Session on "Use Cases and Risks of ML in Capital Markets" | 23rd Dec at 4pm Hi everyone! The AI and Risk Mitigation project is well underway and for the third session, we will be joined by Rachna Maheshwari, Associate Director at CRI… more
The 2023 Monsoon edition is curated by:
- Nischal HP, Vice President of Data Engineering and Data Science at Scoutbee. Nischal curated the MLOps conference which was held online between 23 and 27 July 2021.
- Sumod Mohan, Founder and CEO at AutoInfer. Sumod curated Anthill Inside 2019 edition, held in Bangalore on 23 November.
- AI and Research - covers research, findings, and solutions for challenges on building models in various areas such as fraud detection, forecasting, and analytics. This track delves into the latest methodologies for handling challenges such as large-scale data processing, distributed computing, and optimizing model performance.
- Industrial applications of ML - covers implementation of AI in the industry, with more focus on the AI models, the issues in training, gathering data so, and so forth. ML is being used at scale in industries such as automotive, mechanical, manufacturing, agriculture, and such domains. This track focuses on the challenges in this space, as we see innovation coming out of these industries in the pursuit of using ML on a second-to-second basis.
- AI and Product - covers strategies for building AI products to scale and mitigating challenges. This track provides insights on incorporating AI tools and forecasting techniques to improve model training, developing a working model architecture, and using data in the business context.
There are three phases in the lifecycle of an application - research, application and aftermath of the application.
- Assess capabilities, determining the new frontiers for AI.
- Find a use for the application.
- Learn how to run it, monitor it and update it with time.
The three tracks at the 2023 Monsoon edition of The Fifth Elephant will cover this lifecycle.
The Fifth Elephant 2023 Monsoon edition will be held in-person. Attendance is open to The Fifth Elephant members only. Pick a membership to attend the in-person conference. If you have questions about participation, post a comment here.
- Data/MLOps engineers who want to learn about state-of-the-art tools and techniques, especially from domains such as automobile, agri-tech and mechanical industries.
- Data scientists who want a deeper understanding of model deployment/governance.
- Architects who are building ML workflows that scale.
- Tech founders who are building products that require AI or ML.
- Product managers, who want to learn about the process of building AI/ML products.
- Directors, VPs and senior tech leadership who are building AI/ML teams.
Sponsorship slots are open for:
- Infrastructure (GPU, CPU and cloud providers) and developer productivity tool makers who want to evangelise their offering to developers and decision-makers.
- Companies seeking tech branding among AI and ML developers.
- Venture Capital (VC) firms and investors who want to scan the landscape of innovations and innovators in AI and who want to source leads for investment in the AI and ML space.
Sustainability: Design Considerations for Real-World ML-based Process Model Training & IT/OT-to-SaaS Data Integration for Industrial Decarbonization
Industry (Minerals & Mining, Steel, Cement, Oil & Gas to name a few) comprise nearly 50% of total Green-House-Gas (GHG) Emissions and in the context of the Climate Crisis it is imperative to De-Carbonize existing processes in these industries while new processes with reduced carbon footprint are being introduced subject to availability of technology and suitable financing.
While there has been progress made on sensorization and digitization of process lines in the above mentioned industries, it is imperative to take a step back to assess the essential design considerations around sensor redundancy, calibration, data silos, scalable and highly available data pipelines, as well as the balance of Edge versus SaaS while coming up with an effective IoT-based IT/OT system design that captures real-time process and emissions (CO2, CH4, NOX, SOX, VOC) data from terrestrial and arial (satellite, drone) based systems.
In addition, all AI/ML based models need to have a proper foundation and insights of the real-time processes being modelled so that there is an explainable and rational basis that validates the reliability of AI/ML based models with deep domain expertise and tribal knowledge maintained by highly experienced process line operators. Design around process time lags, process and equipment degradation, limitations of forecasting and what-if analysis, real-world input raw material and environmental variations are few of the major challenges in applying AI/ML in these complex domains where MLOps maturity becomes all the more relevant.
This talk will help to shed light on the real-world design considerations based on the observed challenges and domain insights for a specific set of use industrial cases, which in a generic sense could be applied across the board.
I am currently the Founder & CTO of https://vanashri.com, helping companies in leveraging technology for a more sustainable planet, with past Sustainability experience in the Electric Vehicles space, and in Industrial Decarbonization in the Steel and Mining sectors.