The Rise of AI: What it means for today and tomorrow

Tuesday, September 19, 2023 4:00 pm – 5:30 pm

Location: Impact Stage

Join us at the Impact Stage for an engaging session moderated by Linda Asplund, Vice President – Head of Enterprise Transformation SweFi / Global Head Corporate Experience at Capgemini Invent, and Tony Poulos, Industry Insights Advisor at TM Forum.

In this session, we will have an exclusive interview with Harmeen Mehta, CDIO of BT Group, as we explore how BT Group approaches data and AI as a platform for growth. Gain insights into the path to simplification and setting the foundations for unlocking the power of data and AI. Discover the building blocks, including Graph, CDMC, ML Ops, and responsible tech principles, that enable BT Group to unleash new use cases and create value. Explore the responsible implementation of generative AI and the vision of combining human and artificial intelligence for growth.

Next, we will delve into the question of whether AI is the answer and aim to make sense of the hype surrounding it. Outline the impact of generative AI on the telecom industry and explore the value and strategies for CSPs (Communication Service Providers). Understand how CSPs can make wise investments to leverage generative AI for future growth. Additionally, we will delve into the governance of generative AI, addressing the balance between innovation and ownership. Discuss the current approaches to regulating generative AI, managing intellectual property issues, and ensuring ethical considerations to maintain trust in the generative AI era.

Concluding the session, we will have a panel discussion on generative AI as the game changer. Explore the risks and rewards associated with generative AI and navigate the disruptions that it may bring. Assess the potential applications of generative AI and explore the art of the possible. Our esteemed panelists include Navneet Sahani, Director of Global Telecom Industry Solutions, Cloud GTM Strategy & Solutions at Google; Rick Lievano, CTO of WW Telecommunications at Microsoft; and Jaime Tatis, Vice President – Data Strategy & Enablement at TELUS.

Join us at the Impact Stage for this thought-provoking session that explores the potential of data, AI, and generative AI in driving growth and transforming the telecom industry. Add this session to your calendar now and be part of the conversation that shapes the future of AI-powered growth and innovation.

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Aihub Team

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AI and Virtual Assistants: AI-driven virtual assistants, chatbots, and voice assistants for personalized user interactions.

AI and Business Process Automation: AI-powered automation of repetitive tasks and decision-making in business processes.

AI and Social Media: AI algorithms for content recommendation, sentiment analysis, and social network analysis.

AI for Environmental Monitoring: AI applications in monitoring and protecting the environment, including wildlife tracking and climate modeling.

AI in Cybersecurity: AI systems for threat detection, anomaly detection, and intelligent security analysis.

AI in Gaming: The use of AI techniques in game development, character behavior, and procedural content generation.

AI in Autonomous Vehicles: AI technologies powering self-driving cars and intelligent transportation systems.

AI Ethics: Ethical considerations and guidelines for the responsible development and use of AI systems.

AI in Education: AI-based systems for personalized learning, adaptive assessments, and intelligent tutoring.

AI in Finance: The use of AI algorithms for fraud detection, risk assessment, trading, and portfolio management in the financial sector.

AI in Healthcare: Applications of AI in medical diagnosis, drug discovery, patient monitoring, and personalized medicine.

Robotics: The integration of AI and robotics, enabling machines to perform physical tasks autonomously.

Explainable AI: Techniques and methods for making AI systems more transparent and interpretable

Reinforcement Learning: AI agents that learn through trial and error by interacting with an environment

Computer Vision: AI systems capable of interpreting and understanding visual data.

Natural Language Processing: AI techniques for understanding and processing human language.

Deep Learning: The advancement of deep neural networks and their applications in various domains.

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