Publications (8)
From Robotic Process Automation to Intelligent Process Automation: Emerging Trends
Tathagata Chakraborti, Vatche Isahagian, Rania Khalaf +4
In this survey, we study how recent advances in machine intelligence are disrupting the world of business processes. Over the last decade, there has been steady progress towards th…
FfDL : A Flexible Multi-tenant Deep Learning Platform
K. R. Jayaram, Vinod Muthusamy, Parijat Dube +9
Deep learning (DL) is becoming increasingly popular in several application domains and has made several new application features involving computer vision, speech recognition and s…
A Methodology for Investigating AI Patterns Prevalence in Software Repositories
Srinath Perera, Hasinthaka Piyumal, Frank Leymann +1
As Artificial Intelligence(AI)-based applications take off, a clear understanding of AI patterns can uplift the quality of AI applications. Many AI patterns have been proposed in t…
Robust Agent Compensation (RAC): Teaching AI Agents to Compensate
Srinath Perera, Kaviru Hapuarachchi, Frank Leymann +1
We present Robust Agent Compensation (RAC), a log-based recovery paradigm (providing a safety net) implemented through an architectural extension that can be applied to most Agent…
Dependability in a Multi-tenant Multi-framework Deep Learning as-a-Service Platform
Scott Boag, Parijat Dube, Kaoutar El Maghraoui +7
Deep learning (DL), a form of machine learning, is becoming increasingly popular in several application domains. As a result, cloud-based Deep Learning as a Service (DLaaS) platfor…
A Conversational Digital Assistant for Intelligent Process Automation
Yara Rizk, Vatche Isahagian, Scott Boag +4
Robotic process automation (RPA) has emerged as the leading approach to automate tasks in business processes. Moving away from back-end automation, RPA automated the mouse-click on…
MLSys: The New Frontier of Machine Learning Systems
Alexander Ratner, Dan Alistarh, Gustavo Alonso +66
Machine learning (ML) techniques are enjoying rapidly increasing adoption. However, designing and implementing the systems that support ML models in real-world deployments remains…
IBM Deep Learning Service
Bishwaranjan Bhattacharjee, Scott Boag, Chandani Doshi +15
Deep learning driven by large neural network models is overtaking traditional machine learning methods for understanding unstructured and perceptual data domains such as speech, te…