India's Biggest AI Summit

October 11-13, 2023

The Cypher 2023 will highlight the new innovations that will drive the world’s next wave of change, balancing these breakthroughs against a world that has grown more skeptical about the benefits of the data revolution.

2023 agenda

AI and the Future of Work: Discussing the impact of AI on the workforce, job automation, reskilling, and the gig economy.

Advancements in Generative Models: Showcasing the latest research and innovations in generative AI, including GANs, VAEs, and autoregressive models.

AI for Simulation and Design: Investigating the role of generative AI in creating realistic simulations for training, product development, and virtual environments.

Generative AI for Sustainability: Discussing the use of generative models in optimizing resource allocation, addressing climate change, and promoting sustainable development.

Generative AI in Product Development and Design: Discussing the role of generative models in accelerating product ideation, design exploration, and prototype generation.

Automating Business Processes with Generative AI: Investigating the potential of generative models in automating routine tasks, document processing, and decision-making across various industries.

Scaling Generative AI Solutions: Discussing strategies for implementing and scaling generative AI solutions in enterprises, addressing challenges related to data quality, computational resources, and model interpretability.

2022 Schedule

We are in the process of finalizing the schedule. Please check back this space again.

Expect more than 100 speakers to speak at Cypher 2023

To explore speaking opportunities with Cypher, write to info@analyticsindiamag.com

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  • Day 1 Hall 1

    Sep 21, 2022

  • In the age of algorithmic enterprise, businesses that embrace digital along superficial lines usually fail to accelerate. What most end-users want from AI-based applications are empowerment and transparency. This translates to safeguarding shareholder investment and helping ensure a suitable return on investment (ROI), both now and in the future. Businesses must perform effectively, profitably, and sustainably. So, what makes these enterprises of the future succeed? Is it the AI, is it the human capital or is it a combination of both? What works and what doesn’t work yet for these enterprises?
    Hall 1: Visionary Insights

  • Google has been at the forefront of leveraging machine learning across all its consumer apps. This is something perhaps everyone attending knows and has experienced. This talk aims to inspire the audience with the number of areas google is looking to solve for using deep learning. The talk also covers how being true to its mission statement of making that knowledge accessible and useful providing access to the innovation via its open source contributions and enterprise grade cloud platform
    Hall 1: Visionary Insights

  • After significant technology advancements, organizations are starting to use AI towards concrete business outcomes. While over 90% executives have plans to adopt AI in their businesses, only 18% are confident of it translating to a P&L impact. The need of the hour is realizing real world business benefits and generating measurable monetary impact from AI initiatives. This requires a transformative change across the way organizations think of business models, business strategy, value chains and ways of working enabled by technology and business interventions. In this talk, Prashanth Kaddi, Partner at Deloitte, will present his perspective on how organizations can achieve it and their experiences in helping organizations in this journey.
    Hall 1: Visionary Insights

  • In current turbulent times mired in diminishing skills longevity, Businesses and their L & D are collaborating to future-proof their organizations. A wholesome learning & development for employees at all levels of the talent pyramid ranks high on the enterprise agenda. Join this keynote featuring Minaxi Indra (President, upGrad for Business) and Moytreyee Konwar (Vice President, Products and Programs, upGrad for Business) for practical insights on implementing a reflective business outcomes-oriented Learning and Development Strategy driven by business practices.
    Hall 1: Visionary Insights

  • The health care industry is striving to put the consumer at the center of the ecosystem and find affordable ways to offer more access, choice and control. The possibilities unleashed by digital technologies such as AI, wearables, IoT, 5G and genomics are enabling new ways of thinking and new inventions that can increase mobility and convenience. Consumerism, continuous care and care at home will be the future of health care delivery. In this session we look at how digital health solutions can bring these three together and make the health system work better for everyone.
    Hall 1: Visionary Insights

  • Panel to address the following - a) Criticality and importance - impact on the client value creation b) Domain knowledge - a foundational & integral part of Data Analytics capability development across management levels c) Challenges at play - for the business and the learning function d) Industry best practices e) Way forward
    Hall 1: Visionary Insights

  • According to recent reports by BCG, 1.6 billion tons of food worth about $1.2 trillion are lost or go to waste—one-third of the total amount of food produced globally. $460B/year is waste/loss from Storage to the Distribution value chain. The problem continues to scale yearly, and worldwide hunger and poverty remain at bay.
    Hall 1: Visionary Insights

  • Decision-making is fundamental to driving business value in any process or Operating unit. Businesses and Operations are realising that their job description is changing from “managing and executing transactions” to “generating insights which help in better decision making”. This needs complete repivot on the skilling of an Operations – both in terms of content, scale and speed. Data Democratization would enable Citizen Insight generation which will become a competitive differentiator for the enterprise of the future – through predictive problem solving
    Hall 1: Visionary Insights

  • Technology has been a major part of cricket. It has helped the management strategies and player selection, identifying their flaws and improving the game. In this discussion, India’s former cricket captain, Kapil Dev, will talk about the use of data and analytics in cricket, share some past experiences, difficulties, and learnings as to how he used data during his cricketing career, how it has changed/transformed over the years, and also give us insights as to what is being used currently. Dev is one of the successful captains of Indian cricket history, who led his team to win its first-ever World Cup in 1983, held in England. The recent biopic of his ‘83’ captures this. This discussion will also touch upon his learnings over the years, leadership style, success mantra, and more.
    Hall 1: Visionary Insights

  • Day 1 Hall 2

    Sep 21, 2022

  • Today, Industry 4.0 is the most refined technology for allowing intelligent and automated business applications. IoT, Big Data, Data Science, and artificial intelligence (AI) are growing technologies that are frequently used in industry. When developing a large-scale, real-time AI application system, data scientists must work on many technologies in Machine Learning and Deep Learning algorithms to push their applications; the AI application is resource (Compute and data) hungry. Modern Python software enables for the rapid implementation of AI & Data science algorithms such as recommendation engines, fraud detection, voice assistance, and so on. The Machine Learning algorithm is the foundation of every AI system. Machine learning algorithms learn from data and use hidden patterns in data to accomplish a certain objective.

    The Intel oneAPI software creates an ecosystem of software tools that are optimized for AI training and inferencing. In this workshop, we will look at how to work on optimized frameworks like Tensorflow and Pytorch for accelerating inferencing workloads for deep vision algorithms like CNN, GAN, and Transformers on images and videos. The workshop will provide technical knowledge on oneAPI AI toolkit optimisation frameworks and how these libraries aid in boosting current deep vision models, followed by a hands-on session for participants on the Intel Dev cloud platform.  

    Participants Prerequisites of the workshop

    INTEL WORKSHOP CONTEST

    Hall 2: Solution Spotlights

  • We are living in the information era where every second we are producing plethora of data. Now, businesses have started unlocking the power of user data collected so far and how to leverage it to provide enhanced experience to their customers. However, It is imperative to preserve privacy of users in the process of data sharing while maintaining the utility of data. Differential privacy is helping us to tune privacy guarantee and utility of the data based on goal of data sharing.
    Hall 2: Solution Spotlights

  • The talk is about implementing research in the area of Deep Learning and successfully applying them in various use cases. A few things that would be covered include using a custom loss function and leveraging state of the art “Attention” concept to tabular data. The talk would cover practical aspects and pre-requisites when applying some of the recent findings in everyday projects.
    Hall 2: Solution Spotlights

  • Adopting a data driven decision making culture involves many aspects – from upgrading the data management, analytics, governance to and probably most importantly, upgrading the decision making paradigm. The speaker talks about experiences in transforming organization from traditional analytics eco-systems, to the modern, machine learning, fast paced and nimble organization winning in the market.
    Hall 2: Solution Spotlights

  • In this talk she discusses the current state of applications, the way to progress and five principles of cloud-native architecture that will help customers design systems to take full advantage of the cloud while avoiding the pitfalls of shoe-horning old approaches into a new platform.
    Hall 2: Solution Spotlights

  • Airlines have always been at the cutting edge of leveraging data and data science in business operations. This talk will provide an exposure to the spectrum of data science problems that are addressed and solved on a daily basis to provide you the safe, reliable and comfortable flying experience that you have come to expect from your favorite airline.
    Hall 2: Solution Spotlights

  • Sustainable Development Goals (SDG have been setup by the United Nations in 2015 and intended to be achieved by 2030. In total, 17 SDGs have been identified some notable ones being No Poverty, Zero Hunger, Quality Education, Good health, Clean Water, Sustainable Energy, Affordable and Clean energy. The current pace of incremental development in those focus areas makes it almost impossible to attain the goals by 2030. This talk focusses on how some of the important SDGs could be achieved by the use of Artificial Intelligence.
    Hall 2: Solution Spotlights

  • Day 1 Hall 3

    Sep 21, 2022

  • Travel e-commerce data science space is complex. While there are many success stories, the offline metric improvement/lift and online business metrics may not align in many experiments. The offline model development and deployment strategy suffices in majority of cases. But one must monitor concept drifts, data drifts, remove training data sample selection biases, remove target leakages, minimize omitted variable biases and handle other aspects in applied data science world. Also, on many occasions there may not be sufficient data points for every decision, to learn with high degree of confidence which decision is better or worse to recommend. Considering these factors, we found reinforcement learning or contextual bandits useful. Combine these with online/offline batch learning, and deep learning representation models. At MakeMyTrip-GoIbibo group, we have built in-house platform to facilitate data scientists to quickly launch such experiments and move towards continual learning. This talk is about the problems, platform, use cases/examples we solved upon with this framework, glimpses into a few bandit model forms, off-policy evaluation metrics we use, and also how we combined these models with multi-objective decision methods such as pareto frontiers.
    Hall 3: Tech Deep Dives

  • In the book Predictive Machines, Prof. Ajay Agarwal, explains the economics of AI as centered around bringing down the cost of ‘predictions’. In healthcare, there are several critical patient-centric questions that can be best formulated as predictions – predict which patient is at higher risk for a certain disease, predict which patient would benefit from a novel treatment, predict which patient would be a non-responder, predict which patient will not be adherent to treatment. These patient prediction problems offer a rich testing ground to evaluate a range of AI paradigms – from foundational to emerging and the value they can provide to address these high impact patient-centric questions. In our ZS AI lab, we focused on a particularly complex version of these patient prediction problems – identifying patients who are suffering from rare conditions (affecting <1 in 2000 people) but are currently either undiagnosed or misdiagnosed. During the talk, we will motivate why this is both a hard and an important problem to address. We will highlight a series of systematic experiments that our ZS AI lab scientists conducted to tackle the key challenges underpinning this problem including noisy labels, high data cardinality, and the temporal patient journey dynamics. We will share the meta-learnings from our research - in particular, our findings on the relevance of semi-supervised and generative models. Given the complexity of both the central prediction problem and the overall healthcare domain, we are continuing to enhance our approach along a few key dimensions – the core prediction algorithms, technologies to handle data complexities, and improving model trustworthiness to drive broader adoption with healthcare stakeholders. We will share more on these forward looking aspects. Our broader goal at ZS is to improve health outcomes for all. Realizing this goal requires the best minds to come together, share, discuss, and collaborate. During the session we would, therefore, love to hear your thoughts and experiences with analogous problems and in adjacent fields. Please join us at the session – a small step towards the broader goal of moving from the current state of ‘sick-care’ to truly healthcare.
    Hall 3: Tech Deep Dives

  • Climate change is a globally relevant, urgent, and multi-faceted issue heavily impacted by energy policy and infrastructure. Addressing climate change involves mitigation (i.e. mitigating greenhouse gas emissions) and adaptation (i.e. preparing for unavoidable consequences). Mitigation of GHG emissions requires changes to electricity systems, transportation, buildings, industry, and land use. In this Tech Talk we will be estimating the building energy consumption using various libraries of Intel® oneAPI Toolkits(Intel® AI Analytics Toolkit ) like Intel® Distribution for Python* including highly-optimized scikit-learn and XGBoost libraries Intel® Optimization for TensorFlow* Intel® Optimization of Modin* (available through Anaconda* only). Demonstration of running the notebook using Intel DevCloud . The demo will also showcase how Intel oneAPI is six to seven times faster than the other frameworks
    Hall 3: Tech Deep Dives

  • AI and Cloud Computing have transformed our lives drastically. Every day, people use digital assistants like Siri, Google Home, and Amazon's Alexa, which execute spoken commands such as playing music on a connected speaker, buying a product online, etc. However, AI algorithms have one major drawback- they rely on cloud servers to perform computations and can't power mobile phones, computers and other devices whose applications use AI. Hence AI has limited relevance in areas of sparse connectivity. Another issue caused by AI applications hosted in the cloud is privacy. There are scenarios in which sending personal data to the cloud for processing by ML applications might not be a possibility. Hence, doing ML inference on edge then becomes important. In this session Gunnvant will talk about the edge ML ecosystem that is in place today and is accessible to tinkerers and hobbyists. A discussion on how anyone can get started with writing AI applications on edge and embedded devices will be undertaken. The session will also focus on hardware options that are in place, the software ecosystem that exists, the capabilities and limitations of contemporary stack.
    Hall 3: Tech Deep Dives

  • Over the past 24 months, companies in the oil and gas supply chain have been struggling with supply chain uncertainties and logistics. Challenging external forces are not new to oil and gas marketing companies, but the pace that it happened in last couple of years have forced them to adapt with greater speed and agility to address the current landscape and prepare for a new market reality. This talk covers how oil companies can conduct accurate forecasting and find out ways to fulfill the same using linear programming.
    Hall 3: Tech Deep Dives

  • Artificial intelligence promises to change virtually every aspect of our jobs and personal lives. Already, its influence is undeniable in most aspects of our lives. In the excitement over AI (and the constant debate about its negatives), people often forget that a human element remains critical to technological success. Yes, machines will play a greater role in the economy of tomorrow, and yes, they may replace select jobs that humans currently perform—but people will still be critical to the success of AI This talk will address the advancements in the field of AI in the next decade, its interaction with humans and how this delicate balance needs to be addressed.
    Hall 3: Tech Deep Dives

  • Day 2 Hall 1

    Sep 22, 2022

  • Artificial Intelligence (AI) is transforming industries and solving important, real-world challenges at scale. According to McKinsey, in less than 10 years, AI may be the number one driver of global GDP growth. This is a staggering prediction. Over this next decade, we will see incredible adoption and innovation; in fact, applications that aren’t AI-enabled may feel broken. Google has consistently been recognized as the industry leader in AI/ML. This session will offer an overview of how we at Google are using AI to power some of our own planet-scale applications that touch over 1B+ users each, how we are helping other organizations realize the full potential of AI, challenges in scaling AI and our latest technology innovations that make these fascinating applications of AI possible at scale.
    Hall 1: Visionary Insights

  • Organizations today must embrace DataOps considering the growth in data and the data-driven mandate businesses have to improve outcomes across. Operationalization of data across its lifecycle starting from ingestion up to consumption must be orchestrated for driving seamless flow of data across data pipelines, delivering lineage/ provenance of data to drive adoption while empowering the consumption ecosystem to be aware of the change data will go through from time to time. DataOps strives to foster collaboration greater visibility and coordination between teams leading to better adoption, insights, and improved business strategies.
    Hall 1: Visionary Insights

  • AI enables businesses to make faster decisions, improve operations, and create new revenue streams. However, the full potential of data science and AI can be leveraged by optimizing and automating them. Feature Store is a centralized environment for organizing, storing, and managing ML features. Feature Store enables enterprises to discover, distribute, and deploy ML features at scale, resulting in faster development, deployment, and operationalization. During his keynote, Soumendra will speak about accelerating AI adoption and Feature Store's role in rewiring business impact during his keynote speech.
    Hall 1: Visionary Insights

  • Today in modern data architectures we hear a lot about a new sensation called Data Lakehouse. This talk firstly addresses what is a lake house, what are the perceived missing aspects and how Vertica can help going beyond.
    Hall 1: Visionary Insights

  • What does it take to ensure our workforce is always one step ahead of the industry need? If tech evolution is a continuous process, how can L&D keep up with the curve? Is it time to treat ‘skilling’ as a business investment and not an expense? So many questions. The bottom line? To build organizations that are capable of innovating. We must unlearn our conventional notions of leadership and rethink how continuous learning can happen. Sumanth Palepu, Senior Director-Edology, in his keynote address will answers these questions and present you solutions on cultivating life-long learning.
    Hall 1: Visionary Insights

  • While investments in AI continue to rise worldwide, companies still struggle with the ground level gains. Misalignments between business and technology and a lack of planning ahead are key issues to not realising the potential of AI adoption. As businesses think about adopting AI, they need to look at it in terms of what current problems can be solved with the AI&ML approach-not all can! Looking at gains and pains for clearly articulated AI&ML business use cases helps develop a short and long term strategy for AI adoption. Concentrating on high gain and high pain problems early on in the adoption journey can completely derail the entire initiative! How execution leaders think about people, data, performance and productionization of initiatives seals the case for how successfully AI will generate revenue for the company. The AI adoption process needs to be thought of more like a new type of process where change management, implementation and last mile execution are critical to success. Top level executives have to drive change downwards and hiring a data science head and team does not ensure that happens. Planning before jumping into AI changes the 85% failure rate to success. There are practitioner frameworks and solutions available that can help companies not just adopt AI but drive revenue from it.
    Hall 1: Visionary Insights

  • Businesses must make crucial decisions when they should. And it can only take place if businesses are able to utilise the value of data in real time. They have the ability to quickly and digitally crunch information, examine trends, obtain insights, and make judgments. Data may speed up decision-making within a company and be a growth multiplier for businesses. The panel will be frank about the difficulties businesses have using data to its full potential.
    Hall 1: Visionary Insights

  • Through the rise of digital commerce, marketers and advertisers have relied heavily on third-party cookies to target audiences online. However, plans to phase out third-party cookies by the end of 2024, has left marketers unsure of how to deliver personalized experiences at scale; this could end up costing up to $10 billion in ad revenue. As the death of third-party cookies looms, the need of the hour is to find an AI-enabled approach to build data strategies and identity platforms to keep delivering personalized experiences. Merkle’s Geetha Apathotharanan & Sonia Thakurani share an innovative AI-enabled enterprise identity solution to help brands create unique customer IDs and map customer journeys using first-party data; thus enabling more contextual and personalized customer experiences in a cookie-less world.
    Hall 1: Visionary Insights

  • Creating ML models needs an understanding of the tools and domain knowledge. Given the difficulty in getting data scientists that understand your domain, several AI/ML initiatives never see the light of day. Another challenge is data preparation and real time operational data availability. 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, you can transform your business analyst, who already understands your domain and business, into a citizen data scientist. In addition, Qlik Data Integration helps you leverage real time streaming data from your operational systems streamlining your data pipelines with minimal IT resources.
    Hall 1: Visionary Insights

  • One thing that comes to mind as an after-effect of automation or AI is making human resources obsolete or redundant. However, this is entirely not true. Throughout the history of technological advancements, we have seen humans still being employed, and in fact, more employment has been generated because of these technological disruptions. In this fireside chat, we will discuss: Chetan Bhagat's views on technology disruptions and how he stays up to date with the latest happenings in the world of AI and ML, alongside discussing some of the tools and platforms he uses as a writer and how it has helped him. Also, talk about how India can be ahead of the curve, surpassing these negative connotations. How can India build those capabilities? Why are students going abroad for studies and job opportunities? What is missing in India, particularly in the educational system? Segment 02: Escaping Corporate Life: A Fireside Chat with Chetan Bhagat Chetan Bhagat has spent a fair bit of time working in a corporate setup before venturing into a creative endeavour in 2009 to write full-time. He also runs a podcast called 'Deeptalk,' where he has interviewed some renowned CEOs and celebrities. We will touch upon: His learnings, struggles, views on corporate work culture, leadership style, and the success mantra he follows in life and how it has changed over the years. Some of the struggles and challenges that CEOs have encountered in their career, especially in India, and some leadership philosophies and values to become a successful entrepreneur or a leader. Also, discuss some of the characters in his books inspired by colleagues and bosses. Segment 03: Rapid Fire questions on some candid topics
    Hall 1: Visionary Insights

  • Day 2 Hall 2

    22 Sep 2022

  • Artificial Intelligence (AI) is transforming every aspect of our lives. It is reshaping our economy, society and our lifestyle. Human interface and relationship with machine is undergoing significant changes. Promises of AI are plenty for mankind as well as for enterprises. However with such a power technology, there is a need for responsible usage of AI. Catch Hasit in his session to learn his thoughts on this topic.
    Hall 2: Solution Spotlights

  • While organizations have been using internal data to sharpen their analytics initiatives, companies now have exposure to numerous external data sources such as location, customer preferences, shopping trends, market news, app usage and social media sentiments that if strategically integrated can enable sharp business decisions. According to a Deloitte survey, over 90% data analytics professionals realize the importance of utilizing external data sources to get better insights on shifting consumer behavior, market insights and competitor initiatives. This talk covers how companies can internalize the external or third-party data to unlock improvements in their analytics initiatives.
    Hall 2: Solution Spotlights

  • AI is fuelling transformation across all domains of retail such as eCommerce, supply chain and in-store experience. At Walmart, AI technologies empower us to achieve our purpose – help people save money so they can lead better lives. Across our physical stores and online eCommerce business, AI use-cases are increasingly being applied at scale. In this talk, we will illustrate how AI is a gamechanger for Walmart and also the future of retail. We plan to dive deep into two use cases to talk about the end-to-end lifecycle journey of the solution and its impact with AI technology.
    Hall 2: Solution Spotlights

  • While opportunities to learn and grow has always featured as a key driver of great work culture and employee engagement, business and L&D has traditionally not been confident of formally stating dependence of business sustenance and growth on employee upskilling. Join this panel discussion to hear eminent business leaders engage in a fact-based discussion to establish or debunk this linkage.
    Hall 2: Solution Spotlights

  • Businesses have started to realize the potential of AI/ML solutions for transformational gains. While the potential upsides to AI/ML engagement are evident, these solutions also bring with them new challenges and threats, making organizations susceptible to risks. These challenges can arise due to different reasons such as Data Management, Cybersecurity, Algorithmic Bias, or Behaviour Manipulation. A well-defined Responsible AI strategy with a robust framework for implementation enables leaders to overcome such risks and safeguard ethical, legal, environmental, and social concerns.
    Hall 2: Solution Spotlights

  • Our healthcare system is broken: it’s expensive, slow-moving, and even unattainable to some. So, where do we go from here? As the healthcare system looks to adopt newer technologies, is AI the answer to mending a broken system? In this session, hear on the future of AI in health and its role in improving access and affordability.
    Hall 2: Solution Spotlights

  • In this working session, We will focus on use cases depicting how real-time data pipelines on BQ fuel different initiatives at Bhartatpe. We will be covering topics like - Anomaly and Fraud Detection Risk Analysis and Monitoring Prediction and Forecasting Tailor-made customised offers Credit Score and financial recommendation Clustering and segmentation
    Hall 2: Solution Spotlights

  • ‘AI’ used in mission-critical uses cases like autonomous cars, financial institutions, healthcare etc., carries a substantial financial and societal risk. It is required to address the specifications/requirements of all stakeholders like - Customers, Business owners, Product owners, the Data Science team, Risk managers and Regulators. Requirements like - how did the model work for a prediction? Was there a bias? Did the team follow all necessary steps before pushing the model into production? Can I provide satisfactory evidence about model functioning to regulators? How can I audit my AI models? Was the model consistent in production? When should I retrain my model? What was the reason for the error in production? etc. A good ML Observability framework can solve this problem at scale for businesses. In this session, you’ll learn more about the components of good ML Observability tools for mission-critical AI solutions and successful case
    Hall 2: Solution Spotlights

  • Day 2 Hall 3

    22 Sep 2022

  • Building a clinical search engine that thinks and works the way you do, making it easier to find and apply relevant knowledge. Empower clinicians and students to make faster, better decisions and avoid errors at the point of care through access to the most complete and trusted evidence-based content. Sneak peak of the search functionality of Clinical Key offerings.
    Hall 3: Tech Deep Dives

  • Datasciences profession has been tagged with some rather cliched terms and is often in limelight for the right reasons of its contribution in powering product and experience differentiation. While many industry segments and enterprises of varied scale have setup data sciences teams, the focus of development has primarily been on technical skills. Join this presentation by industry and academia veterans to decipher how to craft a holistic success profile of a rockstar datascientist and leveraging it to power employee development.
    Hall 3: Tech Deep Dives

  • The talk would discuss about challenges w.r.t data and quality of AI models in healthcare – how can we build high quality AI models in healthcare with less data: the challenges and opportunities. How building AI models in health care is different from other industries.
    Hall 3: Tech Deep Dives

  • Within healthcare, technologies such as AI/ML, predictive analytics etc. can be applied to augment human tasks. This may involve assisting disease progression management, tailoring care decisions to individuals, early identification of disease or utilization, improving engagement and adherence, and improving efficiency and consistency of administrative processes. In this session we look at the benefits and pitfalls of using digital health solutions in building a truly modern health care ecosystem.
    Hall 3: Tech Deep Dives

  • Across industries, enterprise leaders are ramping up digital initiatives at an unprecedented pace, reinventing how we live and work. But as these projects get underway, it has been witnessed that roughly only half of all AI proofs of concept ever make it to production. The complexity of ML implementation varies with increasing degrees of expectation from ML infrastructure, model complexity, and deployment. At its core, machine learning operations (MLOps) help teams consistently develop, deploy, monitor, and scale AI and ML models, mitigating the potential risks associated with not having a framework for sustainable innovation.
    Hall 3: Tech Deep Dives

  • Day 3 Hall 1

    23 Sep 2022

  • Machine Learning (ML) has quickly become ubiquitous in banking for both predictive analytics and process automation applications. However, banks in the US remain cautious in adopting ML for high-risk, regulated areas like credit underwriting due to key concerns including ML explainability and robustness. To address the inadequacy of post-hoc explainability tools in XAI for critical applications, we have developed inherently interpretable machine learning models, including Deep ReLU networks and Functional ANOVA-based ML models. Model robustness is a key requirement as models will be subjected to a continually changing environment in production. A conceptually sound model must be able to function properly – without continuous retraining – while remaining relatively invariant in a changing environment. Recently, we released the PiML (Python Interpretable Machine Learning) package as a tool to design inherently interpretable models, and to test machine learning robustness, reliability and resilience.
    Hall 1: Visionary Insights

  • AI is undoubtedly impacting the way of life, though not without its challenges. 'Life 2.0' is what is believed to emerge as this technological revolution advances. At present, Governments globally are looking to invest in it as well as blend it into policies that will not only help economic growth but individual corporate growth. When considering other stakeholders, questions now arise on what impact it currently has in our day-to-day, what can corporations do (particularly where AI and diversity is concerned) and how can we ensure that this technology is used responsibly.
    Hall 1: Visionary Insights

  • -Traditional Design Thinking -The Human Story -Design Thinking in with Lego Play -The element of Design Thinking in AI
    Hall 1: Visionary Insights

  • Building AI & Data products requires strategizing across data collection & scaling techniques, accounting for uncertainty in AI outcomes, and building feedback loops for the AI flywheel effect. In addition to ML techniques strategies, MLOps and Data architectures are also critical. This talk will go through frameworks, challenges and best practises on these topics.
    Hall 1: Visionary Insights

  • Being data-driven organisation is table stakes in today’s hyper competitive environment. In this talk, we will start by sharing our Data Platform strategy at Udaan, which has enabled us to unlock value from our data by embedding data driven decision making in all workflows. Then we will touch upon the worrying trend that nearly 85% of AI/ML models don’t make it to production and will share personal experience on how to mitigate the same. We will end by sharing the data science problem landscape for B2B e-commerce and will go through one use case demonstrating the various ML Ops capabilities that has enabled successful deployment of sophisticated, state-of-the-art ML model.
    Hall 1: Visionary Insights

  • AI-driven facial recognition software is probably the most divisive technology deployed today. This is not only because of the social implications it can have on individuals or certain sections of society but also because the technology itself has proven to be unreliable. Several accidents or instances of misuse have led law enforcement agencies to shut down its use in the US and other countries. While that is the case, Indian governments are on a spree to implement automated FRTs. Also, India doesn't have the appropriate legal frameworks to avoid its implications, such as mass surveillance and misuse of personal data, or accountability frameworks when it works erroneously. All socio-technical factors considered, should FRTs be banned altogether in India?
    Hall 1: Visionary Insights

  • While we understand the cognitive (and logical) algorithms “on the surface of the mind” how much do we understand the unconscious part of our mind and personality? While exploring the unconscious in human beings itself is a difficult task, would AI be able to incorporate both conscious and unconscious part of our awareness? The session looks at Human unconscious and how it influence our behavior and explore what could be a future possibility where machines could also have an unconscious. Santhosh also would be demonstrating hypnosis in this session on some volunteers
    Hall 1: Visionary Insights

  • Day 3 Hall 2


  • - Traditional methods for CX are not suited for the digital era - Customer Data Lake is a pre-requisite for data-driven CX - Data Analytics journey for CX should evolve in 4 stages - Practical use cases for application of Data Science for CX
    Hall 2: Solution Spotlights

  • Unleashing the power of data has great potential to drive significant business outcomes and can create real business differentiation. The journey to realizing this potential involves several important decisions to be made along the way and requires a mindset shift. The Digital Leader plays a critical role in facilitating this transformation and orchestrating the journey. This session attempts to provide a point of view on the role of the digital leader and highlight some of the critical aspects around a wholistic approach assimilated through personal experiences.
    Hall 2: Solution Spotlights

  • FMCG sales has always been about scale. For a company like ITC, the sales & distribution network covers the Indian retail landscape at a speed of 10 stores per second, as the salesmen cover 4 times the earth's circumference very day! While building personalized recommendations is a mature machine learning process, how do the models work around the most crucial human in the loop - the salesman?
    Hall 2: Solution Spotlights

  • how analytics enables entire branch banking space n engaging with right client and garnering max deposits with use of models
    Hall 2: Solution Spotlights

  • "Metaverse is an emerging paradigm from both technical and business perspectives. 3D Modeling plays a key part in the metaverse experience. Recently, Computer Vision and Deep Learning Techniques are being employed in order to meet the challenges of scale, quality and superlative customer experience. In this talk, I will cover the variety of problems that can be addressed by Computer Vision and Deep Learning including personalization, animation, speech personalization and content generation. Specific emphasis would be placed on topics such as 3D Avatar personalization, Full body animation, lip-sync from audio and video and content generation in 3D contexts. AI models including Generative Adversarial Networks, Vision Transformers, Zero-Shot speech personalization and mult-modal transformers would be covered along with corresponding applications."
    Hall 2: Solution Spotlights

  • "* what is product analytics ? * how analytics and data is used to drive product decisions ? * How are hypotheses created ? * what is north star matrix ? * what are tools and techniques for product analytics ?"
    Hall 2: Solution Spotlights

  • Jupiter.co is a social commerce food company based in San Francisco, California. Jupiter helps food creators from TikTok & Instagram launch their own grocery powered recipe shops to sell directly to their followers nationally. Aarshay is a founding team member at Jupiter, leading all personalization efforts from the get go. In this talk, he will be sharing his experiences in deploying data/ML pipelines from a blank slate in the context of early stage startups. He will be discussing various applications of data/ML at Jupiter, along with the learnings and nuances which were unravelled along the path from a blank github repo to a monorepo which powers both data pipelines and serving infrastructure.
    Hall 2: Solution Spotlights

  • Day 3 Hall 3

    23 Sep 2022

  • The availability of more data than ever before together with sophisticated modeling techniques and high computational power to process data has changed the landscape for analytics driven business decision making. For instance, AIML techniques are helping companies understand customer behaviour more closely than ever before resulting in very precise customer segmentation and recommendation models. However the full potential of analytic models in business is far from realized (Gartner 2017, VentureBeat 2019 ). There is an interplay between various business components before a model can lead to business action. In successful frameworks good quality data and robust analytic models converge with seamless deployment, clarity of usage at each stage and strategic alignment with the end business user. This is often not the case. In this talk we highlight the difficulties that arise in the model ecosystem and share a use case where we have solved some of these problems to take our model from development to live implementation in the production environment for automated underwriting at HDFC Life.
    Hall 3: Tech Deep Dives

  • In the age of AI and ML, why do I still love an algorithm that is more than 200 years old. Why I think regression is still as relevant as ever. What I love about it and why do I think some people hate it. Why I feel that it is one of the most important areas which every new data scientist should focus on.
    Hall 3: Tech Deep Dives

  • In this talk I will cover some core concepts of recommender systems and discuss different state of the art architectures used today in industry and how these evolved from early approaches to collaborative filtering traditional machine learning algorithms for regression.
    Hall 3: Tech Deep Dives


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Grab your ticket for a unique experience of inspiration, meeting and networking for the AI & data science industry

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Note: Ticket Pricing to change at any time.

  • Regular Passes

  • Available from 29th Jul to 29th Sep 2023
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  • No Group Discount available
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