Jorge Quiané will present his work on October 13th at 3 pm.
It will be online at https://ecolepolytechnique.zoom.us/j/86323133834?pwd=QzFqdlpwalBwTUtRbzQxYWQwSXNLUT09
Title
AGORA: Building an AI Ecosystem for AI Innovation
Abstract
Artificial intelligence (AI) is driven by a plethora of diverse data-related assets, including datasets, data streams, algorithms, processing software, compute resources, and domain knowledge. Providing all these assets requires a huge investment. As a result, AI technologies are currently dominated by a small number of providers who can afford these investments. This leads to lock-in effects and hinders innovation
He will present Agora, his vision towards a unified AI ecosystem that brings together data, algorithms, models, and computational resources and provides them to a broad audience to foster innovation. Agora (i) treats assets as first-class citizens and leverages a fine-grained exchange of assets, (ii) allows for combining assets to novel applications, and (iii) flexibly executes such applications on available resources. As a result, it enables easy creation and composition of AI pipelines as well as their scalable execution. In this talk, he will particularly focus on the execution layer of Agora and explain how we leverage AI and Big Data to effectively and efficiently support AI ecosystems.
Bio
Jorge Quiané is the head of the Big Data SystemsGroup at the Berlin Institute for the Foundations of Learning and Data (BIFOLD)and a Principal Researcher at DIMA (TU Berlin). He also acts as the Scientific Coordinator of the IAM group at the German Research Center for ArtificialIntelligence (DFKI). His current research is in the broad area of big data: mainly in federated data analytics, scalable data infrastructures, and distributed query processing. He has published numerous research papers on data management and on novel system architectures. He has recently been honored with the Best Paper Award at ICDE 2021 for his work on “EfficientControl Flow in Dataflow Systems”.He holds 5 patents in core database areas and on machine learning. Earlier in his career, he was a senior scientist at the Qatar Computing Research Institute (QCRI) and PostdoctoralResearcher at Saarland University. He obtained his Ph.D. in computer science from the University of Nantes (INRIA).
