Women in AI experts will provide a unique perspective on why it is important to start with the data for algorithms to be ethical, be it for new transformations or for enterprise transitions towards the Generative AI era. Data governance along with regulatory audits are not sufficient anymore, and the multifaceted responsibilities towards an accessible and inclusive future for all humans requires a comprehensive data strategy. The panelists will share industry perspectives from finance and sustainability that emphasize privacy, security, synthetic data, and maturity scores to scale ethical models.

There's no problem more existentially fundamental than climate collapse. Nations and businesses worldwide are scrambling to adapt, anticipate, and mitigate while dramatically reducing the impact they have on the planet. In this session, data and AI expert Navdeep Martin looks at how three organizations were already tackling these monumental changes—and how generative AI is changing their transformations.

Women in AI experts will discuss why data matters for inclusion to be effective in the models being trained. Understanding not only the outputs for individuals, rather how outcomes impact broader communities is a key consideration. Continuously iterating and testing the models is critical to address gender inequities, and the panelists will explore industry use cases from the financial services sector, as well as disinformation in news and media.

While everyone's talking about AI, far fewer have deployed it successfully or turned technology into business outcomes. This panel changes that, bringing together Generative AI experts for a deep dive into the practical application of generative AI. From building new customer offerings to refreshing internal processes, the panellists will reflect on the importance of data quality, data security, the responsible use of data as well as change management when it comes to embedding generative AI into the business strategy.

The emergence of pre-trained deep learning models – e.g., Foundation and generative AI models – such as GPT-4, represents a paradigm shift in the utilization of AI. This keynote, rooted in the insights from "AI iQ™ for a Human-Focused Future," explores the profound differences between implementing these state-of-the-art pre-trained models and traditional machine learning/AI approaches. Find out why the ‘xOps’ paradigm is a fallacy, why the unique technical and operational challenges necessitate sophisticated data and model observability and the imperative for advanced and specialized computational infrastructure to support the intensive demands of these models.

We delve into the strategic considerations surrounding data governance, ethical AI use, and the integration of AI into business processes, underscoring the need for a comprehensive framework that encompasses technological implementation and alignment with organizational goals and values. The discussion extends to the critical role of having a single leader for AI – the Chief AI Officer.

Through a blend of strategic insights and practical examples, this presentation offers a roadmap for businesses looking to navigate the complexities of integrating these models. It provides actionable strategies for building the infrastructure, culture, and processes necessary to harness the transformative potential of these technologies, driving innovation, efficiency, and growth in the digital era. Join us to explore how your organization can transition from traditional AI methodologies to leveraging the power of generative models and observability ensuring a competitive edge in the rapidly evolving corporate landscape. 

Following the explosion of ChatGPT onto the market in late 2022, LexisNexis Legal & Professional quickly saw the massive opportunity for large language models (LLMs) to transform how its customers do legal work. Within weeks, the company pivoted to begin innovating, delivering, and now expanding generative AI solutions for its customers. Across legal and tech industries, the company was recognized as a generative AI leader.

LexisNexis EVP & CTO Jeff Reihl will detail how the company rapidly innovated, delivered, and expanded generative AI solutions. Reihl will share insights into how the company considers its customers’ key challenges and its multi-model approach, prioritizing the best LLM to solve each customer use case. He’ll also share how the company integrates its data assets with LLM technology to improve model output and how the company’s Retrieval Augmented Generation (RAG) platform creates flexibility for the company to adopt new LLM technologies as they change. 

Attendees will learn strategies for deploying generative AI in their organizations to impact products, customers, and internal tools. Reihl will share how attendees should think about deploying generative AI in their organization, how to hire for it, and how to organize teams around it.

The industry has witnessed some tectonic changes over the last few years: on prem to cloud to multi-cloud, BI to AI to GenAI, and data warehouses to data lakes to data lakehouses, to name a few. This constant evolution coupled with the ever-increasing demands of the business makes platform thinking crucial in order to ensure a future-proof infrastructure. As companies race to advance their AI strategies, Dell has seen a gravitational pull towards a modern data architecture that can create high quality data to feed AI and generate high quality outcomes. Join this session to learn about how the Dell Data Lakehouse, powered by Starburst, is the modern paradigm for this new era. You’ll learn about the investments Dell is making in data, analytics, and AI, why Dell and Starburst partnered up on this solution, and how it enables a tremendously powerful yet open and flexible data architecture.

Generative AI has triggered a new era of innovation and collaboration: the Age of Artificial Generative Innovation. AI systems now turn all types of content, from written materials to scientific data, into Copilots that help creators and innovators. These systems use specialized knowledge to break through old limits, sparking fresh ideas and partnering directly with engineers, scientists, and creators. From creating new drugs to inventing new materials, they speed up the innovation cycle. Systems of AGI fundamentally transform how we interact with and communicate knowledge, and how we apply this knowledge. In this talk I will illustrate how AI streamlines and accelerates innovation, reshaping how we work together with machines to invent the future.

In this executive debate, leading industry analyst Mike Ferguson welcomes leaders from premier software companies to discuss key topics in data management and analytics. Panelists will debate the impact of Generative AI, the implications of key industry trends, how best to deal with real-world customer challenges, how to build a modern data and analytics (D&A) architecture, data and AI governance and sharing, and on-the-horizon issues that companies should be planning for today.

Attendees will learn best practices for data and analytics implementation in a modern data-driven enterprise from seasoned executives and experienced analysts in a packed, unscripted, candid discussion.

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 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.

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.