All Posts

    [Earley AI Podcast] Episode 29: Maxim Serebryakov

    Artificial Voice Intelligence

    Guest: Maxim Serebryakov

     

     

    About this Episode:


    Today’s guest is Maxim Serebryakov, Co-Founder and CEO at Sanas. Max joins Seth Earley and Chris Featherstone and shares what influenced him to start his company. Max also discusses what it was like to study artificial intelligence at Stanford and how it created a broad perspective on how things work. Be sure to listen in on Mike giving his advice on how you can go above and beyond to help anyone!



    Takeaways:

    • Max was born in New York then shortly after, he moved to Russia where his family is from. When he came back to coming to the US, the accents around him and being an immigrant were the brewing grounds for the creation of his company, Sanas.
    • Max studied at Stanford and he spent a lot of time doing research into artificial intelligence and studying artificial intelligence. Through these experiences, he ended up building Sanas.
    • Artificial intelligence shows the limitations of modern-day voice conversion research. Max learned that you're not just modulating the pitch and tone, you're changing the underlying phonings that are present within it.
    • Max and his team chose to do their deployments initially with contact centers and enterprises. They saw that their pain point is initially with these deployment verticals because speech is very structured.
    • Max’s company, Sanas, works with some of the largest contact centers and top enterprises in the world. They work with them to better help their customer service interactions since it is a crucial part of these companies.


    Quote of the Show:

    • “We ended up building an algorithm that really doesn't exist in the research world. It's very innovative. It works on the edge, works with clients, and it's very efficient.” (11:02)


    Links:



    Ways to Tune In:



    Thanks to our sponsors:

    Earley Information Science Team
    Earley Information Science Team
    We're passionate about enterprise data and love discussing industry knowledge, best practices, and insights. We look forward to hearing from you! Comment below to join the conversation.

    Recent Posts

    [RECORDED] Product Data: Insights for Success - How AI is Automating Product Data Programs

    Artificial Intelligence is changing the way businesses interact with their customers. From hyper-personalized experiences to chatbots built on Large Language Models, AI is driving new investment in digital experiences. That same AI and LLM can also be used to automate your product data program. From data onboarding and validation to generating descriptions and validating images, AI can help generate content faster and at a higher quality level to improve product findability, search, and conversion rates. In our second webinar in the Product Data Mastery series, we’re speaking with Madhu Konety from IceCream Labs to show exactly how AI and product data can work together for your business.

    AI’s Value for Product Data Programs

    By Dan O'Connor, Director of Product Data, Earley Information Science

    The Critical Role of Content Architecture in Generative AI

    What is Generative AI? Generative AI has caught fire in the industry – almost every tech vendor has a ChatGPT-like offering (or claims to have one). They are claiming to use the same technology – a large language model (LLM) (actually there are many Large Language Models both open source and proprietary fine-tuned for various industries and purposes) to access and organize content knowledge of the enterprise. As with previous new technologies, LLMs are getting hyped. But what is generative AI?