareness of the environment and the user's speech and communicative acts.
Do you have the know-how to apply business analysis techniques to deliver innovative solutions? Are you able to challenge the status quo? Are you able to understand business drivers and developments, and explain in a succinct and understandable manner? We're looking for a Use Case Manager who will: • interact and closely engage with all relevant stakeholders to establish risk identification, control and supervision to support AI and machine learning solutions • define requirements and functional specifications for the model developers • manage the development process through production and solution transfer to the stakeholders Methodologies and Models within Group Compliance, Regulatory and Governance is a newly established unit which uses state of the art AI/Machine Learning based solutions, covering the entire non-financial risk control and compliance space. Our mandate is to design and build the next-generation methodology set and AI development pipeline & tooling in an end-to-end responsibility.
Provide a cyber-shield armour to European EPES to survive coordinated, large scale cybersecurity and privacy incidents; guarantee the continuity of operations and minimize cascading effects in the infrastructure itself, the environment and the end-users at reasonable cost. PHOENIX focuses on the protection of the European EPES via: (i) Cybersecurity & Data Privacy by design and by innovation, (ii) cross-country Cybersecurity Information Sharing, realising NIS Directive (iii) realistic exploitation, penetration testing and verification/certification methodologies and procedures and (iv) validation in 5 real-life Large Scale Pilots (LSP) across Europe. The PHOENIX joint Cybersecurity Certification Centre will support EPES systems and assets cybersecurity, privacy and interoperability certification methodologies.
In any undergraduate or postgraduate programme, the ultimate milestone is to complete a research project. The inception of a research project occurs from the research proposal. This course will teach you the significant concepts associated with research methodology and how you can create your research proposal.