Vanishing Gradients

Episode 34: The AI Revolution Will Not Be Monopolized

August 22nd, 2024  |  Season 1  |  1 hr 42 mins

data science, genai, llms, machine learning, nlp

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.

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

August 12th, 2024  |  Season 1  |  1 hr 25 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 pre-cursor 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 large language models that evolved into a full-fledged conference, attracting over 2,000 participants.

In this episode, we dive deep into their experience and the unique insights it gave them into the current state and future of AI education and application.

Episode 32: Building Reliable and Robust ML/AI Pipelines

July 27th, 2024  |  Season 1  |  1 hr 15 mins

data science, genai, llms, machine learning

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 Brain, and software engineering at Facebook.

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

July 9th, 2024  |  Season 1  |  1 hr 36 mins

data science, genai, llms, machine learning

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.

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

June 26th, 2024  |  Season 1  |  1 hr 15 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 (Part 2).

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

June 26th, 2024  |  Season 1  |  1 hr 30 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 (Part 1).

Episode 28: Beyond Supervised Learning: The Rise of In-Context Learning with LLMs

June 10th, 2024  |  Season 1  |  1 hr 5 mins

data science, genai, llms, machine learning

Hugo speaks with Alan Nichol, co-founder and CTO of Rasa, where they build software to enable developers to create enterprise-grade conversational AI and chatbot systems across industries like telcos, healthcare, fintech, and government.

Episode 27: How to Build Terrible AI Systems

May 31st, 2024  |  Season 1  |  1 hr 32 mins

data science, genai, llms, machine learning

Hugo speaks with Jason Liu, an independent consultant who uses his expertise in recommendation systems to help fast-growing startups build out their RAG applications. He was previously at Meta and Stitch Fix is also the creator of Instructor, Flight, and an ML and data science educator.

Episode 26: Developing and Training LLMs From Scratch

May 15th, 2024  |  Season 1  |  1 hr 51 mins

data science, genai, machine learning

Hugo speaks with Sebastian Raschka, a machine learning & AI researcher, programmer, and author.They’ll tell you everything you need to know about LLMs, but were too afraid to ask: from covering the entire LLM lifecycle, what type of skills you need to work with them, what type of resources and hardware, prompt engineering vs fine-tuning vs RAG, how to build an LLM from scratch, and much more.

Episode 25: Fully Reproducible ML & AI Workflows

March 18th, 2024  |  Season 1  |  1 hr 20 mins

data science, genai, machine learning

Hugo speaks with Omoju Miller, a machine learning guru and founder and CEO of Fimio, where she is building 21st century dev tooling.

Episode 24: LLM and GenAI Accessibility

February 27th, 2024  |  Season 1  |  1 hr 30 mins

data science, genai, machine learning

Hugo speaks with Johno Whitaker, a Data Scientist/AI Researcher doing R&D with answer.ai, about where we’ve come from regarding tooling and accessibility for foundation models, ML, and AI, where we are, and where we’re going.

Episode 23: Statistical and Algorithmic Thinking in the AI Age

December 21st, 2023  |  Season 1  |  1 hr 20 mins

Hugo speaks with Allen Downey, curriculum designer at Brilliant, Professor Emeritus at Olin College, and author, about the key statistical and data skills we all need to navigate an increasingly data-driven and algorithmic world. The goal will be to dive deep into the statistical paradoxes and fallacies that get in the way of using data to make informed decisions.

Episode 22: LLMs, OpenAI, and the Existential Crisis for Machine Learning Engineering

November 28th, 2023  |  Season 1  |  1 hr 20 mins

Jeremy Howard (Fast.ai), Shreya Shankar (UC Berkeley), and Hamel Husain (Parlance Labs) join Hugo Bowne-Anderson to talk about how LLMs and OpenAI are changing the worlds of data science, machine learning, and machine learning engineering.

Episode 21: Deploying LLMs in Production: Lessons Learned

November 14th, 2023  |  Season 1  |  1 hr 8 mins

Hugo speaks with Hamel Husain (ex-Github, Airbnb), a machine learning engineer who loves building machine learning infrastructure and tools, about generative AI, large language models, the business value they can generate, and how to get started.

Episode 20: Data Science: Past, Present, and Future

October 5th, 2023  |  Season 1  |  1 hr 26 mins

Hugo speaks with Chris Wiggins (Columbia, NYTimes) and Matthew Jones (Princeton) about their recent book How Data Happened, and the Columbia course it expands upon, data: past, present, and future.

Episode 19: Privacy and Security in Data Science and Machine Learning

August 15th, 2023  |  Season 1  |  1 hr 23 mins

Hugo speaks with Katharine Jarmul about privacy and security in data science and machine learning. Katharine is a Principal Data Scientist at Thoughtworks Germany focusing on privacy, ethics, and security for data science workflows.