The Promise of Generative Artificial Intelligence of Things (GenAIoT)

The Internet of Things (IoT) has revolutionized how we interact with the world around us, but its data-driven ecosystem faces a crucial challenge: the constant need for diverse and realistic data for testing, training, and personalization. Generative AIoT (GenAIoT) emerges as a potential game-changer, harnessing the power of generative AI to create synthetic data, dynamically control devices, and personalize user experiences within the IoT landscape.
This talk delves into the vast possibilities of GenAIoT, exploring its various applications across different domains. We'll envision scenarios where:
Simulated sensor data: AI generates realistic readings for diverse environments, testing and optimizing IoT devices without relying on real-world deployments.
Real-time device adaptation: AI personalizes device behavior based on user preferences or changing contexts, creating smarter and more responsive IoT interactions.
AI-powered content creation: Generate customized user interfaces, reports, and even control instructions, tailoring the IoT experience to individual needs.
Join us on this journey to explore the exciting potential of GenAIoT, unlocking its promise while anticipating and mitigating the challenges it presents.

Harnessing Generative AI to Automate Business Processes

GenAI is a powerful tool that has the potential to automate a wide range of business processes, from tender response to customer service to market research to content creation. In this talk, I will present use cases of how organizations are using GenAI to automate their business processes. I will share my insights and lessons learned as a Data & AI architect helping organizations design and implement these solutions, and navigate their digital transformation journeys to harness AI. I will cover the following topics:
Identifying the right business processes to automate with GenAI;
Preparing high quality training data for GenAI;
Deploying GenAI models in production;
Measure success of GenAI-powered automation projects;
Techniques for optimizing GenAI for custom use cases.
I will conclude with an outlook of the future of GenAI and how I believe it will transform the way businesses operate.

Building a Robust Data Foundation for AI Success

In the age of artificial intelligence, the fuel that drives innovation is not just code, but data. But having a data lake isn't enough. This session dives deep into the critical foundations that transform raw data into the driving force behind impactful AI solutions.

Join us as we explore 5 Data Foundations for AI success:
Data Strategy: Setting a clear vision for how your data will empower AI initiatives.
Data Preparation: From collection to cleansing, mastering the art of preparing data for AI consumption.
Data Governance: Ensuring data quality, security, and compliance to build trust and avoid pitfalls.
Scalability and Infrastructure: Building a robust architecture that can handle the ever-growing volume and velocity of data.
Feedback Loops: Continuously improving your AI models by feeding them high-quality, relevant feedback data.

Learn from real-world case studies and expert insights on how to:
-Optimize your data infrastructure for seamless AI integration.
-Implement robust data governance practices for ethical and responsible AI development.
-Turn your data into valuable assets that fuel innovation and drive business outcomes.
Whether you're a seasoned AI practitioner or just starting your journey, this session will equip you with the knowledge and tools to build a solid data foundation for AI success.

Building a tool customers actually want to use

When we onboarded our first set of beta customers, we were excited to showcase how our synthetic data generation tool works, help them generate data with AI, and gather feedback before going GA. However, it wasn’t long before one customer dropped out of beta, citing that the tool was too difficult to use.

This feedback was a wake-up call for our team. We soon realized that this challenge wasn’t unique to us. In fact, Gartner Peer Insights revealed that for every single vendor, the most common dislikes were about the complexity of setting up and getting started, which validated what we were hearing from our own customers. Determined to address this, our team focused on simplifying the generation process. We introduced features like smart database sizing, automated check constraint generation, and an "AI everything" setting to enable users to get started with no manual configuration.

Through this process, we learned valuable lessons about simplifying generation setup: never assume that the user has perfect knowledge of their database, never sign an issue off as solved just because it can be handled by manual configurations, and always work closely with users to learn how they use your tool. In this talk, we’ll share what worked, what didn’t, and the insights we gained while testing our simplified setup—a crucial step in our roadmap to going GA.

Evaluating the realism of synthetic data in DevOps

Synthetic data is rapidly gaining traction, but evaluating its quality remains complex. What works for one application may not be suitable for another. Given its critical role in training machine learning models, testing applications, and ensuring data privacy, it’s essential to assess how well synthetic data mirrors real-world data while safeguarding sensitive information. DevOps and data teams must prioritize the right metrics in testing environments. In this session, we’ll provide practical insights into assessing and applying synthetic data effectively, helping attendees understand its limitations and key considerations for different use cases.

Accelerate Your Digital Career with the Global Talent Visa

The Global Talent Visa (GTV) is an opportunity for exceptional talent in digital technology to live and work abroad. The application process can be complex, but it is possible to succeed with careful preparation.

In this webinar, Maryleen & Miracle will share their unique experience of obtaining both the UK and Australia GTVs through the digital technology route. They will compare the two visas and discuss the pros and cons of each, as well as provide insights into the key requirements and considerations for applying and renewing.

Topics covered
*Australia and the UK as potential relocation spots for digital technology professionals
*Specific criteria for qualifying for the GTV in digital technology
*Steps involved in the GTV application process for digital technology professionals
*Challenges faced by digital technology professionals applying for the GTV
*Specific strategies or best practices found helpful during the GTV application process
*Advice for digital technology professionals considering applying for the GTV

[Panel] Future of AI