As AI and machine learning have advanced, user interface design has continually evolved to improve the human experience of interacting with technology. Early text-based command line interfaces gave way to graphical user interfaces powered by desktop computers. More recently, responsive voice-enabled and multi-touch interfaces have expanded how users can issue commands and access information across an expanding array of devices. At the forefront of this evolution are large language models like GPT-3. Trained on immense datasets using deep learning, these massive AI systems demonstrate unprecedented ability to understand, generate and engage with human language at scale. In user experience applications, LLMs have introduced capabilities like personalized recommendations and customized content creation based on individual interests and behaviors learned over interactions. Their prowess with natural language also enabled new types of conversational interfaces through fluid, goal-oriented dialogue. While groundbreaking, LLMs interact solely through written or spoken exchanges without means for direct action in the physical world. Emerging large action models now seek to fuse linguistics comprehension with capabilities for embodied interaction and task completion. Systems trained with Constitutional AI techniques, such as Anthropic’s AgentGPT, pursue helpful, harmless and honest discussions oriented around user objectives rather than rote prompts. Through respectful clarification and context-aware flexibility, large action models facilitate collaborative problem-solving via goal-driven discussions. Comprehending multi-step plans agreed upon verbally, they integrate execution of supporting tasks like database queries, calculations or device controls. By automating routine subprocessing while maintaining an engaged conversational partnership, comprehensive end-to-end assistance materializes. Visionary future scenarios involve ubiquitous virtual assistants seamlessly integrating modalities like voice, touch, vision across interconnected platforms. Anthropic assistants may help through multisensory care facilitated by dexterous social robots. Overcoming challenges regarding grounding language to physical behaviors, developing unified foundations bridging modalities, ensuring accessibility and navigating interactions within complex real-world systems will determine realizing this future. With continued responsible progress, the roles of LLMs and embodied conversational agents may revolutionize not just how we design but fundamentally how we interact with and experience technology. _Note: Antrhopic’s Claude Instant LLM assisted in drafting and revising this post._