Many organizations strive toward data-driven, yet most of them struggle to get relevant insights to the right stakeholders in a timely manner, resulting in a reactive rather than proactive approach. Given a world of fast-paced data intake and customer expectations of real-time, drawing insights and making decisions faster are critical paths to building timely and contextual relevance with customers. Join Murli Buluswar, Head of Analytics - US Personal Bank at Citi, to learn how delivering preemptive solutions though leveraging next generation technologies increases operational efficiency. Murli will discuss how to use conversational Generative AI to increase democratization of intelligence and reduce the friction between data, insight, decision, and outcome.

As Generative AI becomes increasingly relevant in our everyday lives, many businesses are trying to figure out how this technology can be used to leverage their data. But while its power can be applied to any organization with a large amount of customer and industry data, the application of this new technology has been highly uneven across sectors.

In this session, Mr. Chi will explore how GenAI can be used to benefit society’s unsung heroes, including teachers, students, and authors. In a panel discussion with experts in publishing and education, he will examine what these sectors can do to thrive in a world dictated by data, and how to mitigate any unwarranted pitfalls.

Join us for an insightful session on the evolving landscape of Data Quality and Observability practices, transitioning from manual to augmented approaches driven by semantics and GenAI. Discover the framework enabling organisations to build the architecture for conversational data quality, leaving behind the limitations of traditional, resource-heavy methods and legacy technology. Learn why context is paramount in data quality and observability, and leave with actionable insights to propel your organisation into the future of data management.

Generative AI has the potential to transform the retail and consumer industry. In this session, we will share Google's perspective and specific use cases that can help drive value for retailers across digital commerce, marketing, store operations and supply chain. The session will also feature customer success stories and a discussion with retailers at the forefront of using generative AI.

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Now with generative AI, organizations can build voice assistant experiences and deploy them in a hybrid way, both on-device and on the cloud, to support low-latency and low-connectivity scenarios. Learn how automotive customers are using this technology to power the next generation of their in-car voice assistants.

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Our research estimates that gen AI could add over $4 trillion of value annually — join McKinsey to hear the latest research on where the highest value use cases and opportunities for gen AI are across your organization. Hear how McKinsey and ING collaborated to build a GenAI-enabled customer service agent, and see examples of how industry-leading companies are productionalizing use cases to increase revenues and reduce costs today. By attending this session, your contact information may be shared with the sponsor for relevant follow up for this event only.

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Today's customers expect more from digital experiences. Learn how to transform your current website into a hub for customer engagement and AI-powered experiences. With generative AI, there are significant opportunities for enhancing the discoverability of pages and content with website search or conversations, translation and localization of text or images, and incorporating dynamic recommendations tailored to user experiences. Discover how to unlock AI's potential for your website, elevating customer experiences and driving business success.

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Generative AI is a huge opportunity, but the rubber meets the road when going from ideation to testing and deploying. Assurance has leveraged the existing Data Mesh approach to make the deployment of Generative AI solutions both scalable and safe. This allowed the team to focus on this new technology solving Assurance’s business needs while relying on tried and tested data principles. Killian Farrell, Principal Data Scientist at Assurance, will discuss testing and deployment strategies as well as the integration with an existing data lake. When turning a hype into valuable data products, it is clear that a good foundation in data excellence and testing flexibility is key to achieving success.

The core of journalism was trust. For centuries, the cost of a printing press or broadcast license limited who could create news, but the rise of the Internet has turned everyone into a publisher. From fake news to hallucinations, modern journalism faces an existential threat, not only from a flood of unreliable sources but also from motivated actors bent on applying the latest technologies to inflame political polarization.

Is there a way to save the 4th Estate on which democratic society relies? In this talk, DM Radio's Eric Kavanagh suggests that the foundation of every story must be data with a proven, verifiable lineage. The carefully curated fusion of real-world transactional data and generative AI will radically transform the news industry, triggering a much-needed Renaissance in world-class journalism—but only if we use embeddings and open-source code to ensure accountability and transparency.

Generative AI is driving the next industrial revolution and businesses are racing to use it to improve customer experiences, healthcare, and operations. But to succeed, they need a plan. In this session, we'll highlight practical use cases and challenges of scaling AI in 2024. We'll also show you how NVIDIA DGX Cloud on Google Cloud supports the entire AI app lifecycle, from development to deployment. You'll learn how to speed up the return on investment of AI.

By attending this session, your contact information may be shared with the sponsor for relevant follow up for this event only.

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The concept of time and money spent on proof of concept (POC) has dramatically changed with generative AI. Since POCs can now be conducted immediately and at a low cost due to generative AI, businessmen and companies wanting to utilize generative AI in their operations should get started right away.

GenAI can look deceptively easy when it comes to showing a cool demo, but can prove incredibly hard to productionalize. This session will cover the challenges behind industrializing GenAI applications in the enterprise, and the approaches engineers are taking to meet these challenges. Attendees will get to take a look under the hood to see how Data Engineering and Integration techniques can help us go from simple demos to production grade applications with consistently high quality results.  

We will explore how Retrieval Augmented Generation (RAG) workflows go from naive to advanced. Techniques discussed will cover a typical GenAI application flow with topics including multiple and hybrid models, refined data processing, data security, getting transparency in results, combining structured and unstructured data, and putting it all together to get high performance and cost effective outcomes. Attendees will leave the session with a framework to understand proposed solutions from their teams and ask the right questions to test if a solution can become industrial-grade.

In a classic cart before the horse scenario, many companies have jumped at leveraging Generative AI and other AI technologies. However, most of those same companies haven't completed the core work of building a reliable & secure foundation that provides data accessibility, analytics speed, and ensures data quality. The resulting risk for leaders is overinvestment in AI programs that may not have accurate & secure data access, further exposing the business to harm. It is a case of slowing down to speed up - ensure the foundation is solid before you build the house. In this talk by Starburst CEO Justin Borgman, and Head of Partner Solutions Architecture, Data & Analytics - AI/ML, Subodh Kumar from AWS, you'll learn about the essential data foundations for AI success. The foundation, the plumbing, and the framing that will set businesses up for AI success.

If everything goes the way that the experts say it will, Generative AI will eventually be a core part of nearly every piece of technology we use. But before that happens, some organizations will likely make their current products worse, as they try to integrate GenAI functionality in their existing services. Join Benn Stancil, Field CTO at ThoughtSpot, to strategize which Generative AI dreams are worth chasing, what foundations you need to build and leverage AI, and how to take advantage of these AI developments while avoiding major disasters. 

This session will explore the transformative impact of Generative AI on data strategy. It will highlight how GenAI, based on a lakehouse platform, empowers organizations through people, process, and platform. The talk will also delve into how by grounding your strategy with governance in mind you can increase innovation, competitiveness, and productivity, by enabling data-driven decision-making.

We are in a Great Acceleration—a singularity, not in the capital-S-Kurzwellian sense of robots rising up, but in the one Foucault described: A period of time where change is so widespread, and so fundamental, that one cannot properly discern what the other side of that change will be like.

In this talk, Data Universe chair Alistair Croll charts the course from traditional software to generative AI—software that makes stuff up. He'll discuss its rapid adoption, and some unintended and surprising consequences everyone should understand, exploring inexorable swings between centralized and decentralized architectures.

Implementing generative AI applications requires large amounts of computation that can seamlessly scale to train, fine-tune, and serve the models. NVIDIA and Google Cloud have partnered to offer a range of GPU options to address this challenge. Using NVIDIA GPUs with Google Kubernetes Engine removes the heavy lifting needed to set up AI deployments, automate orchestration, manage large training clusters, and serve low-latency inference. Join us to see what ElevenLabs has built using NVIDIA GPUs with GKE. Please note: seating is limited and on a first-come, first served basis; standing areas are available

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Implementing generative AI applications with large language models (LLMs), and diffusion models requires large amounts of computation that can seamlessly scale to train, fine-tune, and serve the models. Google Cloud TPUs. Cohere is leveraging the compute-heavy Cloud TPU v4 and v5e to train sophisticated gen AI models that meet the heightened needs of their enterprise users. Check out how Cohere and Cloud TPUs are delivering enterprise-tailored large language models (LLMs) that can help increase business productivity by automating time-consuming and monotonous workflows. Please note: seating is limited and on a first-come, first served basis; standing areas are available

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