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.

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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

Multilingual LLMs and the Values Divide in AI with Sara Hooker - #651

Multilingual LLMs and the Values Divide in AI with Sara Hooker - #651

Today we’re joined by Sara Hooker, director at Cohere and head of Cohere For AI, Cohere’s research lab. In our conversation with Sara, we explore some of the challenges with multilingual models like p...

16 Okt 20231h 18min

Scaling Multi-Modal Generative AI with Luke Zettlemoyer - #650

Scaling Multi-Modal Generative AI with Luke Zettlemoyer - #650

Today we’re joined by Luke Zettlemoyer, professor at University of Washington and a research manager at Meta. In our conversation with Luke, we cover multimodal generative AI, the effect of data on mo...

9 Okt 202338min

Pushing Back on AI Hype with Alex Hanna - #649

Pushing Back on AI Hype with Alex Hanna - #649

Today we’re joined by Alex Hanna, the Director of Research at the Distributed AI Research Institute (DAIR). In our conversation with Alex, we discuss the topic of AI hype and the importance of tacklin...

2 Okt 202349min

Personalization for Text-to-Image Generative AI with Nataniel Ruiz - #648

Personalization for Text-to-Image Generative AI with Nataniel Ruiz - #648

Today we’re joined by Nataniel Ruiz, a research scientist at Google. In our conversation with Nataniel, we discuss his recent work around personalization for text-to-image AI models. Specifically, we ...

25 Sep 202344min

Ensuring LLM Safety for Production Applications with Shreya Rajpal - #647

Ensuring LLM Safety for Production Applications with Shreya Rajpal - #647

Today we’re joined by Shreya Rajpal, founder and CEO of Guardrails AI. In our conversation with Shreya, we discuss ensuring the safety and reliability of language models for production applications. W...

18 Sep 202340min

What’s Next in LLM Reasoning? with Roland Memisevic - #646

What’s Next in LLM Reasoning? with Roland Memisevic - #646

Today we’re joined by Roland Memisevic, a senior director at Qualcomm AI Research. In our conversation with Roland, we discuss the significance of language in humanlike AI systems and the advantages a...

11 Sep 202359min

Is ChatGPT Getting Worse? with James Zou - #645

Is ChatGPT Getting Worse? with James Zou - #645

Today we’re joined by James Zou, an assistant professor at Stanford University. In our conversation with James, we explore the differences in ChatGPT’s behavior over the last few months. We discuss th...

4 Sep 202342min

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