Vanishing Gradients

Oct 07 2024 37 ep. 80 mins 118
Vanishing Gradients Podcast artwork

A podcast about all things data, brought to you by data scientist Hugo Bowne-Anderson. It's time for more critical conversations about the challenges in our industry in order to build better compasses for the solution space! To this end, this podcast will consist of long-format conversations between Hugo and other people who work broadly in the data science, machine learning, and AI spaces. We'll dive deep into all the moving parts of the data world, so if you're new to the space, you'll have an opportunity to learn from the experts. And if you've been around for a while, you'll find out what's happening in many other parts of the data world.

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Episode 1: Introducing Vanishing Gradients

Feb 16 2022 5 mins  
In this brief introduction, Hugo introduces the rationale behind launching a new data science podcast and gets excited about his upcoming guests: Jeremy Howard, Rachael Tatman, and Heather Nolis! Original music, bleeps, and blops by local Sydney legend PlaneFace!

Episode 37: Prompt Engineering, Security in Generative AI, and the Future of AI Research Part 2

Oct 07 2024 50 mins  
Hugo speaks with three leading figures from the world of AI research: Sander Schulhoff, a recent University of Maryland graduate and lead contributor to the Learn Prompting initiative; Philip Resnik, professor at the University of Maryland, known for his pioneering work in computational linguistics; and Dennis Peskoff, a researcher from Princeton specializing in prompt engineering

Episode 36: Prompt Engineering, Security in Generative AI, and the Future of AI Research Part 1

Sep 30 2024 63 mins  
Hugo speaks with three leading figures from the world of AI research: Sander Schulhoff, a recent University of Maryland graduate and lead contributor to the Learn Prompting initiative; Philip Resnik, professor at the University of Maryland, known for his pioneering work in computational linguistics; and Dennis Peskoff, a researcher from Princeton specializing in prompt engineering

Episode 35: Open Science at NASA -- Measuring Impact and the Future of AI

Sep 19 2024 58 mins  
Hugo speaks with Dr. Chelle Gentemann, Open Science Program Scientist for NASA’s Office of the Chief Science Data Officer, about NASA’s ambitious efforts to integrate AI across the research lifecycle. In this episode, we’ll dive deeper into how AI is transforming NASA’s approach to science, making data more accessible and advancing open science practices. We explore Measu

Episode 34: The AI Revolution Will Not Be Monopolized

Aug 22 2024 102 mins  
Hugo speaks with Ines Montani and Matthew Honnibal, the creators of spaCy and founders of Explosion AI. Collectively, they've had a huge impact on the fields of industrial natural language processing (NLP), ML, and AI through their widely-used open-source library spaCy and their innovative annotation tool Prodigy. These tools have become essential for many data scientists and N

Episode 33: What We Learned Teaching LLMs to 1,000s of Data Scientists

Aug 12 2024 85 mins  
Hugo speaks with Dan Becker and Hamel Husain, two veterans in the world of data science, machine learning, and AI education. Collectively, they’ve worked at Google, DataRobot, Airbnb, Github (where Hamel built out the precursor to copilot and more) and they both currently work as independent LLM and Generative AI consultants. Dan and Hamel recently taught a course on fine-tuning

Episode 32: Building Reliable and Robust ML/AI Pipelines

Jul 26 2024 75 mins  
Hugo speaks with Shreya Shankar, a researcher at UC Berkeley focusing on data management systems with a human-centered approach. Shreya's work is at the cutting edge of human-computer interaction (HCI) and AI, particularly in the realm of large language models (LLMs). Her impressive background includes being the first ML engineer at Viaduct, doing research engineering at Google

Episode 31: Rethinking Data Science, Machine Learning, and AI

Jul 09 2024 96 mins  
Hugo speaks with Vincent Warmerdam, a senior data professional and machine learning engineer at :probabl, the exclusive brand operator of scikit-learn. Vincent is known for challenging common assumptions and exploring innovative approaches in data science and machine learning. In this episode, they dive deep into rethinking established methods in data science, machine learning, an

Episode 30: Lessons from a Year of Building with LLMs (Part 2)

Jun 25 2024 75 mins  
Hugo speaks about Lessons Learned from a Year of Building with LLMs with Eugene Yan from Amazon, Bryan Bischof from Hex, Charles Frye from Modal, Hamel Husain from Parlance Labs, and Shreya Shankar from UC Berkeley. These five guests, along with Jason Liu who couldn't join us, have spent the past year building real-world applications with Large Language Models (LLMs). They'

Episode 29: Lessons from a Year of Building with LLMs (Part 1)

Jun 25 2024 90 mins  
Hugo speaks about Lessons Learned from a Year of Building with LLMs with Eugene Yan from Amazon, Bryan Bischof from Hex, Charles Frye from Modal, Hamel Husain from Parlance Labs, and Shreya Shankar from UC Berkeley. These five guests, along with Jason Liu who couldn't join us, have spent the past year building real-world applications with Large Language Models (LLMs). They'