Schedule

We are in the process of finalising the schedule for 2022. Please check back this page again.
  • MachineCon 2022

    Jun 24, 2022

  • There are very few industries that are as complex and challenging as Manufacturing, and the industry is facing unprecedented challenges – raw material shortages, supply chain disruptions, erratic commodity prices, and new entrants with deep pockets challenging status quo of otherwise hard to disrupt industries. All of this while adhering to stringent Sustainability goals. Very few talked about it until a few years go, but Manufacturing might go through a period of renaissance over the coming years with multi billion dollar investments to setup new factories across the globe. This talk is about the pragmatic role of AI in navigating some of these challenges.

  • This keynote will double down on the four key superpowers of growth that – according to Intel - are the basis of tech enablement, thus shaping digital transformation in the new normal. The session will also delve into the possibilities of AI, enterprise AI strategies, and delivering AI from edge to cloud, along with toolkits for AI and analytics. Join in to explore cutting-edge technologies and solutions that help businesses accelerate digitization initiatives, along with Intel’s role in helping them achieve the goal.

  • Today, most organizations struggle to use data to understand what is likely to happen and why it is likely to happen unless they can invest in large data science teams to create machine learning models. Qlik AutoML is our automated machine learning capability that allows business analysts to generate models, make predictions, and test scenarios all within a simple, no-code user experience. With this capability, we are helping transform the traditional business analyst into a citizen data scientist, allowing them to leverage the power of predictive analytics in areas where data scientists don't focus.

  • The impact of AI can be seen across Industries. This session will talk about how AI can be leveraged to solve complex problems across industries. While data, compute and cutting edge models are helping AI adoption, the role of skill, data pipelines and tools which can help faster development cycles is critical. The session will provide an overview of the various Nvidia tools and technologies which helps developers build faster pipelines and better models for AI.

  • With the increased usage of machine learning and artificial intelligence in the real world, the need is felt more than before for implementing ""conscious"" designs that incorporate principles of ethics, and moral values from fairness, respect, transparency, and accountability. While there have been detailed debates on the feasibility of implementing values into ""artificial"" intelligence, the increased human-machine interaction in the implementation of the latest machine learning and artificial intelligence systems calls for a revisit to the topic of whether future AI systems must include as part of their design, an embodiment of values into the socio-technical systems. As we interact in a world of self-driving cars, reusable rockets and autonomous machines around us, the need to ensure error-free, non-life-threatening machine learning algorithms has been felt increasingly across domains. As a result, there is a lot of research around building AI systems that go beyond the replica of human ""gray matter"" to superseding ""gray areas"" in ethics and embodying value systems through intuitive correlations. Easy as it may sound, this needs alignment to more complex, real-world societal norms driven by morals, laws, ethics and most importantly, human biases. Whither from here, and how can we develop machines incorporating ethics? Tune in for more on this topic.

  • Hiring data science talent is getting increasingly tough and there an evident supply-demand gap even today. While there are scores of well-structured courses being published and the data science education industry is getting formalised, industry leaders are still of the opinion that talent graduating from universities and ed-tech firms are not ready for the real world. In this panel, we will talk to industry leaders to understand where is the underlying problem and what will it take to bridge this talent gap.

  • Data has become the foundation of the digital economy. The ability to access data and extract insights from the data is critical to driving customer satisfaction, cost efficiency and profitability. Over the last decade the adoption of modern business intelligence platforms have accelerated data usage in enterprises. The result is that newer user personas are being onboarded with data and existing business users are asking more complex questions. This increases strain on all data specialist teams. Tableau now makes it possible to cover a wide range of use cases for a broad set of users - Ask Data for natural language query, Data Stories for narrative generation out of dashboards, Tableau Business Science for easier access to statistics and machine learning. Learn about how you can scale you analytics journeys from the foundations and basics to advanced predictive and prescriptive analytics.

  • There's been a lot of hype around Al and ML, and its potential to drive transformation in every organization. Al & Machine learning went from being an aspirational technology to mainstream extremely fast. Automation is further making ML Ops more efficient and we're seeing a tipping point, where the recent hype for these technologies is transitioning to real impact on businesses. ML led Digital transformation requires many ingredients; a problem statement, sponsorship from senior leadership team, the right skills, data and technology. Customers around the world are taking advantage of the AWS Machine Learning Platform to innovate and digitally transform their businesses. This session provides guidelines that organizations can use to break down innovation barriers and achieve an ML led transformation that helps them engage and serve their customers better.

  • Data and its monetization is an imperative for every Enterprise and Digital Native. Innovation with AI a need for every ISV. Intel works with the large eco-system of partners and customers to optimize their Analytics and AI stacks that brings data to life. Irrespective of the deployment of these stacks on the Edge, Cloud, or On-Prem, deployed as VMs, or Containers; Intel tools can be applied. The session will elaborate these tools, techniques and their benefits.

MachineCon 2019 Schedule

2019 Schedule

MachineCon 2018 schedule

2018 Schedule