Raven v2 and the Race to Smarter Voice Agents with Matt Henderson (Deep Learning with PolyAI, Episode 81)
About this episode
In this episode, your host Nikola Mrkšić sits down with Matt Henderson, VP of Research at PolyAI, to unpack the state of large language models, their quirks, and what really matters when building smarter voice agents for customer service.
Join us for a discussion on:
- Why GPT-5 may feel more incremental than game-changing
- Why reasoning models can fail at surprisingly simple tasks
- How PolyAI's Raven outperforms generalist LLMs in latency-sensitive, real-world CX use cases
- The balance between speed, accuracy, and reasoning for live customer interactions
- What open-source models, quantization, and fine-tuning mean for enterprise AI strategies
👉 Learn more about Raven and conversational AI here: https://poly.ai/blog/polyai-raven-v2-large-language-model/
Get every episode summarized
Each time Deep Learning with PolyAI publishes, we email you a written briefing from the transcript — the topics, who appeared, and any specific claims, with the ad reads skipped.
Email me new episodesFree for 3 shows. No card needed.
Hosts & guests
No transcript yet
This episode has not been transcribed. Request it and it moves to the front of the queue.
More episodes
More from Deep Learning with PolyAI
What happens if your AI agents get 1% better every day?
Deep Learning with PolyAI
Who's coordinating your army of AI agents?
Deep Learning with PolyAI
Why should CX leaders care about MCP?
Deep Learning with PolyAI
Can AI really hear a call the way a person does?
Deep Learning with PolyAI