Convo AI World

What does it take to translate a conversation as it happens? In this special montage episode of the Convo AI World Podcast, we bring together selected conversations with Palabra's Artem Kukharenko, Soniox's Klemen Simonic, Rime's Lily Clifford, Akool's Jeff Lu, and Professor Mérouane Debbah to explore the challenges of real-time translation. The episode begins with the human promise of speaking across language barriers, then examines the decisions a translation system must make before a sentence is complete. Klemen explains the tension between responding quickly and waiting for enough information to preserve meaning. Palabra's perspective adds the reality of mixed-language conversations, where people can switch between languages without announcing the switch. Lily and Mérouane broaden the discussion to dialects, regional data, and cultural context. Their insights show why supporting a language involves more than adding its name to a list. Jeff takes the conversation beyond words, exploring how translated video can preserve a speaker's voice and facial expression. From everyday multilingual interactions to enterprise requirements around privacy and customization, the masterclass connects technical choices to the experience of the people using them. It closes with a vision of translation becoming a seamless part of conversation and the work still needed to get there. Check out video episodes and subscribe to the Convo AI Newsletter at podcast.convoai.world

In this episode of the Convo AI World Podcast, Hermes Frangoudis speaks with Neal Patel, co-founder of ScaleDown, about choosing models for the specific jobs inside an AI application. Neal explains how his work forecasting data center demand led him to focus on token efficiency. At ScaleDown, that means building small language models for tasks such as classification, extraction, and summarization. He describes how the team combines existing model components with task-specific neural heads, and where these specialists can work alongside a larger model that handles planning and conversation. For voice AI builders, the discussion covers routing, parallel subagents, conversation history, and post-call analysis. Neal explains the difference between query-aware compression and a generic summary, and why preserving the information needed for an answer matters more than simply shrinking a prompt. He also explores using classifiers for evaluation, where consistency can matter as much as speed. The conversation closes with ScaleDown's integration tools and roadmap, plus Neal's view of how model selection could become more automated. Throughout, he makes a useful distinction: specialized models may reduce variability on a defined task, but they are not fully deterministic. Check out video episodes and subscribe to the Convo AI Newsletter at podcast.convoai.world

In this episode of the Convo AI World Podcast, Hermes Frangoudis sits down with Dustin Allen, co-founder of Trinitite, to explore why evaluating an agent is only part of making it reliable in production. Dustin traces Trinitite's origins to a productivity app for accountants and finance teams, where a damaged spreadsheet exposed the need to replay actions, restore data, and understand what went wrong. He explains why his team now treats AI delivery, governance, and security as connected parts of the same system, and how Trinitite uses deterministic inference to make its own assessments more repeatable and failures easier to investigate. The conversation gets practical about voice AI: where to place controls in a cascading pipeline, how asynchronous monitoring can preserve conversational flow, and why sensitive tool calls may need checks before an action proceeds. Dustin also discusses multimodal systems, developer tools, and the challenge of observing agents running locally on a device. For teams building voice agents or enterprise AI, the episode offers a grounded discussion of continuous monitoring, remediation, and the limits of guardrails, with an emphasis on learning from failures and keeping people involved in deciding which risks matter most. Check out video episodes and subscribe to the Convo AI Newsletter at podcast.convoai.world

What does it take to give AI a face, and build a digital character people actually want to talk to? In this special montage episode of the Convo AI World Podcast, we bring together experts from Trulience, Akool, and AKA Virtual to unpack the technology, design choices, and product thinking behind the rapidly evolving world of AI avatars and digital humans. Jeff Lu of Akool explains why his team has focused on photorealistic people, real-time video generation, and running increasingly capable AI experiences closer to the edge. Jia Shen of AKA Virtual makes the case for a very different approach: characters do not always need to imitate humans. He explains why caricature, animation, and clearly defined character roles can sometimes create more believable experiences. Richard Bowdler of Trulience explores another part of the stack: giving conversational AI a face and body while keeping the underlying intelligence modular. That means combining avatars with LLMs, speech technologies, knowledge, and other components while allowing developers to choose the "brain" behind the character. Whether you're building conversational AI agents, virtual assistants, interactive entertainment, customer experiences, or the next generation of AI characters, this masterclass offers a practical look at what it takes to turn an AI model into a digital presence people can actually interact with. Check out video episodes and subscribe to the Convo AI Newsletter at podcast.convoai.world

What does it take to evolve from live voice experiences to AI-powered game hosts? In this episode of the Convo AI World Podcast, Agora's John Moore sits down with Geremie Camara, co-founder of Live Play Mobile, to explore how conversational AI is reshaping live gaming and interactive entertainment. With more than 100,000 hours of live-hosted gameplay, Live Play Mobile has spent years learning what keeps players engaged. Now, the team is applying those lessons to AI avatars that can entertain, personalize experiences, and scale globally alongside human hosts. Geremie shares why real-time infrastructure matters, how AI and human hosts complement each other, what it takes to make AI feel natural, and the engineering challenges behind voice quality, latency, memory, and production-ready conversational AI. Whether you're building voice AI, AI agents, gaming experiences, or real-time applications, this conversation offers practical insights into where conversational AI is heading, and what it takes to build engaging AI experiences at scale. Check out video episodes and subscribe to the Convo AI Newsletter at podcast.convoai.world