Scott Stephenson, CEO of Deepgram, discusses the evolution and business applications of Voice AI, exploring its value in applications and common use cases. He also delves into the process of adding Voice AI to existing applications and collecting user feedback for voice-centric interactions.
Voice AI is evolving rapidly with improved accuracy and human-like interactions.
Companies integrating Voice AI must consider deployment options for flexibility and customization.
Automated observability tools are shaping the future of real-time monitoring in Voice AI systems.
Deep dives
Overview of Panoptica Cloud Security Solution
Panoptica, Cisco's cloud application security solution, offers end-to-end lifecycle protection for cloud-native application environments. Organizations can safeguard their APIs, serverless functions, containers, and Kubernetes environments with comprehensive cloud security, compliance, and monitoring. It provides deep visibility, contextual risk assessments, and actionable remediation insights. Powered by graph-based technology, Panoptica's AttackPath engine prioritizes dynamic remediation for vulnerable attack vectors, aiding security teams in quick risk identification and mitigation.
Exploration of Voice AI with Scott Stevenson
Scott Stevenson, CEO of DeepGram, discusses his background transitioning from particle physics to building cutting-edge audio AI at DeepGram. The company's work in audio analysis and waveform processing has evolved to focus on making audio waveforms searchable and discovering insights in aggregated large bodies of data like podcasts and conversations.
Evolution of Voice AI Maturity
Voice AI is experiencing a shift towards real-time applications and improved human-like interactions. The technology is advancing rapidly, with enhancements in speech-to-text accuracy, low latency text-to-speech responses, and cognitive abilities for more authentic human interactions. The upcoming 2.0 version of voice AI aims to incorporate deep context passing between models for personalized and contextual conversational experiences.
Deployment and Business Considerations for Voice AI
Companies looking to deploy voice AI solutions face considerations such as cost, quality, and latency trade-offs. DeepGram offers flexibility with multiple deployment options, including on-premise, private cloud, or hosted solutions. Businesses can start with demos and gradually customize models to match user needs and use cases, focusing on high-priority interactions and practical applications.
User Interaction and Observability in Voice AI
User interaction feedback and observability in voice AI systems are key for evaluating performance and enhancing user experience. While initial feedback methods involve manual observation and user testing, the industry is evolving towards automated observability tools for real-time monitoring and feedback on AI agent performance, signaling a growing maturity in the voice AI lifecycle.
Topic 1 - Welcome to the show. Before we jump into Deepgram and Voice AI, let’s talk a little bit about your background and then what led you to start the company.
Topic 2 - Let’s start by stepping back and looking at the bigger picture. Many of us have interacted with voice technologies, from Siri to Alexa to various call-center “agents”. From a maturity perspective, where are we in terms of voice-centric interactions with computing systems?
Topic 3 - When businesses think about including computer-aided voice-centric interactions to their applications, what’s the typical thought process for where it makes sense to the business, how it represents their brand, etc.?
Topic 4 - How does Deepgram bring Voice AI to applications? What do developers have to think about when adding Voice AI to an existing application, or to think about building a voice-centric application from the start?
Topic 5 - What are some of the most common use-cases when Voice AI adds new value to the application? What areas are starting to push the edges of possible?
Topic 6 - How do companies usually go about collecting user-feedback about the voice-centric interactions?
Topic 7 - If you look forward a year or two, where do you see Voice AI types of technologies evolving?