Track host
About the track
The global AI market size is projected to grow from ~ USD 380 billion in 2022 to USD ~1.4K billion in 2029 at a compound annual growth rate of 20.1% in the forecast period. With the surge in demand and interest in AI-powered technologies, many new trends are emerging in this space. This QCon London track invites tech professionals and executives, who are involved with the AI technology in some capacity, to see what’s next in the realm of Artificial Intelligence and Machine Learning trends.
The day in the host's words
Sessions in this track
Wednesday 29 March. 5 sessions per track, chosen and introduced by the Track Host.
10:35 Mountbatten (6th Fl.) Session Machine Learning Strategy & Principles to Scale and Evolve MLOps @DoorDash Hien Luu Sr. Engineering Manager @Zoox & Author of MLOps with Ray, Speaker and Conference Committee Chair MLOps has become a major enabler to successfully operationalize ML applications and for ML practitioners to realize the power of ML to bring impact to business. The journey to implementing MLOps will be unique to each company. 11:50 Mountbatten (6th Fl.) Session Digital Twins Cognitive Digital Twins: A New Era of Intelligent Automation Yannis Georgas Intelligent Industry Lead @Capgemini Traditionally, Digital Twins have been helping businesses make data-driven decisions, increase efficiency, and improve the overall performance of their physical assets. 13:40 Mountbatten (6th Fl.) Session AI Responsible AI: From Principle to Practice! Mehrnoosh Sameki Principal PM Manager @Microsoft Enabling responsible development of artificial intelligent technologies is one of the major challenges we face as the field moves from research to practice. Researchers and practitioners from different disciplines have highlighted the ethical and legal challenges posed by the use of machine… 14:55 Mountbatten (6th Fl.) Session Graphs Graph Learning at the Scale of Modern Data Warehouses Subramanya Dulloor Founding Engineer @Kumo.ai Data warehouses have become a staple for enterprises, providing a wealth of information that can be harnessed to improve decision-making through the use of machine learning (ML). 16:10 Mountbatten (6th Fl.) Session python Simplifying Real-Time ML Pipelines with Quix Streams: An Open Source Python Library for ML Engineers Tomáš Neubauer CTO & Co-Founder @Quix As data volume and velocity continue to increase, the need for real-time machine learning (ML) is becoming more pressing. However, building real-time ML pipelines can be complex and time-consuming, requiring expertise in both ML and streaming application development.QCon London 2023 is a three day conference for senior software engineers, architects and team leads. An international program committee of working engineers selects every session. Patterns and practices, not products and pitches.