Engineering Production NLP Systems at T-Mobile with Heather Nolis - #600

Engineering Production NLP Systems at T-Mobile with Heather Nolis - #600

Today we’re joined by Heather Nolis, a principal machine learning engineer at T-Mobile. In our conversation with Heather, we explored her machine learning journey at T-Mobile, including their initial proof of concept project, which held the goal of putting their first real-time deep learning model into production. We discuss the use case, which aimed to build a model customer intent model that would pull relevant information about a customer during conversations with customer support. This process has now become widely known as blank assist. We also discuss the decision to use supervised learning to solve this problem and the challenges they faced when developing a taxonomy. Finally, we explore the idea of using small models vs uber-large models, the hardware being used to stand up their infrastructure, and how Heather thinks about the age-old question of build vs buy.

Episoder(781)

Patterns and Middleware for LLM Applications with Kyle Roche - #659

Patterns and Middleware for LLM Applications with Kyle Roche - #659

Today we’re joined by Kyle Roche, founder and CEO of Griptape to discuss patterns and middleware for LLM applications. We dive into the emerging patterns for developing LLM applications, such as off p...

11 Des 202335min

AI Access and Inclusivity as a Technical Challenge with Prem Natarajan - #658

AI Access and Inclusivity as a Technical Challenge with Prem Natarajan - #658

Today we’re joined by Prem Natarajan, chief scientist and head of enterprise AI at Capital One. In our conversation, we discuss AI access and inclusivity as technical challenges and explore some of Pr...

4 Des 202341min

Building LLM-Based Applications with Azure OpenAI with Jay Emery - #657

Building LLM-Based Applications with Azure OpenAI with Jay Emery - #657

Today we’re joined by Jay Emery, director of technical sales & architecture at Microsoft Azure. In our conversation with Jay, we discuss the challenges faced by organizations when building LLM-based a...

28 Nov 202343min

Visual Generative AI Ecosystem Challenges with Richard Zhang - #656

Visual Generative AI Ecosystem Challenges with Richard Zhang - #656

Today we’re joined by Richard Zhang, senior research scientist at Adobe Research. In our conversation with Richard, we explore the research challenges that arise when regarding visual generative AI fr...

20 Nov 202340min

Deploying Edge and Embedded AI Systems with Heather Gorr - #655

Deploying Edge and Embedded AI Systems with Heather Gorr - #655

Today we’re joined by Heather Gorr, principal MATLAB product marketing manager at MathWorks. In our conversation with Heather, we discuss the deployment of AI models to hardware devices and embedded A...

13 Nov 202338min

AI Sentience, Agency and Catastrophic Risk with Yoshua Bengio - #654

AI Sentience, Agency and Catastrophic Risk with Yoshua Bengio - #654

Today we’re joined by Yoshua Bengio, professor at Université de Montréal. In our conversation with Yoshua, we discuss AI safety and the potentially catastrophic risks of its misuse. Yoshua highlights ...

6 Nov 202348min

Delivering AI Systems in Highly Regulated Environments with Miriam Friedel - #653

Delivering AI Systems in Highly Regulated Environments with Miriam Friedel - #653

Today we’re joined by Miriam Friedel, senior director of ML engineering at Capital One. In our conversation with Miriam, we discuss some of the challenges faced when delivering machine learning tools ...

30 Okt 202344min

Mental Models for Advanced ChatGPT Prompting with Riley Goodside - #652

Mental Models for Advanced ChatGPT Prompting with Riley Goodside - #652

Today we’re joined by Riley Goodside, staff prompt engineer at Scale AI. In our conversation with Riley, we explore LLM capabilities and limitations, prompt engineering, and the mental models required...

23 Okt 202339min

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