IDEO, Jenna Fizel, Danny DeRuntz // Invisible Machines // S2E10
Aug 31, 2023
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Jenna Fizel and Danny DeRuntz from IDEO join the hosts to discuss the creation of Lotbot, digital twins, machines communicating for safety, composability in technical architectures, Google's new tool and updates, the impact of technology on jobs, the value of anthropomorphism, prompt engineering and coding similarities, language standpoint and providing context, singularity and chatbot moderation challenges, and discoverability challenges in UI design.
Lottbot started as a small project to solve parking issues at IDEO but gained popularity and evolved over time, with the creator content with its original purpose.
The interaction between Lottbot and the camera utilized natural language instead of traditional APIs, enabling a more inclusive and transparent system.
The concept of digital twins presents transformative possibilities for expanding Lottbot to encompass various functionalities beyond parking management and exploring the evolving relationship between digital and physical experiences.
Deep dives
The Origin of Lottbot and Its Usage
The podcast episode discusses the origin and usage of Lottbot, a chatbot that helps people find parking spaces in a tight parking lot. Lottbot was developed at IDEO and initially used computer vision on a camera to detect available spots. The chatbot was integrated into Slack and utilized Google's dialogue flow to interact with users. It started as a small project to solve parking issues within IDEO but gained popularity and evolved over time. Despite the potential for expansion and adding more capabilities, the creator, Danny, is content with Lottbot focusing on its original purpose and does not have ambitions for it to become a comprehensive system.
The Incorporation of Natural Language and the Anthropomorphization of Lottbot
The podcast delves into the usage of natural language in the interaction between Lottbot and the camera. Rather than using traditional APIs, the camera and Lottbot communicated with each other in natural language, enabling humans to be part of the conversation. This approach facilitated a more inclusive and transparent system. Additionally, the podcast explores the concept of anthropomorphism in Lottbot's personality and behavior. It highlights the challenges of defining boundaries for a bot with human-like traits and discusses the importance of intentional design to ensure appropriate and respectful communication.
The Potential of Digital Twins and Reflections on the Future
The podcast touches upon the concept of digital twins and their potential to augment physical spaces with digital information. Digital twins are seen as representations of entities in the digital realm, enabling interaction and providing enriched experiences. The discussion revolves around the transformative possibilities of expanding the scope of Lottbot to become a digital twin of IDEO, encompassing various functionalities beyond parking management. The conversation also explores the broader context of the evolving relationship between digital and physical experiences, contemplating the implications of these advances and the potential shifts in how we perceive and interact with technology.
The Potential of Composability and Natural Language in Interacting with Machines
The podcast explores the potential of composability and natural language in interacting with machines. Composability allows for the creation of flexible and modular architectures that can enable seamless and frictionless deployment of various applications. This can eliminate the need for complex provisioning processes and increase scalability. Natural language interfaces can further enhance composable architectures by enabling users to interact with machines using natural language, eliminating the need for technical involvement and allowing for easier and more accessible deployment. The combination of composability and natural language can revolutionize the way we interact with machines and facilitate a more intuitive and user-friendly experience.
The Role of Context in Discovery and Predictive Interfaces
The podcast discusses the importance of context in discovery and predictive interfaces. By leveraging a digital twin model and providing relevant context to AI systems, it becomes possible to anticipate user needs and offer timely suggestions. This just-in-time interface can enhance the user experience by proactively offering relevant information or functionality before users even realize they need it. Predictive interfaces that can understand user intents and predict their next actions can offer a powerful and personalized experience. This approach to discovery can help users discover new features, capabilities, or services, while ensuring that information is presented at the right time for maximum effectiveness.
Robb and Josh welcome Jenna Fizel (Senior Director, Emerging Technology) and Danny DeRuntz (Executive Design Director) of IDEO for a practical exploration of building conversational experiences focusing on their creation, Lotbot. The conversation branches out into the many facets of digital twins, the languages machines might use to communicate with each other, and the blurring edges between bots and brands.
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