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Pinned update
Guidelines for speakers updated Guidelines for speaking at The Fifth Elephant are updated here more
The Fifth Elephant 2023 edition #
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 Fifth Elephant 2023 annual conference will cover this lifecycle.
Editors #
The 2023 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.
Tracks and themes #
- AI and research.
- 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.
- Economies of Data Science and MLOps - covers implementation of Machine Learning (ML) lifecycle at an organization and how it is helping the organization scale.
Speak at The Fifth Elephant 2023 #
If you are interested in speaking at the conference, submit your talk idea here. The editors will review your talk description and give feedback.
Guidelines for speaking, speaker honorarium policy, and travel grant policy details are published here.
Who should participate in MLOps conference? #
- 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.
Subscribe to join #
The Fifth Elephant 2023 conference will be held in-person. Attendance is open to The Fifth Elephant-Hasgeek subscribers only. Purchase a subscription to attend the conference in-person. If you have questions about participation, post a comment here.
Sponsorship #
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.
If you are interested in sponsoring, email sales@hasgeek.com.
Contact information #
Join The Fifth Elephant Telegram group on https://t.me/fifthel or follow @fifthel on Twitter. For any inquiries, call The Fifth Elephant on +91-7676332020.
Hosted by
The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more
Accepting submissions till 30 Jun 2023, 11:59 PM
Not accepting submissions
Submission guidelines and selection criteria #
If you are interested in speaking at The Fifth Elephant, note the following guidelines:
- Submit a description of your talk, explaining the problem that your talk covers, and one concrete takeaway for audience. Talks have to give at least one practical insight to the audience.
- Preference will be given to talk experiential talks such as case studies, journeyman stories and implementation stories.
- Editors will comment on the description. Make sure to watch out for comments from Nischal HP and Sumod Mohan on your submission. Editors’ decision on which talks are selected for the conference will be final. Talks which are not selected will also receive feedback, so that speakers can present their talks at other opportunities under The Fifth Elephant umbrella.
- If you submission is included in the shortlist, you will be required to prepare an outline of your talk and go through a rehearsal.
The call for submissions will be closed on 30 June. In the meanwhile, talks will be selected on a rolling basis, as individuals make submissions.
Speaker honorarium #
Speakers will be paid an honorarium of Rs. 5,000. Honorarium will be paid after the conference is completed.
Travel for outstation - domestic and international - speakers #
The Fifth Elephant conference is financed by subscriptions and sponsorships. Limited travel grants are available for outstation speakers. These will be given on a first-come-first-serve basis.
- Speakers (or their companies) can fund their travel and accommodation for the conference in exchange for sponsorship credits.
- Speakers delivering talks as part of sponsored talks will have to cover their own travel and accommodation. This will not be counted as part of sponsorship credits.
Topics for submission #
You can submit an experiential talk on one of the following topics. You are welcome to submit talks on other topics. Focus on the relevance of the talk, who are the stakeholders who will be impacted by your talk, and what is the takeaway for them.
- AI and research.
- Decisions Intelligence Systems.
- Responsible AI.
- Privacy.
- Industrial applications of ML - implementation of AI, with more focus on the AI models, the issues in training, gathering data so, and so forth in industries such as automotive, mechanical, manufacturing, agriculture, and such. Explain the challenge you are working on, and the innovation coming out of these industries as they pursue ML on a second-to-second basis.
- Machine Learning (ML) application lifecycle at an organization and how it is helping the organization scale.
- Cloud or tools associated with ML application lifecycle.
- Data labeling and classification.
- Data security, data privacy and data governance.
- “Build versus buy” experiential case studies.
The conference is also accepting:
- Lightning talks on ideas and innovations that individuals are testing/implementing using AI.
- Showcase for open source projects built for MLOps.
If you have questions about submitting a talk or speaking at the conference, post a comment here.
Make a submission
Accepting submissions till 30 Jun 2023, 11:59 PM
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dhruvil karani Solving bias in recommender systems using negative samplingProblem # Recommender systems suffer a major deficiency in their feedback loops. When a user interacts with only a few out of many items on a website, we can only assume their interest in those specific items. Hence, the feedback is biased. more
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Arjun Jain Bumpy Roads, High Speeds: My Unexpected Journey from PhD to Tech EntrepreneurshipBackground # In 2015, I sold the intellectual property (IP) of my Silicon Valley company, Perceptive Code LLC, to Mercedes Benz. Subsequently, I was tasked with meeting certain milestones as part of the handover process. I chose to complete this task in India, where I aways wanted to be. I successfully downsized our research model, initially consuming 6GB of GPU memory, to a mere 300KB of weights… more
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Vikram Vij Forecasting @ Samsung AdsSamsung Ads is an intuitive audience platform that delivers meaningful experiences reaching the right audience across screens, formats and devices. With more than 900M Mobiles and 150M Smart TVs, and the largest first party data set powered by ACR, we help marketers reach targets and enhance experiences that span digital landscapes. The business has grown 10x since 2015. Our foundation is based o… more
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Lavanya Tekumalla Speaker lT
lavanya Tekumalla Time-series modeling for demand forecasting,Link to presentation: # https://drive.google.com/file/d/1hH90FCWxRFv0IQcoBqX2yRM1DcTzDBQr/view?usp=sharing more
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Narayanan Subramaniam  Sustainability: Design Considerations for Real-World ML-based Process Model Training & IT/OT-to-SaaS Data Integration for Industrial DecarbonizationIndustry (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. more
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Abhinav Dadhich Learnings from Building Deep Learning Models for Better Cardiac CareAbstract: # Echocardiogram(Echo) is one of the common modality that captures state of the heart in the form images and videos. Using Ultrasound technique, an echo study captures multiple cross sections of the heart, termed as Views. Cardiologist utilizes measurements on the basis of these Views to analyse heart functions. In order to automate this process to measure how heart is functioning, an i… more
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Ajeevansh Gautam Elevating High-Quality Calls: Harnessing the Synergy of ML and Innovative Architecture at SquadStackProblem Statement # In our journey at Squadstack, we encountered a significant challenge in maintaining exceptional customer interactions during telemarketing calls. We realized the need to evaluate callers based on various parameters to identify and flag undesirable interactions, this would become a robust solution and will help streamline the evaluation process and provide targeted training int… more
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Ravi Theja  Glance TV - Revolutionizing Television Screensavers with AIProblem Statement: Television screensavers, though often visually appealing, are frequently static and detached from the dynamic world we live in. They do not offer users relevant, real-time information or the ability to customize content to suit their preferences. The disconnect between screensavers and the rich media environment of the digital age presents a need for innovation. more
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Siddhant Agarwal Graphs are everywhereGraph databases and social graph Graph databases are the most scalable, high-performance way to query and store highly interconnected data. They help improve intelligence, predictive analytics, social network analysis, and decision and process management – which all involve highly connected data with lots of relationships. A relevant use case for graph databases is the social graph. more
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Arvind Saraf Title: Building real-time video-based analytics productAbstract: # Companies are now building products using real-time computer vision and machine learning of video from various systems and processes. This requires a full stack system consisting of video ingestion and storage, live inferencing, post-processing of data generated, and use of the data in the business context or customer’s domain language. We demonstrate a preferred architecture and stac… more
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AJ
Ayyanar Jeyakrishnan  MLOps for Enterprise using AWS SagemakerMy Previous Session MLOps for Enterprise on Sagemaker https://github.com/aws-data-usergroup-bangalore/sagemaker-mlops more
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Srinivasa Rao Aravilli Privacy Preserving Machine Learning at ScaleIn this talk , I will talk about privacy risks with Machine Learning and explain in detail about Privacy Preserving Machine Learning techqniues. Introudce variious frameworks which can be used to implement to protect ML Models, Training Data, Inference Results from privacy threats. Talk about privacy threats in Large Lanauge Models ( LLM’s) and varous benchmarks in ML with resepct to privacy pres… more
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Rohit Agarwal 7 mistakes while deploying GenAI apps in productionI’ve built production LLM systems and made multiple mistakes. The talk will focus on key areas to focus on while deploying LLM and Generative AI systems in production more
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Vikas S Shetty Ensemble Techniques for Object Detection ModelsDNN (Deep Neural Network) models are nonlinear and have a high variance, which can be frustrating when preparing a final model for making predictions. In order to get good results with any model, there are certain criteria (data, hyperparameters) that need to be fulfilled. But in the real-world scenario, you might either end up with bad training data or might have a hard time figuring out appropr… more
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Hosted by
The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more