Start / Vanishing Gradients / Episode 1 introducing vanishing gradients

Episode 1: Introducing Vanishing Gradients

5 min • 16 februari 2022

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!

Senaste avsnitt

Episode 54: Scaling AI: From Colab to Clusters — A Practitioner’s Guide to Distributed Training and Inference

18 juli | 41 min

Episode 53: Human-Seeded Evals & Self-Tuning Agents: Samuel Colvin on Shipping Reliable LLMs

8 juli | 45 min

Episode 43: Tales from 400+ LLM Deployments: Building Reliable AI Agents in Production

16 januari | 61 min

Episode 42: Learning, Teaching, and Building in the Age of AI

4 januari | 80 min

Episode 41: Beyond Prompt Engineering: Can AI Learn to Set Its Own Goals?

30 december 2024 | 44 min

Episode 40: What Every LLM Developer Needs to Know About GPUs

24 december 2024 | 104 min

Episode 39: From Models to Products: Bridging Research and Practice in Generative AI at Google Labs

25 november 2024 | 103 min

Episode 38: The Art of Freelance AI Consulting and Products: Data, Dollars, and Deliverables

4 november 2024 | 84 min

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

8 oktober 2024 | 51 min

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

30 september 2024 | 64 min

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

19 september 2024 | 58 min

Episode 34: The AI Revolution Will Not Be Monopolized

22 augusti 2024 | 103 min

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

12 augusti 2024 | 85 min

Episode 32: Building Reliable and Robust ML/AI Pipelines

27 juli 2024 | 75 min

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

9 juli 2024 | 96 min

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

26 juni 2024 | 75 min

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

26 juni 2024 | 90 min

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

9 juni 2024 | 66 min

Episode 27: How to Build Terrible AI Systems

31 maj 2024 | 92 min

Episode 26: Developing and Training LLMs From Scratch

15 maj 2024 | 112 min

Episode 25: Fully Reproducible ML & AI Workflows

18 mars 2024 | 81 min

Episode 24: LLM and GenAI Accessibility

27 februari 2024 | 90 min

Episode 23: Statistical and Algorithmic Thinking in the AI Age

20 december 2023 | 81 min

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

27 november 2023 | 80 min

Episode 21: Deploying LLMs in Production: Lessons Learned

14 november 2023 | 68 min

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

5 oktober 2023 | 87 min

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

14 augusti 2023 | 83 min

Episode 18: Research Data Science in Biotech

24 maj 2023 | 73 min

Episode 17: End-to-End Data Science

17 februari 2023 | 76 min

Episode 16: Data Science and Decision Making Under Uncertainty

14 december 2022 | 83 min

Episode 15: Uncertainty, Risk, and Simulation in Data Science

7 december 2022 | 54 min

Episode 14: Decision Science, MLOps, and Machine Learning Everywhere

20 november 2022 | 69 min

Episode 13: The Data Science Skills Gap, Economics, and Public Health

11 oktober 2022 | 83 min

Episode 12: Data Science for Social Media: Twitter and Reddit

30 september 2022 | 93 min

Episode 11: Data Science: The Great Stagnation

16 september 2022 | 106 min

Episode 10: Investing in Machine Learning

18 augusti 2022 | 87 min

9: AutoML, Literate Programming, and Data Tooling Cargo Cults

19 juli 2022 | 102 min

Episode 8: The Open Source Cybernetic Revolution

16 maj 2022 | 66 min

Episode 7: The Evolution of Python for Data Science

1 maj 2022 | 63 min

Episode 6: Bullshit Jobs in Data Science (and what to do about them)

4 april 2022 | 87 min

Episode 5: Executive Data Science

23 mars 2022 | 108 min

Episode 4: Machine Learning at T-Mobile

9 mars 2022 | 104 min

Episode 3: Language Tech For All

1 mars 2022 | 93 min

Episode 2: Making Data Science Uncool Again

20 februari 2022 | 106 min

Episode 1: Introducing Vanishing Gradients

16 februari 2022 | 5 min

Episode 1: Introducing Vanishing Gradients

Senaste avsnitt

Episode 54: Scaling AI: From Colab to Clusters — A Practitioner’s Guide to Distributed Training and Inference

Episode 53: Human-Seeded Evals & Self-Tuning Agents: Samuel Colvin on Shipping Reliable LLMs

Episode 52: Why Most LLM Products Break at Retrieval (And How to Fix Them)

Episode 51: Why We Built an MCP Server and What Broke First

Episode 50: A Field Guide to Rapidly Improving AI Products -- With Hamel Husain

Episode 49: Why Data and AI Still Break at Scale (and What to Do About It)

Episode 48: HOW TO BENCHMARK AGI WITH GREG KAMRADT

Episode 47: The Great Pacific Garbage Patch of Code Slop with Joe Reis

Episode 46: Software Composition Is the New Vibe Coding

Episode 45: Your AI application is broken. Here’s what to do about it.

Episode 44: The Future of AI Coding Assistants: Who’s Really in Control?

Episode 43: Tales from 400+ LLM Deployments: Building Reliable AI Agents in Production

Episode 42: Learning, Teaching, and Building in the Age of AI

Episode 41: Beyond Prompt Engineering: Can AI Learn to Set Its Own Goals?

Episode 40: What Every LLM Developer Needs to Know About GPUs

Episode 39: From Models to Products: Bridging Research and Practice in Generative AI at Google Labs

Episode 38: The Art of Freelance AI Consulting and Products: Data, Dollars, and Deliverables

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

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

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

Episode 34: The AI Revolution Will Not Be Monopolized

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

Episode 32: Building Reliable and Robust ML/AI Pipelines

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

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

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

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

Episode 27: How to Build Terrible AI Systems

Episode 26: Developing and Training LLMs From Scratch

Episode 25: Fully Reproducible ML & AI Workflows

Episode 24: LLM and GenAI Accessibility

Episode 23: Statistical and Algorithmic Thinking in the AI Age

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

Episode 21: Deploying LLMs in Production: Lessons Learned

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

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

Episode 18: Research Data Science in Biotech

Episode 17: End-to-End Data Science

Episode 16: Data Science and Decision Making Under Uncertainty

Episode 15: Uncertainty, Risk, and Simulation in Data Science

Episode 14: Decision Science, MLOps, and Machine Learning Everywhere

Episode 13: The Data Science Skills Gap, Economics, and Public Health

Episode 12: Data Science for Social Media: Twitter and Reddit

Episode 11: Data Science: The Great Stagnation

Episode 10: Investing in Machine Learning

9: AutoML, Literate Programming, and Data Tooling Cargo Cults

Episode 8: The Open Source Cybernetic Revolution

Episode 7: The Evolution of Python for Data Science

Episode 6: Bullshit Jobs in Data Science (and what to do about them)

Episode 5: Executive Data Science

Episode 4: Machine Learning at T-Mobile

Episode 3: Language Tech For All

Episode 2: Making Data Science Uncool Again

Episode 1: Introducing Vanishing Gradients