India's Biggest AI Summit

The keynote will explore the transformative impact of Digi Yatra on enhancing the digital travel experience. Digi Yatra, an initiative leveraging biometric boarding systems and paperless processing, is revolutionizing airport operations, significantly improving passenger convenience and efficiency. By integrating cutting-edge technology, Digi Yatra aims to streamline processes, reduce waiting times, and elevate the overall customer experience, setting a new standard for digital innovation in the aviation industry.

This session explores how artificial intelligence is transforming public administration and service delivery in Karnataka. It highlights AI-driven initiatives aimed at enhancing efficiency, transparency, and citizen engagement in governance. The discussion will cover real-world applications, from automated public services and predictive analytics to AI-powered decision-making tools, highlighting both successes and challenges. This session aims to showcase how AI can drive significant improvements in governance and inspire further innovation in the sector.

In the era of Artificial Intelligence and Machine Learning (AIML), service delivery is undergoing a profound transformation, redefining business operations and customer experiences. This session explores how AIML is revolutionising service delivery models across industries, driving efficiency, and enabling hyper-personalization. We will delve into the significant impact of these advancements on the digital economy, including new opportunities for growth, shifts in job markets, and the emergence of innovative business models. Attendees will gain insights into the challenges and strategies for leveraging AIML to stay competitive in an increasingly digital world.

Vulnerability in cybersecurity has undergone a paradigm shift in its appreciation. In pre-Stuxnet era – plugging vulnerability meant strength of an IT Infrastructure to withstand external intrusion causing damage to process & technology. In the post-Stuxnet era – plugging vulnerability means appetite of the IT Infrastructure to withstand both external & internal targeted attacks on people, process & technology. Earlier, the remedy was to protect endpoints while now it is to keep endpoints behind layers of physical & digital security solutions – manned & unmanned. While in the previous times, device native application(s) would alert & protect; now the layers of security exponentially increase in number, size, strength and velocity to protect the endpoints under their wings. But in both these cases, cost for security is directly proportional to the number of endpoints. In 2023, India witnessed more than 101 crore smartphones in operation - the number is projected to cross 135 crores in 2030 and 153 crores in 2040 respectively**. Adding to them are the innumerable sensor-driven IoTs that make our life more accessible & affordable. This complex eco-system requires multiple redundancy in connectivity for lag-less continuity. Cumulatively, no amount of vulnerability protection methods can ensure pre-emptive, preventive and remedial security from relentless AI-BOT driven surface-less attacks that target the zillions of exposures every IT Infrastructure generates in minutes. Hence, the need for managing exposure of an IT Infrastructure has evolved as a viable alternative over the conventional endpoint-based vulnerability (i.e., weakness) protection. Typically, Exposure Management ensures an engulfing security around every exposure of an IT Infrastructure irrespective of the endpoints and their vulnerabilities it comprises.

The exploration of the Moon and Mars has always been a significant objective in space research. One of the critical challenges in such missions is ensuring the safe and precise landing of spacecraft on these extraterrestrial bodies. This challenge is addressed by the development of autonomous landing systems powered by Artificial Intelligence (AI). Objective The primary objective of autonomous landing systems is to enable spacecraft to land safely on the Moon and Mars without human intervention. These systems must be capable of making real-time decisions during the landing process, navigating challenging terrains, and dealing with unexpected obstacles. Key Components AI Algorithms: AI plays a crucial role in the decision-making process. Machine learning algorithms, particularly deep learning, are used to train models on vast amounts of data, including satellite imagery, previous landing data, and simulations. These models help the spacecraft recognize and avoid hazards, such as craters and rocks. Sensors and Imaging Systems: High-resolution cameras, LiDAR, and radar are essential for capturing detailed images and data about the landing site. These sensors feed real-time information to the AI system, allowing it to assess the environment and adjust the landing trajectory. Navigation and Control Systems: AI-powered navigation systems guide the spacecraft to the targeted landing zone. They continuously monitor the spacecraft's position, velocity, and orientation, making necessary adjustments to ensure a precise landing. Simulation and Testing: Before an actual mission, extensive simulations are conducted to test the AI algorithms and control systems. These simulations replicate the conditions on the Moon and Mars, providing a safe environment to refine the technology. Challenges Uncertainty in Terrain: The Moon and Mars have unpredictable and varied terrains, making it challenging to design a one-size-fits-all landing system. Communication Delays: The significant distance between Earth and these celestial bodies results in communication delays, making real-time human control impractical. Power and Resource Limitations: Spacecraft have limited power and computational resources, requiring AI systems to be highly efficient. Unavailability of ample amount of data: As AI algorithms need vast amounts of data to train the models, it may put some restrictions on using AI technology. But still due to the recent success of Chandrayaan-3 mission , sufficient amounts of data have become available. Future Prospects AI-driven autonomous landing systems are expected to revolutionize space exploration by enabling more frequent and safer missions. As AI technology advances, we can anticipate more sophisticated systems capable of handling even more complex landing scenarios, paving the way for human colonization of the Moon and Mars. This synopsis highlights the role of AI in overcoming the challenges associated with landing on the Moon and Mars, emphasizing the importance of continued research and development in this field.

Artificial Intelligence is poised to revolutionize road safety in India by enhancing traffic management, reducing accidents, and improving overall transportation efficiency. Through real-time data analysis, predictive modeling, and advanced driver assistance systems, AI can optimize traffic flow, monitor road conditions, and alert drivers to potential hazards. With the integration of AI-driven smart infrastructure and autonomous technologies, India has the opportunity to significantly lower road fatalities, ensure safer journeys, and pave the way for smarter, more sustainable mobility solutions.

Robots are moving into our homes and workplaces. This means that they will need to understand language and gestures as well as pick up other non-verbal cues, just like humans, to deliver effective services. Connected intelligence through LLMs, accessed via 5G and cloud will allow robots to freely interact with humans. We will give a brief on some of our ongoing efforts in this direction – with a focus on 3D perception with semantic augmentation and LLM based planning.

The session will talk about the challenges in leveraging black box AI/ML models for fraud control and seeks to define a framework for Ethical AI for healthcare fraud control using a Human AI augmented approach.