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In this episode of the 'Deep Learning with PolyAI' podcast, Nikola and Damien discuss PolyAI's recent $50 million Series C funding round led by NVIDIA's NVentures, alongside other notable investors. They explore the company's growth, innovative engineering, and the future of voice AI technology. The conversation also touches upon the recent developments in OpenAI's GPT 4.0, including its ability to handle voice interactions and the technical challenges of latency and interruptions in automated systems. The episode wraps up with a discussion on future product announcements and the broader implications of voice AI in customer service and consumer applications.

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Damien welcomes Fertitta Entertainment's contact center director Brian Jeppesen to the pod to discuss Brian's long career in customer service, the nuances of the casino-hoteling industry, and why roadblocking by IVR is an outdated approach.

Introducing: Conversations - a collection of provocative chats with the next generation of CX leaders.

Read Brian's recent blog here.

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Damien and Nikola tackle the age-old tech question: should enterprise contact centers build or buy AI solutions? They cover pros and cons considered in the decision-making process, highlighting the importance of established vendors, internal capabilities, technological advancements, user experience, and the need for accountability and measuring success.

Yeah, we sell voice AI, so we're a bit biased. Check out this buyer's guide for practical tips on requirements and vendor evaluations.

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Damien welcomes Business Value Analyst Steven Fine to the pod and discusses the evolution of measuring success in contact centers, focusing on integrating AI and automation technologies to improve customer experience and operational efficiency. Their chat emphasizes the importance of marrying sentiment analysis with Customer Satisfaction (CSAT) metrics for a more accurate understanding of customer satisfaction, as well as diving into innovative means of measuring success, such as looking at the entire customer journey and combining bot performance with overall conversation sentiments.

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Today's chat between Nikola and Damien delves into the concept of 'AI washing,' where companies exaggerate their level of investment in AI technology to capitalize on the current hype. The episode covers the evolution of AI, the challenge of distinguishing genuine AI applications from superficial ones, the potential need for regulation to prevent misuse of AI, and the implications for consumer experiences.

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Nikola and Damien delve into the topic of humanizing technology and AI, touching upon the preference for non-human interactions in vulnerable states, the challenges of identifying automated systems during conversations, and the importance of transparency in AI interactions. Opinions on the potential cultural impacts of humanized AI, the debate around maintaining human-like experiences, and the societal and regulatory considerations surrounding the humanization of technology also steer the convo.

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In today's episode, Michelle and Nikola discuss the challenges and strategies involved in managing disruptive change, particularly related to deploying AI in large businesses. Their talk emphasizes the importance of champions within organizations, the role of companies like Accenture, starting small to de-risk projects, and the impact of change management on loyalty and company success.

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Join Damien and Tomasz, a senior machine learning engineer at PolyAI, as they discuss the key highlights of NVIDIA's megacon GTC. They discuss standout sessions, including the announcement of NVIDIA Blackwater platform for reducing cost and energy requirements of high-performance AI systems. They also talk about the concerns around the size of language models, ethical utilization of AI, and PolyAI's presentation on automatic speech recognition. Furthermore, they touch upon the challenges and potential solutions related to large language models, and the preference towards smaller models in the ASR space.

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Laura debuts hosting in today's episode, which discusses various concerns and myths around generative AI, particularly addressing Gartner's prediction of a customer's death due to bad information from AI chatbots. It also delves into real-life scenarios such as the Air Canada lawsuit, mishaps with Google Gemini, and the overall impact of generative AI on public confidence. They offer tips for organizations looking to implement generative AI, focusing on behavior testing, risk mitigation in regulated industries, and data utilization.

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