A Chief Privacy Officer, a Computer Scientist, and a Lawyer walk into a bar … and the bartender is a Chief Data Officer. 

Artificial intelligence is rapidly transforming our world, and with it comes the risk of unintended consequences. AI can infringe on privacy, create and perpetuate bias and discrimination, negatively impact economic opportunities, and harm customers. AI can spread disinformation and perpetuate deepfakes, affecting democratic processes and participation. Companies and institutions face reputational, cultural, economic, legal, and regulatory risks if they don’t identify, address, and govern AI’s potential harm to individuals and society throughout the AI lifecycle. 

This panel discussion among data experts will explore the importance of creating and maintaining AI systems that are human-centric, accountable, transparent, explainable, and privacy enhanced.

In this session, Jordan Morrow will explore the impact of integrating data and AI strategies with business goals, highlighting their importance in driving organizational success. He will emphasize the significance of imbuing data professionals with business acumen and the need for fostering data and AI literacy across the organization. Jordan will focus on strategies for data professionals that not only enhance their understanding business combined with the application of data and AI but also effectively generate real business value.

Large Language Models like the GPT, Gemini, Gemma and Llama series are rapidly transforming the world in general and the field of data science in particular. This talk introduces deep-learning transformer architectures including LLMs. Critically, it also demonstrates the breadth of capabilities state-of-the-art LLMs can deliver, including for dramatically revolutionizing the development of machine learning models and commercially successful AI products. This talk provides an overview of the full lifecycle of LLM development, from training to production deployment, with an emphasis on leveraging the open-source Python libraries like Hugging Face Transformers and PyTorch Lightning.

Operating data lakes over object storage poses challenges: testing ETL changes, staging pipelines, ensuring best practices, debugging, and tracking data usage for ML reproducibility. Enter lakeFS—an open-source data version control tool transforming object storage into Git-like repositories. Learn how lakeFS enables unified workflows for code and data, providing benefits like faster development and error recovery. Join us to explore lakeFS and harness the power of data as code for your team's success.

As the field of data analytics continues to progress and expand, the role of semantic layers in harnessing the power of AI is becoming increasingly crucial. The incorporation of context and constraint is essential to optimizing the potential of Language Model Models (LLMs), which requires a more structured and specialized approach. While traditional methods have made strides in providing some context through prompt engineering and knowledge graphs, semantic layers offer unparalleled clarity and efficiency in bridging the gap for LLMs. To further unfold the narrative on semantic layers and their transformative impact on AI-enabled analytics, we invite you to a thought-provoking session with Artyom Keydunov, Cube's CEO & Co-founder.

Join Jamie Underwood and Andy Hannah for a transformative deep dive into the Responsible Data Revolution. In this session, they'll explore the crucial intersection of innovation and advanced analytics, delving into the legal aspects surrounding it. With Jamie's expertise in navigating the intricacies of intellectual property and Andy's deep entrepreneurial and analytical experience, we'll uncover the ethical and legal considerations that arise in the era of big data and AI. 

From privacy concerns to intellectual property rights, they'll discuss the evolving landscape of data governance and responsible innovation. Gain insights into strategies for leveraging data ethically and responsibly while maximizing its potential for transformative innovation. This session promises to equip you with the knowledge and tools to navigate the complex terrain of the data revolution responsibly.

The Federal Government's approach to AI Policy, Governance, and Security is evolving to address this dynamic landscape of artificial intelligence and the explosion of Large Language Models. The goal is to develop a framework with the aim of reducing risk to people and the planet in the development, procurement and use of AI and the comprehensive strategies employed to formulate and implement policies ensuring responsible AI use. Emphasizing robust governance frameworks, organizations navigate ethical considerations, privacy concerns, and potential biases. Security protocols are paramount, safeguarding against cyber threats and ensuring the integrity of AI systems. Leveraging this multifaceted approach will help to foster innovation while prioritizing transparency, accountability, and the public interest. The Federal Government's commitment to shaping a secure and ethical AI landscape underscores its pivotal role in technological evolution.

In this session, analytics expert and renowned AI author David Boyle will take the audience on a fascinating journey into applied AI. We'll explore how language models like ChatGPT are revolutionizing analytics, sharing dozens of practical examples of how AI is transforming data interpretation, decision-making, and communication.

We'll explore using these tools in planning analytics to generate hypotheses and analytical strategies. David will demonstrate GPT-4's Code Interpreter executing complex data tasks like cleaning and analysis, allowing attendees to see firsthand see the iterative nature of working with AI: How it can write code, perform analysis, and refine outputs based on feedback.

Finally, we'll look at bringing insights to life. AI can turn complex findings into compelling stories for decision-makers. It can generate visualizations, interpret results, and translate technical terms into actionable business insights. This helps close the gap between data teams and leadership by serving as a mediator.

This session will be far more than a simple demonstration of AI's capabilities, but instead offer a roadmap for harnessing AI's power to revolutionize your work. Join David to consider the broader implications of AI in decision-making and how to integrate these tools into your workflows.

In this session, Chad Sanderson, CEO of Gable.ai and author of the upcoming O’Reilly book: "Data Contracts," tackles the necessity of modern data management in an age of hyper iteration, experimentation, and AI. He will explore why traditional data management practices fail and how the cloud has fundamentally changed data development. The talk will cover a modern application of data management best practices, including data change detection, data contracts, observability, and CI/CD tests, and outline the roles of data producers and consumers. Attendees will leave with a clear understanding of modern data management's components and how to leverage them for better data handling and decision-making.

There is a mad rush these days to embrace the power of AI inside every enterprise. But, through a decade of research, Jack Phillips' research has shown that a firm's data and analytics maturity hold the answer as to how ready a firm is to leverage AI. There is no "free lunch" when it comes to AI adoption -- the foundational elements of high quality data, a data-driven culture, and understanding the right business problems must all be in place

Mr. Phillips will walk through IIA's globally accepted methodology for measuring data and analytics maturity, and share industry and company benchmarks to allow you to estimate where your company stands today. Most importantly, Mr. Phillips will open the playbook around what the highest-performing analytical competitors are doing differently than the rest. 

Tech moves fast; the law, not so much. How does a slowly-evolving legal industry govern ever-evolving technology? How do companies (and inventors) protect their AI-related data and intellectual property while not infringing the rights of others? Which type of IP is best suited for AI products? Copyrights? Patents? Trade secrets?

Join Jamie Underwood, a seasoned trial lawyer with over two decades of experience resolving IP issues in high-stakes cases, as she provides you with an overview of the benefits, drawbacks, and open questions to consider when making IP-related decisions about AI and the data supporting it.

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.

Data is the linchpin of competitive advantage. This session takes you on a deep dive into the revolutionary best practices of enterprise AI data pipelines. We'll unpack the complexities of data integration from multiple silos, orchestrating data to GPUs, and building fast and efficient infrastructure for AI. We'll explore innovative strategies for data governance, real-time processing, and seamless orchestration across disparate systems.

Learn how industry leaders are leveraging these practices to drive decision-making, enhance customer experiences, and catalyze digital transformation. Join us to empower your enterprise with the architecture that will lead tomorrow's Enterprise AI landscape, and walk away with a practical blueprint for constructing resilient, scalable, and efficient Enterprise AI architectures.

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 explores the technological advancements of analytics, data science, machine learning, AI, and quantum computing. Beginning with an overview of the historical development and current state of these technologies. LexisNexis' Flavio Villanustre will explore how analytics has transformed industries; how data science extracts valuable insights, how machine learning has moved from simple rule-based systems to today's deep learning models; and how quantum computing promises to solve previously intractable problems at speeds unattainable by classical computers.

Attendees will learn about the benefits and associated risks of each technology: Increases in efficiency, productivity, and innovation juxtaposed against vulnerabilities in privacy, security, bias, and wider societal concerns such as unemployment. These competing issues underscore the need for responsible, ethical research and deployment of such tools.

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.

Join data nerd and business strategist David Boyle to hear how and where artificial intelligence is driving business data-driven transformation.

Combining more than two decades of experience pioneering data-driven change at global brands like EMI Music, HarperCollins, BBC, MasterClass and Harrods with a crazy 18 months of experience as a leading author and consultant on the role of language models in many of the world’s leading companies, David will share his perspective on the role of AI relative to other forms of data / insight / analytics in business transformation.

Expect fascinating case studies highlighting how AI has redefined business strategies and unlocked new growth. Discover strategies for capitalizing on AI to overcome industry challenges, open new market opportunities, and transform culture and commerce. And hear about a failure or two along the way. 

You'll leave with a new outlook on AI's potential, ready to embrace AI as the driving force for your data strategy.

AI has been with us for years in everyday technologies such as mapping, facial recognition, and cancer detection. But ChatGPT and its cousins made AI "real" to the masses by letting us interact with the AI directly, rather than having it work its magic behind the scenes of an app. Where might this strong AI tailwind take us? Will it push us to AI sentience or will we, as AI’s engineers, be hoisted with our own petard—or will it be a little of both? In this keynote, startup and AI pioneer Jana Eggers will share her observations and advice from delivering large-scale AI-enabled systems from more than 30 years across research, supply chain optimization, search engines, travel, and generalized decision support.

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.