Shows
Vanishing GradientsEpisode 64: Data Science Meets Agentic AI with Michael Kennedy (Talk Python)We have been sold a story of complexity. Michael Kennedy (Talk Python) argues we can escape this by relentlessly focusing on the problem at hand, reducing costs by orders of magnitude in software, data, and AI.
In this episode, Michael joins Hugo to dig into the practical side of running Python systems at scale. They connect these ideas to the data science workflow, exploring which software engineering practices allow AI teams to ship faster and with more confidence. They also detail how to deploy systems without unnecessary complexity and how Agentic AI is fundamentally reshaping development workflows.
2025-12-031h 02Vanishing GradientsEpisode 63: Why Gemini 3 Will Change How You Build AI Agents with Ravin Kumar (Google DeepMind)Gemini 3 is a few days old and the massive leap in performance and model reasoning has big implications for builders: as models begin to self-heal, builders are literally tearing out the functionality they built just months ago... ripping out the defensive coding and reshipping their agent harnesses entirely.
Ravin Kumar (Google DeepMind) joins Hugo to breaks down exactly why the rapid evolution of models like Gemini 3 is changing how we build software. They detail the shift from simple tool calling to building reliable "Agent Harnesses", explore the architectural tradeoffs between deterministic workflows and high-agency systems, the nuance...
2025-11-221h 00Vanishing GradientsEpisode 62: Practical AI at Work: How Execs and Developers Can Actually Use LLMsMany leaders are trapped between chasing ambitious, ill-defined AI projects and the paralysis of not knowing where to start. Dr. Randall Olson argues that the real opportunity isn't in moonshots, but in the "trillions of dollars of business value" available right now. As co-founder of Wyrd Studios, he bridges the gap between data science, AI engineering, and executive strategy to deliver a practical framework for execution.
In this episode, Randy and Hugo lay out how to find and solve what might be considered "boring but valuable" problems, like an EdTech company automating 20% of its support tickets with...
2025-10-3159 min
Agile and Project Management - DrunkenPM RadioNavigating AI - Making Sense of Agents and When To Use Them with Hugo Bowne-AndersonIn this conversation, Dave Prior and Hugo Bowne-Anderson discuss the evolving landscape of AI and data science, focusing on the role of AI agents in solving business problems. Hugo shares insights on how to effectively implement AI solutions, the importance of understanding the underlying data, and the need for continuous improvement in AI systems. They also touch on the skills necessary for navigating the AI landscape, the value of collaboration between technical and non-technical teams, and the importance of assessing the value of AI projects. Hugo concludes by offering a course on building AI applications, emphasizing the iterative nature of...
2025-10-2843 min
DataTalks.ClubHow to Build and Evaluate AI systems in the Age of LLMs - Hugo Bowne-AndersonIn this talk, Hugo Bowne-Anderson, an independent data and AI consultant, educator, and host of the podcasts Vanishing Gradients and High Signal, shares his journey from academic research and curriculum design at DataCamp to advising teams at Netflix, Meta, and the US Air Force. Together, we explore how to build reliable, production-ready AI systems—from prompt evaluation and dataset design to embedding agents into everyday workflows.You’ll learn about: How to structure teams and incentives for successful AI adoptionPractical prompting techniques for accurate timestamp and data generationBuilding and maintaining evaluation sets to avoi...
2025-10-241h 01Vanishing GradientsEpisode 61: The AI Agent Reliability Cliff: What Happens When Tools Fail in ProductionMost AI teams find their multi-agent systems devolving into chaos, but ML Engineer Alex Strick van Linschoten argues they are ignoring the production reality. In this episode, he draws on insights from the LLM Ops Database (750+ real-world deployments then; now nearly 1,000!) to systematically measure and engineer constraint, turning unreliable prototypes into robust, enterprise-ready AI.
Drawing from his work at Zen ML, Alex details why success requires scaling down and enforcing MLOps discipline to navigate the unpredictable "Agent Reliability Cliff". He provides the essential architectural shifts, evaluation hygiene techniques, and practical steps needed to move beyond guesswork and...
2025-10-1628 minVanishing GradientsEpisode 60: 10 Things I Hate About AI Evals with Hamel HusainMost AI teams find "evals" frustrating, but ML Engineer Hamel Husain argues they’re just using the wrong playbook. In this episode, he lays out a data-centric approach to systematically measure and improve AI, turning unreliable prototypes into robust, production-ready systems.
Drawing from his experience getting countless teams unstuck, Hamel explains why the solution requires a "revenge of the data scientists." He details the essential mindset shifts, error analysis techniques, and practical steps needed to move beyond guesswork and build AI products you can actually trust.
We talk through:
The 10(+1) critical mistakes that cause te...
2025-09-301h 13Vanishing GradientsEpisode 59: Patterns and Anti-Patterns For Building with AIJohn Berryman (Arcturus Labs; early GitHub Copilot engineer; co-author of Relevant Search and Prompt Engineering for LLMs) has spent years figuring out what makes AI applications actually work in production. In this episode, he shares the “seven deadly sins” of LLM development — and the practical fixes that keep projects from stalling.
From context management to retrieval debugging, John explains the patterns he’s seen succeed, the mistakes to avoid, and why it helps to think of an LLM as an “AI intern” rather than an all-knowing oracle.
We talk through:
Why chasing perfect accuracy is a dead en...
2025-09-2447 minVanishing GradientsEpisode 58: Building GenAI Systems That Make Business Decisions with Thomas Wiecki (PyMC Labs)While most conversations about generative AI focus on chatbots, Thomas Wiecki (PyMC Labs, PyMC) has been building systems that help companies make actual business decisions. In this episode, he shares how Bayesian modeling and synthetic consumers can be combined with LLMs to simulate customer reactions, guide marketing spend, and support strategy.
Drawing from his work with Colgate and others, Thomas explains how to scale survey methods with AI, where agents fit into analytics workflows, and what it takes to make these systems reliable.
We talk through:
Using LLMs as “synthetic consumers” to simulate surveys and...
2025-09-091h 00Vanishing GradientsEpisode 57: AI Agents and LLM Judges at Scale: Processing Millions of Documents (Without Breaking the Bank)While many people talk about “agents,” Shreya Shankar (UC Berkeley) has been building the systems that make them reliable. In this episode, she shares how AI agents and LLM judges can be used to process millions of documents accurately and cheaply.
Drawing from work on projects ranging from databases of police misconduct reports to large-scale customer transcripts, Shreya explains the frameworks, error analysis, and guardrails needed to turn flaky LLM outputs into trustworthy pipelines.
We talk through:
Treating LLM workflows as ETL pipelines for unstructured text
Error analysis: why you need humans reviewing the...
2025-08-2941 minVanishing GradientsEpisode 56: DeepMind Just Dropped Gemma 270M... And Here’s Why It MattersWhile much of the AI world chases ever-larger models, Ravin Kumar (Google DeepMind) and his team build across the size spectrum, from billions of parameters down to this week’s release: Gemma 270M, the smallest member yet of the Gemma 3 open-weight family. At just 270 million parameters, a quarter the size of Gemma 1B, it’s designed for speed, efficiency, and fine-tuning.
We explore what makes 270M special, where it fits alongside its billion-parameter siblings, and why you might reach for it in production even if you think “small” means “just for experiments.”
We talk through:
Where 27...
2025-08-1445 minVanishing GradientsEpisode 55: From Frittatas to Production LLMs: Breakfast at SciPyTraditional software expects 100% passing tests. In LLM-powered systems, that’s not just unrealistic — it’s a feature, not a bug. Eric Ma leads research data science in Moderna’s data science and AI group, and over breakfast at SciPy we explored why AI products break the old rules, what skills different personas bring (and miss), and how to keep systems alive after the launch hype fades.
You’ll hear the clink of coffee cups, the murmur of SciPy in the background, and the occasional bite of frittata as we talk (hopefully also a feature, not a bug!)
We t...
2025-08-1238 minVanishing GradientsEpisode 54: Scaling AI: From Colab to Clusters — A Practitioner’s Guide to Distributed Training and InferenceColab is cozy. But production won’t fit on a single GPU.
Zach Mueller leads Accelerate at Hugging Face and spends his days helping people go from solo scripts to scalable systems. In this episode, he joins me to demystify distributed training and inference — not just for research labs, but for any ML engineer trying to ship real software.
We talk through:
• From Colab to clusters: why scaling isn’t just about training massive models, but serving agents, handling load, and speeding up iteration
• Zero-to-two GPUs: how to get started without Kubernetes, Slurm, or a PhD in n...
2025-07-1841 min
Synthesized SunsetsXX: A Career in Science Fiction Criticism w/Rich HortonThis week we spoke with long time Science Fiction reviewer and anthologist Rich Horton. We talked about his experience in the early internet sci-fi community on Usenet, his career in sci-fi criticism at Tangent and Locus, his work creating sci-fi/fantasy best of the year anthologies, our thoughts on the current slate of Hugo Award nominees, and more.We hope you enjoy!TIMESTAMPS:0:14 - Introduction0:39 - What drew you to Substack?1:33 - Rich Horton started Substack by reading people already here (Ted Gioia, Lincoln Michel, Naomi Kanakia)
2025-07-101h 38Vanishing GradientsEpisode 53: Human-Seeded Evals & Self-Tuning Agents: Samuel Colvin on Shipping Reliable LLMsDemos are easy; durability is hard. Samuel Colvin has spent a decade building guardrails in Python (first with Pydantic, now with Logfire), and he’s convinced most LLM failures have nothing to do with the model itself. They appear where the data is fuzzy, the prompts drift, or no one bothered to measure real-world behavior. Samuel joins me to show how a sprinkle of engineering discipline keeps those failures from ever reaching users.
We talk through:
• Tiny labels, big leverage: how five thumbs-ups/thumbs-downs are enough for Logfire to build a rubric that scores every call in r...
2025-07-0844 minVanishing GradientsEpisode 52: Why Most LLM Products Break at Retrieval (And How to Fix Them)Most LLM-powered features do not break at the model. They break at the context. So how do you retrieve the right information to get useful results, even under vague or messy user queries?
In this episode, we hear from Eric Ma, who leads data science research in the Data Science and AI group at Moderna. He shares what it takes to move beyond toy demos and ship LLM features that actually help people do their jobs.
We cover:
• How to align retrieval with user intent and why cosine similarity is not the answer
• How...
2025-07-0228 minVanishing GradientsEpisode 51: Why We Built an MCP Server and What Broke FirstWhat does it take to actually ship LLM-powered features, and what breaks when you connect them to real production data?
In this episode, we hear from Philip Carter — then a Principal PM at Honeycomb and now a Product Management Director at Salesforce. In early 2023, he helped build one of the first LLM-powered SaaS features to ship to real users. More recently, he and his team built a production-ready MCP server.
We cover:
• How to evaluate LLM systems using human-aligned judges
• The spreadsheet-driven process behind shipping Honeycomb’s first LLM feature
• The challenges of tool us...
2025-06-2647 minVanishing GradientsEpisode 50: A Field Guide to Rapidly Improving AI Products -- With Hamel HusainIf we want AI systems that actually work, we need to get much better at evaluating them, not just building more pipelines, agents, and frameworks.
In this episode, Hugo talks with Hamel Hussain (ex-Airbnb, GitHub, DataRobot) about how teams can improve AI products by focusing on error analysis, data inspection, and systematic iteration. The conversation is based on Hamel’s blog post A Field Guide to Rapidly Improving AI Products, which he joined Hugo’s class to discuss.
They cover:
🔍 Why most teams struggle to measure whether their systems are actually improving
📊 How error...
2025-06-1727 minVanishing GradientsEpisode 49: Why Data and AI Still Break at Scale (and What to Do About It)If we want AI systems that actually work in production, we need better infrastructure—not just better models.
In this episode, Hugo talks with Akshay Agrawal (Marimo, ex-Google Brain, Netflix, Stanford) about why data and AI pipelines still break down at scale, and how we can fix the fundamentals: reproducibility, composability, and reliable execution.
They discuss:
🔁 Why reactive execution matters—and how current tools fall short
🛠️ The design goals behind Marimo, a new kind of Python notebook
⚙️ The hidden costs of traditional workflows (and what breaks at scale)
📦 What it takes to build modular, m...
2025-06-051h 21
Synthesized SunsetsXVIII: Chinese Sci-Fi Fandom w/ Regina Kanyu WangThis week we hosted Regina Kanyu Wang, an award-winning writer and editor of Chinese science fiction. In 2022, she co-edited The Way Spring Arrives, a pioneering collection of stories from Chinese female and non-binary authors. We were super excited to have someone from the scene help us develop our thoughts about Chinese science fiction, which eventually turned into Kevin’s article “Golden Age Science Fiction is Being Reborn… in China?”.In this episode, we discuss Regina’s curatorial approach, the differences between America and China, and what it’s like to be a sci-fi fan outside of the Anglosphere...
2025-06-031h 35Vanishing GradientsEpisode 48: HOW TO BENCHMARK AGI WITH GREG KAMRADTIf we want to make progress toward AGI, we need a clear definition of intelligence—and a way to measure it.
In this episode, Hugo talks with Greg Kamradt, President of the ARC Prize Foundation, about ARC-AGI: a benchmark built on Francois Chollet’s definition of intelligence as “the efficiency at which you learn new things.” Unlike most evals that focus on memorization or task completion, ARC is designed to measure generalization—and expose where today’s top models fall short.
They discuss:
🧠 Why we still lack a shared definition of intelligence
🧪 How ARC tasks force mo...
2025-05-231h 04
Catalog & Cocktails: The Honest, No-BS Data PodcastHow to Get Out of AI Proof-of-Concept Purgatory with Hugo Bowne-AndersonHugo Bowne-Anderson, Independent Data & AI Scientist, joins us to tackle why most AI applications fail to make it past the demo stage. We'll explore his concept of Evaluation-Driven Development (EDD) and how treating evaluation as a continuous process—not just a final step—can help teams escape "Proof-of-Concept Purgatory." How can we build AI applications that remain reliable and adaptable over time? What shifts are happening as boundaries between data, ML, and product development collapse? From practical testing approaches to monitoring strategies, this episode offers essential insights for anyone looking to create AI applications that deliver genuine business value beyo...
2025-04-1059 min
Catalog & Cocktails: The Honest, No-BS Data PodcastTAKEAWAYS - How to Get Out of AI Proof-of-Concept Purgatory with Hugo Bowne-AndersonHugo Bowne-Anderson, Independent Data & AI Scientist, joins us to tackle why most AI applications fail to make it past the demo stage. We'll explore his concept of Evaluation-Driven Development (EDD) and how treating evaluation as a continuous process—not just a final step—can help teams escape "Proof-of-Concept Purgatory." How can we build AI applications that remain reliable and adaptable over time? What shifts are happening as boundaries between data, ML, and product development collapse? From practical testing approaches to monitoring strategies, this episode offers essential insights for anyone looking to create AI applications that deliver genuine business value beyo...
2025-04-1005 minVanishing GradientsEpisode 47: The Great Pacific Garbage Patch of Code Slop with Joe ReisWhat if the cost of writing code dropped to zero — but the cost of understanding it skyrocketed?
In this episode, Hugo sits down with Joe Reis to unpack how AI tooling is reshaping the software development lifecycle — from experimentation and prototyping to deployment, maintainability, and everything in between.
Joe is the co-author of Fundamentals of Data Engineering and a longtime voice on the systems side of modern software. He’s also one of the sharpest critics of “vibe coding” — the emerging pattern of writing software by feel, with heavy reliance on LLMs and little regard for structur...
2025-04-071h 19Vanishing GradientsEpisode 46: Software Composition Is the New Vibe CodingWhat if building software felt more like composing than coding?
In this episode, Hugo and Greg explore how LLMs are reshaping the way we think about software development—from deterministic programming to a more flexible, prompt-driven, and collaborative style of building. It’s not just hype or grift—it’s a real shift in how we express intent, reason about systems, and collaborate across roles.
Hugo speaks with Greg Ceccarelli—co-founder of SpecStory, former CPO at Pluralsight, and Director of Data Science at GitHub—about the rise of software composition and how it changes the way individu...
2025-04-031h 08Vanishing GradientsEpisode 45: Your AI application is broken. Here’s what to do about it.Too many teams are building AI applications without truly understanding why their models fail. Instead of jumping straight to LLM evaluations, dashboards, or vibe checks, how do you actually fix a broken AI app?
In this episode, Hugo speaks with Hamel Husain, longtime ML engineer, open-source contributor, and consultant, about why debugging generative AI systems starts with looking at your data.
In this episode, we dive into:
Why “look at your data” is the best debugging advice no one follows.
How spreadsheet-based error analysis can uncover failure modes faster than complex dashboards.
The...
2025-02-201h 17
The Joe Reis ShowHugo Bowne-Anderson - Exploring the Future of AI and AutomationHugo Bowne-Anderson and I chat about the future of AI and automation, agents, and much more.
2025-02-181h 22Vanishing GradientsEpisode 44: The Future of AI Coding Assistants: Who’s Really in Control?AI coding assistants are reshaping how developers write, debug, and maintain code—but who’s really in control? In this episode, Hugo speaks with Tyler Dunn, CEO and co-founder of Continue, an open-source AI-powered code assistant that gives developers more customization and flexibility in their workflows.
In this episode, we dive into:
The trade-offs between proprietary vs. open-source AI coding assistants—why open-source might be the future.
How structured workflows, modular AI, and customization help developers maintain control over their tools.
The evolution of AI-powered coding, from autocomplete to intelligent code suggestions and beyond.
Why the best d...
2025-02-041h 34Vanishing GradientsEpisode 43: Tales from 400+ LLM Deployments: Building Reliable AI Agents in ProductionHugo speaks with Alex Strick van Linschoten, Machine Learning Engineer at ZenML and creator of a comprehensive LLMOps database documenting over 400 deployments. Alex's extensive research into real-world LLM implementations gives him unique insight into what actually works—and what doesn't—when deploying AI agents in production.
In this episode, we dive into:
The current state of AI agents in production, from successes to common failure modes
Practical lessons learned from analyzing hundreds of real-world LLM deployments
How companies like Anthropic, Klarna, and Dropbox are using patterns like ReAct, RAG, and microservices to build reliable systems
The evol...
2025-01-161h 01Vanishing GradientsEpisode 42: Learning, Teaching, and Building in the Age of AIIn this episode of Vanishing Gradients, the tables turn as Hugo sits down with Alex Andorra, host of Learning Bayesian Statistics. Hugo shares his journey from mathematics to AI, reflecting on how Bayesian inference shapes his approach to data science, teaching, and building AI-powered applications.
They dive into the realities of deploying LLM applications, overcoming “proof-of-concept purgatory,” and why first principles and iteration are critical for success in AI. Whether you’re an educator, software engineer, or data scientist, this episode offers valuable insights into the intersection of AI, product development, and real-world deployment.
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2025-01-041h 20Vanishing GradientsEpisode 41: Beyond Prompt Engineering: Can AI Learn to Set Its Own Goals?Hugo Bowne-Anderson hosts a panel discussion from the MLOps World and Generative AI Summit in Austin, exploring the long-term growth of AI by distinguishing real problem-solving from trend-based solutions. If you're navigating the evolving landscape of generative AI, productionizing models, or questioning the hype, this episode dives into the tough questions shaping the field.
The panel features:
Ben Taylor (Jepson) – CEO and Founder at VEOX Inc., with experience in AI exploration, genetic programming, and deep learning.
Joe Reis – Co-founder of Ternary Data and author of Fundamentals of Data Engineering.
Juan Sequeda – Principal Scientist and Head o...
2024-12-3143 min
Learning Bayesian StatisticsLearning and Teaching in the Age of AI, with Hugo Bowne-AndersonProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meOur theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work!Visit our Patreon page to unlock exclusive Bayesian swag ;)Takeaways:Effective data science education requires feedback and rapid iteration.Building LLM applications presents unique challenges and opportunities.The software development lifecycle for AI differs from traditional methods.Collaboration between data scientists and software engineers is crucial.Hugo's new cour...
2024-12-261h 23Learning Bayesian StatisticsLearning and Teaching in the Age of AI, with Hugo Bowne-AndersonProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meOur theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work!Visit our Patreon page to unlock exclusive Bayesian swag ;)Takeaways:Effective data science education requires feedback and rapid iteration.Building LLM applications presents unique challenges and opportunities.The software development lifecycle for AI differs from traditional methods.Collaboration between data scientists and software engineers is crucial.Hugo's new cour...
2024-12-261h 23Vanishing GradientsEpisode 40: What Every LLM Developer Needs to Know About GPUsHugo speaks with Charles Frye, Developer Advocate at Modal and someone who really knows GPUs inside and out. If you’re a data scientist, machine learning engineer, AI researcher, or just someone trying to make sense of hardware for LLMs and AI workflows, this episode is for you.
Charles and Hugo dive into the practical side of GPUs—from running inference on large models, to fine-tuning and even training from scratch. They unpack the real pain points developers face, like figuring out:
How much VRAM you actually need.
Why memory—not compute—ends up being the bott...
2024-12-241h 43
Design Her Travel: Tips & Inspiring Stories for Women and Solo TravelersHow to Become a Private Yacht Chef and Travel the World: Insights from a Superyacht Veteran #134What does it take to become a chef in one of the most exclusive industries in the world? This week’s episode is part of our Below Deck IRL: What It Really Takes to Work in the Superyacht Industry and Get Paid to Travel the World series. Host Kim Anderson chats with Chris DeMaillet, a seasoned chef with over 20 years of experience in the exclusive world of superyachts. From Michelin-starred kitchens to the high seas, Chris shares his journey and spills the tea on what it takes to thrive as a pri...
2024-12-1050 minDesign Her Travel: Tips & Inspiring Stories for Women and Solo TravelersSeaman's Airfare - The Travel Hack You Didn't Know You Needed | TRAVEL TALK #133Ever heard of seaman’s airfare? This little-known travel hack could change the way you fly!In this week’s Travel Talk episode, host Kim Anderson dives into one of the lesser-known perks of working in the yachting industry—seaman’s airfare. This episode, inspired by her conversation earlier this week with Hugo Ortega, founder of Superyacht Sunday School (Episode #132), explores what this unique travel hack is all about and why it’s a game-changer for yacht crew and maritime professionals.As part of the Below Deck IRL series, Kim breaks down how s...
2024-12-0516 minDesign Her Travel: Tips & Inspiring Stories for Women and Solo TravelersBelow Deck IRL: How to Work on Superyachts and Get Paid to Travel w/ Hugo Ortega #132If you’re hooked on the drama and glamour of Below Deck, imagine living it for real—but with fewer tantrums and way more travel. This week’s episode dives into the reality of working as private yacht crew, showing you how to turn your wanderlust into a paycheck while exploring the world’s most exclusive destinations. Learn how to step into this exciting, lucrative career and live the ultimate Below Deck lifestyle.Joining host Kim Anderson is Hugo Ortega, a seasoned yachtie with over a decade of experience in the pr...
2024-12-0355 minVanishing GradientsEpisode 39: From Models to Products: Bridging Research and Practice in Generative AI at Google LabsHugo speaks with Ravin Kumar,*Senior Research Data Scientist at Google Labs. Ravin’s career has taken him from building rockets at SpaceX to driving data science and technology at Sweetgreen, and now to advancing generative AI research and applications at Google Labs and DeepMind. His multidisciplinary experience gives him a rare perspective on building AI systems that combine technical rigor with practical utility.
In this episode, we dive into:
• Ravin’s fascinating career path, including the skills and mindsets needed to work effectively with AI and machine learning models at different stages of the pipeline.
...
2024-11-251h 43Vanishing GradientsEpisode 38: The Art of Freelance AI Consulting and Products: Data, Dollars, and DeliverablesHugo speaks with Jason Liu, an independent AI consultant with experience at Meta and Stitch Fix. At Stitch Fix, Jason developed impactful AI systems, like a $50 million product similarity search and the widely adopted Flight recommendation framework. Now, he helps startups and enterprises design and deploy production-level AI applications, with a focus on retrieval-augmented generation (RAG) and scalable solutions.
This episode is a bit of an experiment. Instead of our usual technical deep dives, we’re focusing on the world of AI consulting and freelancing. We explore Jason’s consulting playbook, covering how he structures contracts to maxi...
2024-11-051h 23Vanishing GradientsEpisode 37: Prompt Engineering, Security in Generative AI, and the Future of AI Research Part 2Hugo 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 and its applications in the social sciences.
This is Part 2 of a special two-part episode, prompted—no pun intended—by these guys being part of a team, led by Sander, that wrote a 76-page survey analyzing prompting techniques, agents, and generative AI. The...
2024-10-0850 minVanishing GradientsEpisode 36: Prompt Engineering, Security in Generative AI, and the Future of AI Research Part 1Hugo 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 and its applications in the social sciences.
This is Part 1 of a special two-part episode, prompted—no pun intended—by these guys being part of a team, led by Sander, that wrote a 76-page survey analyzing prompting techniques, agents, and generative AI. The...
2024-09-301h 03Vanishing GradientsEpisode 35: Open Science at NASA -- Measuring Impact and the Future of AIHugo 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
Measuring the Impact of Open Science: How NASA is developing new metrics to evaluate the effectiveness of open science, moving beyond traditional publication-based assessments.
The Process of Scientific Discovery: Insights into the collaborative nature of research and how breakthr...
2024-09-1958 minVanishing GradientsEpisode 34: The AI Revolution Will Not Be MonopolizedHugo 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 NLP practitioners in industry and academia alike.
In this wide-ranging discussion, we dive into:
• The evolution of applied NLP and its role in industry
• The balance between large language models and smaller, specialized models
• Human-in-the-loop distillation for cr...
2024-08-221h 42Vanishing GradientsEpisode 33: What We Learned Teaching LLMs to 1,000s of Data ScientistsHugo 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 large language models that evolved into a full-fledged conference, attracting over 2,000 participants. This experience gave them unique insights into the current state and future of AI education and application.
In this episode, we dive in...
2024-08-121h 25Vanishing GradientsEpisode 32: Building Reliable and Robust ML/AI PipelinesHugo 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.
In this episode, we dive deep into the world of LLMs and the critical challenges of building reliable AI pipelines. We'll explore:
The fascinating journey from classic machine learning to the current LLM...
2024-07-271h 15Vanishing GradientsEpisode 31: Rethinking Data Science, Machine Learning, and AIHugo 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, and AI. We explore Vincent's principled approach to the field, including:
The critical importance of exposing yourself to real-world problems before applying ML solutions
Framing problems correctly and understanding the data generating process
The power of visualization and human intuition in data analysis
...
2024-07-091h 36Vanishing GradientsEpisode 30: Lessons from a Year of Building with LLMs (Part 2)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've distilled their experiences into a report of 42 lessons across operational, strategic, and tactical dimensions, and they're here to share their insights.
We’ve split this roundtable into 2 episodes and, in this second episode, we'll ex...
2024-06-261h 15Vanishing GradientsEpisode 29: Lessons from a Year of Building with LLMs (Part 1)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've distilled their experiences into a report of 42 lessons across operational, strategic, and tactical dimensions, and they're here to share their insights.
We’ve split this roundtable into 2 episodes and, in this first episode, we'll ex...
2024-06-261h 30Vanishing GradientsEpisode 28: Beyond Supervised Learning: The Rise of In-Context Learning with LLMsHugo 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.
What's super cool is that Alan and the Rasa team have been doing this type of thing for over a decade, giving them a wealth of wisdom on how to effectively incorporate LLMs into chatbots - and how not to. For example, if you want a chatbot that takes specific and important actions like transferring money, do you want to fully entrust the conversation...
2024-06-101h 05Vanishing GradientsEpisode 27: How to Build Terrible AI SystemsHugo 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.
They talk about how Jason approaches consulting companies across many industries, including construction and sales, in building production LLM apps, his playbook for getting ML and AI up and running to build and maintain such apps, and the future of tooling to do so.
They take an inverted thinking...
2024-05-311h 32Vanishing GradientsEpisode 26: Developing and Training LLMs From ScratchHugo speaks with Sebastian Raschka, a machine learning & AI researcher, programmer, and author. As Staff Research Engineer at Lightning AI, he focuses on the intersection of AI research, software development, and large language models (LLMs).
How do you build LLMs? How can you use them, both in prototype and production settings? What are the building blocks you need to know about?
In this episode, we’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...
2024-05-151h 51Vanishing GradientsEpisode 25: Fully Reproducible ML & AI WorkflowsHugo speaks with Omoju Miller, a machine learning guru and founder and CEO of Fimio, where she is building 21st century dev tooling. In the past, she was Technical Advisor to the CEO at GitHub, spent time co-leading non-profit investment in Computer Science Education for Google, and served as a volunteer advisor to the Obama administration’s White House Presidential Innovation Fellows.
We need open tools, open data, provenance, and the ability to build fully reproducible, transparent machine learning workflows. With the advent of closed-source, vendor-based APIs and compute becoming a form of gate-keeping, developer tools are at...
2024-03-181h 20Vanishing GradientsEpisode 24: LLM and GenAI AccessibilityHugo speaks with Johno Whitaker, a Data Scientist/AI Researcher doing R&D with answer.ai. His current focus is on generative AI, flitting between different modalities. He also likes teaching and making courses, having worked with both Hugging Face and fast.ai in these capacities.
Johno recently reminded Hugo how hard everything was 10 years ago: “Want to install TensorFlow? Good luck. Need data? Perhaps try ImageNet. But now you can use big models from Hugging Face with hi-res satellite data and do all of this in a Colab notebook. Or think ecology and vision models… or medi...
2024-02-271h 30
Indisch & IndonesischVerborgen Identiteit (Een Stem voor Komot), met Saskia Cornets de Groot*** Zin om online Indonesisch te leren of meer te leren over de Indonesische cultuur? Scroll naar beneden voor informatie over BaliBound Academy, Indonesisch Plus Plus, en Indonesisch DigiTaal ***Verborgen Identiteit (Een Stem voor Komot)Vandaag praat ik met Saskia Cornets de Groot. Saskia beschrijft zichzelf als vrouw, moeder en indo; daarnaast is zij een nakomeling van zowel de rechtsgeleerde Hugo de Groot en verschillende generaties koloniale bestuurders in voormalig Nederlands-Indie als van een nyai, haar Sundanese overgrootmoeder Komot. De afgelopen jaren maakte Saskia een aantal reizen naar Indonesië om haar Indische achtergrond en gesc...
2024-02-251h 01Vanishing GradientsEpisode 23: Statistical and Algorithmic Thinking in the AI AgeHugo speaks with Allen Downey, a curriculum designer at Brilliant, Professor Emeritus at Olin College, and the author of Think Python, Think Bayes, Think Stats, and other computer science and data science books. In 2019-20 he was a Visiting Professor at Harvard University. He previously taught at Wellesley College and Colby College and was a Visiting Scientist at Google. He is also the author of the upcoming book Probably Overthinking It!
They discuss Allen's new book and the key statistical and data skills we all need to navigate an increasingly data-driven and algorithmic world. The goal was...
2023-12-201h 20Vanishing GradientsEpisode 22: LLMs, OpenAI, and the Existential Crisis for Machine Learning EngineeringJeremy 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.
Jeremy Howard is co-founder of fast.ai, an ex-Chief Scientist at Kaggle, and creator of the ULMFiT approach on which all modern language models are based. Shreya Shankar is at UC Berkeley, ex Google brain, Facebook, and Viaduct. Hamel Husain has his own generative AI and LLM consultancy Parlance Labs and was previously at Outerbounds, Github, and Airbnb.
They...
2023-11-271h 20Vanishing GradientsEpisode 21: Deploying LLMs in Production: Lessons LearnedHugo speaks with Hamel Husain, a machine learning engineer who loves building machine learning infrastructure and tools 👷. Hamel leads and contributes to many popular open-source machine learning projects. He also has extensive experience (20+ years) as a machine learning engineer across various industries, including large tech companies like Airbnb and GitHub. At GitHub, he led CodeSearchNet, a large language model for semantic search that was a precursor to CoPilot. Hamel is the founder of Parlance-Labs, a research and consultancy focused on LLMs.
They talk about generative AI, large language models, the business value they can generate, and how to...
2023-11-141h 08Vanishing GradientsEpisode 20: Data Science: Past, Present, and FutureHugo 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.
Chris is an associate professor of applied mathematics at Columbia University and the New York Times’ chief data scientist, and Matthew is a professor of history at Princeton University and former Guggenheim Fellow.
From facial recognition to automated decision systems that inform who gets loans and who receives bail, we all now move through a world determined by data-empowered algorithms. These technologies didn’t just appe...
2023-10-051h 26Vanishing GradientsEpisode 19: Privacy and Security in Data Science and Machine LearningHugo 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. Previously, she has held numerous roles at large companies and startups in the US and Germany, implementing data processing and machine learning systems with a focus on reliability, testability, privacy, and security.
In this episode, Hugo and Katharine talk about
What data privacy and security are, what they aren’t and the differences between them (hopefully dispelling common misconceptions along the way!);
Wh...
2023-08-141h 23DataTalks.ClubData Developer Relations - Hugo Bowne-AndersonWe talked about:
Hugo's background
Why do tools and the companies that run them have wildly different names
Hugo's other projects beside Metaflow
Transitioning from educator to DevRel
What is DevRel?
DevRel vs Marketing
How DevRel coordinates with developers
How DevRel coordinates with marketers
What skills a DevRel needs
The challenges that come with being an educator
Becoming a good writer: nature vs nurture
Hugo's approach to writing and suggestions
Establishing a goal for your content
Choosing a form of media for your content
Is DevRel intercompany or intracompany?
The Vanishing Gradients podcast
Finding Hugo online
2023-06-1650 min
Cinefilia e Companhia#53 – Sangue negro, de Paul Thomas Anderson (e Top 3 atuações de Daniel Day-Lewis)O grande privilégio de falar a respeito de um dos melhores filmes do século XXI ficou para Hugo, Henrique e seu convidado especial: Willian de Andrade. O épico moderno de Paul Thomas Anderson é tratado aqui num longo e delicioso episódio que procura dar conta de tantas e tantas qualidades que podem ser percebidas ao longo do filme. No final, os participantes arriscam realizar um Top 3 de filmes protagonizados pelo icônico Daniel Day-Lewis.
Não deixe de dar a sua opinião sobre o episódio e participar da enquete. Queremos muito saber o que você...
2023-06-152h 24Vanishing GradientsEpisode 18: Research Data Science in BiotechHugo speaks with Eric Ma about Research Data Science in Biotech. Eric leads the Research team in the Data Science and Artificial Intelligence group at Moderna Therapeutics. Prior to that, he was part of a special ops data science team at the Novartis Institutes for Biomedical Research's Informatics department.
In this episode, Hugo and Eric talk about
What tools and techniques they use for drug discovery (such as mRNA vaccines and medicines);
The importance of machine learning, deep learning, and Bayesian inference;
How to think more generally about such high-dimensional, multi-objective optimization problems;
The importance of...
2023-05-251h 12
Sleepless CreativesTurnips and Talking Horses: Tales That Never Grow Old with Writer Josh Anderson-GreyDo you have any thoughts or ideas about the show? Send us a text! Hello Creatives,Step into a world of literary wonder as we mark our podcast's second anniversary with the launch of our guest reader series. Scriptwriter and radio presenter Josh Anderson-Grey takes the microphone, bringing his warm, expressive voice to a collection of timeless poetry and classic fairy tales.The journey begins with Victor Hugo's haunting "To Cruel Ocean," where waves whisper tales of the deep to those who dwell on shore. Emma Lazarus follows with her powerful me...
2023-02-2724 minVanishing GradientsEpisode 17: End-to-End Data ScienceHugo speaks with Tanya Cashorali, a data scientist and consultant that helps businesses get the most out of data, about what end-to-end data science looks like across many industries, such as retail, defense, biotech, and sports, including
scoping out projects,
figuring out the correct questions to ask,
how projects can change,
delivering on the promise,
the importance of rapid prototyping,
what it means to put models in production, and
how to measure success.
And much more, all the while grounding their conversation in real-world examples from data science, business, and life.
In a world where...
2023-02-171h 16Vanishing GradientsEpisode 16: Data Science and Decision Making Under UncertaintyHugo speaks with JD Long, agricultural economist, quant, and stochastic modeler, about decision making under uncertainty and how we can use our knowledge of risk, uncertainty, probabilistic thinking, causal inference, and more to help us use data science and machine learning to make better decisions in an uncertain world.
This is part 2 of a two part conversation in which we delve into decision making under uncertainty. Feel free to check out part 1 here but this episode should also stand alone.
Why am I speaking to JD about all of this? Because not only is he...
2022-12-141h 23Vanishing GradientsEpisode 15: Uncertainty, Risk, and Simulation in Data ScienceHugo speaks with JD Long, agricultural economist, quant, and stochastic modeler, about decision making under uncertainty and how we can use our knowledge of risk, uncertainty, probabilistic thinking, causal inference, and more to help us use data science and machine learning to make better decisions in an uncertain world.
This is part 1 of a two part conversation. In this, part 1, we discuss risk, uncertainty, probabilistic thinking, and simulation, all with a view towards improving decision making and we draw on examples from our personal lives, the pandemic, our jobs, the reinsurance space, and the corporate world. In...
2022-12-0753 minVanishing GradientsEpisode 14: Decision Science, MLOps, and Machine Learning EverywhereHugo Bowne-Anderson, host of Vanishing Gradients, reads 3 audio essays about decision science, MLOps, and what happens when machine learning models are everywhere.
Links
Our upcoming Vanishing Gradients live recording of Data Science and Decision Making Under Uncertainty with Hugo and JD Long!
Decision-Making in a Time of Crisis by Hugo Bowne-Anderson
MLOps and DevOps: Why Data Makes It Different by Ville Tuulos and Hugo Bowne-Anderson
The above essay syndicated on VentureBeat
When models are everywhere by Hugo Bowne-Anderson and Mike Loukides
2022-11-211h 09Vanishing GradientsEpisode 13: The Data Science Skills Gap, Economics, and Public HealthHugo speak with Norma Padron about data science education and continuous learning for people working in healthcare, broadly construed, along with how we can think about the democratization of data science skills more generally.
Norma is CEO of EmpiricaLab, where her team‘s mission is to bridge work and training and empower healthcare teams to focus on what they care about the most: patient care. In a word, EmpiricaLab is a platform focused on peer learning and last-mile training for healthcare teams.
As you’ll discover, Norma’s background is fascinating: with a Ph.D. in hea...
2022-10-121h 22
Crest SurfcastCrest Podcast Ep52 - Hugo TagholmWith more heat than ever on governments' approaches to clean oceans, sewage discharge, sustainability and plastic reduction, we catch up with one of the shining lights of surfing's ecological movements. Hugo Tagholm has decades of experience trying to hold power to account on behalf of the environment. Right as the SAS Safer Seas and Rivers app was in most headline bulletins for exposing the extent to which water companies actually use loopholes to pollute, Hugo spoke extenisvely with Rob and Tom (who'd also been asked to speak to the BBC the day before about the same story). Listen as...
2022-10-041h 15Vanishing GradientsEpisode 12: Data Science for Social Media: Twitter and RedditHugo speakswith Katie Bauer about her time working in data science at both Twitter and Reddit. At the time of recording, Katie was a data science manager at Twitter and prior to that, a founding member of the data team at Reddit. She’s now Head of Data Science at Gloss Genius so congrats on the new job, Katie!
In this conversation, we dive into what type of challenges social media companies face that data science is equipped to solve: in doing so, we traverse
the difference and similarities in companies such as Twitter and Reddit,
th...
2022-09-301h 32Vanishing GradientsEpisode 11: Data Science: The Great StagnationHugo speaks with Mark Saroufim, an Applied AI Engineer at Meta who works on PyTorch where his team’s main focus is making it as easy as possible for people to deploy PyTorch in production outside Meta.
Mark first came on our radar with an essay he wrote called Machine Learning: the Great Stagnation, which was concerned with the stagnation in machine learning in academic research and in which he stated
Machine learning researchers can now engage in risk-free, high-income, high-prestige work. They are today’s Medieval Catholic priests.
This is just the tip...
2022-09-161h 45
Pipeline ConversationsBuilding MLOps Tools with OuterboundsThis week I spoke with Savin Goyal and Hugo Bowne-Anderson from Outerbounds. They both work on leading, building and helping people put models into production through Metaflow, and I'm sure current users of ZenML will find this conversation interesting to hear how they think through the broader questions and engineering problems involved with MLOps.
Above all, we spoke about the challenges involved in building a tool that handles the whole machine learning story, from collecting data to training models, to deployment and back again. In many ways it's great that there are lots of smart people thinking...
2022-08-2259 minVanishing GradientsEpisode 10: Investing in Machine LearningHugo speaks with Sarah Catanzaro, General Partner at Amplify Partners, about investing in data science and machine learning tooling and where we see progress happening in the space.
Sarah invests in the tools that we both wish we had earlier in our careers: tools that enable data scientists and machine learners to collect, store, manage, analyze, and model data more effectively. As you’ll discover, Sarah identifies as a scientist first and an investor second and still believes that her mission is to enable companies to become data-driven and to generate ROI through machine and statistical learning. In...
2022-08-181h 26Vanishing Gradients9: AutoML, Literate Programming, and Data Tooling Cargo CultsHugo speaks with Hamel Husain, Head of Data Science at Outerbounds, with extensive experience in data science consulting, at DataRobot, Airbnb, and Github.
In this conversation, they talk about Hamel's early days in data science, consulting for a wide array of companies, such as Crocs, restaurants, and casinos in Las Vegas, diving into what data science even looked like in 2005 and how you could think about delivering business value using data and analytics back then.
They talk about his trajectory in moving to data science and machine learning in Silicon Valley, what his expectations were...
2022-07-191h 41Vanishing GradientsEpisode 8: The Open Source Cybernetic RevolutionHugo speaks with Peter Wang, CEO of Anaconda, about what the value proposition of data science actually is, data not as the new oil, but rather data as toxic, nuclear sludge, the fact that data isn’t real (and what we really have are frozen models), and the future promise of data science.
They also dive into an experimental conversation around open source software development as a model for the development of human civilization, in the context of developing systems that prize local generativity over global extractive principles. If that’s a mouthful, which it was, or an e...
2022-05-161h 05
Pop culture cinéWes AndersonDans ce podcast vous en apprendrez plus sur le réalisateur Wes Anderson."Sappheiros - Embrace" est sous licence Creative Commons (cc-by)Musique promue par BreakingCopyright: https://bit.ly/sappheiros-embrace Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.
2022-05-0908 minVanishing GradientsEpisode 7: The Evolution of Python for Data ScienceHugo speaks with Peter Wang, CEO of Anaconda, about how Python became so big in data science, machine learning, and AI. They jump into many of the technical and sociological beginnings of Python being used for data science, a history of PyData, the conda distribution, and NUMFOCUS.
They also talk about the emergence of online collaborative environments, particularly with respect to open source, and attempt to figure out the movings parts of PyData and why it has had the impact it has, including the fact that many core developers were not computer scientists or software engineers, but...
2022-05-011h 02Vanishing GradientsEpisode 6: Bullshit Jobs in Data Science (and what to do about them)Hugo speaks with Jacqueline Nolis, Chief Product Officer at Saturn Cloud (formerly Head of Data Science), about all types of failure modes in data science, ML, and AI, and they delve into bullshit jobs in data science (yes, that’s a technical term, as you’ll find out) –they discuss the elements that are bullshit, the elements that aren’t, and how to increase the ratio of the latter to the former.
They also talk about her journey in moving from mainly working in prescriptive analytics building reports in PDFs and power points to deploying machine learning products...
2022-04-041h 27Vanishing GradientsEpisode 5: Executive Data ScienceHugo speaks with Jim Savage, the Director of Data Science at Schmidt Futures, about the need for data science in executive training and decision, what data scientists can learn from economists, the perils of "data for good", and why you should always be integrating your loss function over your posterior.
Jim and Hugo talk about what data science is and isn’t capable of, what can actually deliver value, and what people really enjoy doing: the intersection in this Venn diagram is where we need to focus energy and it may not be quite what you think it...
2022-03-231h 48Vanishing GradientsEpisode 4: Machine Learning at T-MobileHugo speaks with Heather Nolis, Principal Machine Learning engineer at T-mobile, about what data science, machine learning, and AI look like at T-mobile, along with Heather’s path from a software development intern there to principal ML engineer running a team of 15.
They talk about: how to build a DS culture from scratch and what executive-level support looks like, as well as how to demonstrate machine learning value early on from a shark tank style pitch night to the initial investment through to the POC and building out the function; all the great work they do with R...
2022-03-101h 44Vanishing GradientsEpisode 3: Language Tech For AllRachael Tatman is a senior developer advocate for Rasa, where she’s helping developers build and deploy ML chatbots using their open source framework.
Rachael has a PhD in Linguistics from the University of Washington where her research was on computational sociolinguistics, or how our social identity affects the way we use language in computational contexts. Previously she was a data scientist at Kaggle and she’s still a Kaggle Grandmaster.
In this conversation, Rachael and I talk about the history of NLP and conversational AI//chatbots and we dive into the fascinating tension between rule...
2022-03-011h 32Vanishing GradientsEpisode 2: Making Data Science Uncool AgainJeremy Howard is a data scientist, researcher, developer, educator, and entrepreneur. Jeremy is a founding researcher at fast.ai, a research institute dedicated to making deep learning more accessible. He is also a Distinguished Research Scientist at the University of San Francisco, the chair of WAMRI, and is Chief Scientist at platform.ai.
In this conversation, we’ll be talking about the history of data science, machine learning, and AI, where we’ve come from and where we’re going, how new techniques can be applied to real-world problems, whether it be deep learning to medicine or portin...
2022-02-211h 45
Vanishing GradientsEpisode 1: Introducing Vanishing GradientsIn 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!
2022-02-1605 min
Screen Speak#34 - The MatrixThe Matrix is a 1999 science fiction action film written and directed by the Wachowskis. It stars Keanu Reeves, Laurence Fishburne, Carrie-Anne Moss, Hugo Weaving, and Joe Pantoliano. It depicts a dystopian future in which humanity is unknowingly trapped inside a simulated reality, the Matrix, which intelligent machines have created to distract humans while using their bodies as an energy source.When computer programmer Thomas Anderson, under the hacker alias "Neo", uncovers the truth, he is drawn into a rebellion against the machines, along with other people who have been freed from the Matrix.
2021-12-031h 24
Back on the BusHugo HouleWhat a great chat we had with our man Hugo Houle. Hugo made a big impression on both Randy and me back in 2011 when he was 20 years old as he had a level of professionalism that stood out for someone of that age. We always knew he would make it to the world tour but he has become such an amazing rider in the super domestique role. He's found his niche in the sport and is one of the best in the business at helping others win. In our discussion, Hugo describes his progression over the years and the...
2021-09-011h 03
Turn the Lens with Jeff FrickHugo Bowne-Anderson: Data Scientists, Evangelists, Easy Button | Turn the Lens #15I always enjoy a look into the lives and activities of those fortunate professionals who carry the title of 'Evangelist.' Hugo Bowne-Anderson, Head of Data Science Evangelism and Marketing for Coiled joined me from the future, Sydney, Australia for a conversation on all things Coiled, Dask, and the Pythonic ecosystem. Hugo shares a unique perspective, having been a practicing data scientist in the world of molecular cell biology, as well as an instructor, developing and delivering online interactive data sciences classes that have been enjoyed by over half a million learners. A big part of Hugo's...
2021-08-0727 min
Remember the FilmEp. 14 - Boogie Nights and Other Paul Thomas Anderson FilmsOur Film to Remember this week was one of Josh's favorites from one of his favorite directors, Boogie Nights (1997), directed by Paul Thomas Anderson. After talking about Boogie Nights we then discuss the rest of PTA's filmography and what we like or even sometimes don't like about his movies. Next week we are talking Mark Wahlberg and watching The Departed!
2021-01-311h 49
We Believe.Silent Night (Cover by Aimee Hugo and Michael Anderson)Silent Night
Sung by Aimee Hugo
Arranged by Michael Anderson
2021-01-2004 min
Cuenta cuentosCuento: El leve Pedro. Autor: Enrique Anderson Imbert.En esta ocasión compartimos la historia del leve Pedro, del autor argentino Enrique Anderson Imbert.
2020-11-3008 min
The English RoomEleições dos EUA explicadasNesse episódio iremos conversar principalmente em inglês sobre a o sistema de eleição dos EUA. Vamos entender quais são os critérios para alguém ganhar uma eleição lá e comparar com o sistema brasileiro. É uma ótima chance de treinar seu listening!
Ajude a nossa campanha para construir um curso gratuito em nosso site apoia.se/noportuguesehere (doações a partir de 5 reais)
Wanna go to our online meetings? t.me/thenglishroom
Nosso Meetup: https://www.meetup.com/The-English-Room/
Ouça também ao Pod...
2020-11-1043 min
COVID Coffee Chats @UCalgaryEpisode 3: Reimagining experiential learning with Ron HugoIn this episode, Ron Hugo, professor in the department of mechanical and manufacturing engineering, talks about the challenges of getting to know and connect with students in online learning. He shares with us how he has continued experiential learning in the distance learning format by creating individual at home lab kits for his 217 students. Through prototyping his experiments, researching the history of other individuals, and integrating the history of heat transfer into his lab manuals, he has developed a more holistic perspective of his subject. He chats about how this experience has provided a greater appreciation for being in f...
2020-11-0422 min
The English RoomSuperando obstáculos no aprendizado de idiomas (live compilation)Quer fazer aula de inglês personalizada: 11 98786-9152
Confira também nosso canal no Youtube:
9 razões para aprender sem traduzir: https://youtu.be/eyb-HMHRtQ8
Ajude o canal a crescer tornando-se um apoiador oficial: apoia.se/noportuguese
Participe do nosso grupo de WhatsApp e encontros gratuitos de conversação: https://chat.whatsapp.com/LdspoCb3ZpP6pqjX80hCfS
Nosso Grupo de Conversação no Telegram: https://t.me/noportuguesehere
Thanks for listening
Um agradecimento especial aos nossos apoiado...
2020-10-2851 min
MLOps.communityMLOps Coffee Sessions #14 Conversation with the Creators of Dask // Hugo Bowne-Anderson and Matthew RocklinJoin the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletterDaskWhat is it?Parallelism for analyticsWhat is parallelism?Doing a lot at once by splitting tasks into smaller subtasks, which can be processed in parallel (at the same time)Distributed work across multiple machines and then combined the resultsHelpful for CPU-bound - doing a bunch of calculations on the CPU. The rate at which the process progresses is limited by the speed of the CPUConcurrency?Similar a but things don’t have to happen at the same time, they can happen asynchronously. They can overlap.Shared stateHelpful to I/O bound - networking, reading from disk, etc. The rate at which a process progresses is limited by the speed of the I...
2020-10-1256 min
GametalksVictor Hugo "Buiu" e a vida dupla de caster e organizador de campeonatos de e-sportsNo episódio desta semana conversei com o Victor Hugo "Buiu", gerente de projetos do Kombat Klub e caster de campeonatos online. Buiu me falou sobre a paixão desses jogos, a vida de organizador e narrador ao mesmo tempo, seus maiores orgulhos e a comunidade que se ergueu para profissionalizar os campeonatos de fighting games.
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Se você gostou deste episódio, deixe um review e 5 estrelas lá no iTunes! Isso ajuda um bocado o Gametalks a alcançar mais pessoas! https://ratethispodcast.com/gametalks
Siga o Gametalks na Twitch para acompanhar as gra...
2020-07-1037 min
La Roue LibreLe Face à FaceLe Face à Face de La Roue Libre c'est Jules Tarla et Hugo Ferraro qui confrontent leurs opinions sur deux sujets : "Se péter le bide à table" et "Claude François".
Auteurs : Hugo Ferraro et Jules Tarla
Interprètes : Hugo Ferraro et Jules Tarla
Montage : Jules Tarla
Jingle La Roue Libre, DrGasm
Extraits :
"Magnolias for Ever", Etienne Roda-Gil
"Le téléphone pleure", Frank Thomas
"Je vais à Rio", Eddy Marnay / Adrienne Anderson / Peter Al
2020-05-1800 min
Indulge In The Thought-Provoking Full Audiobook Now, Thriller Fans!Les Misérables: Penguin Classics by Victor HugoPlease visithttps://thebookvoice.com/podcasts/1/audiobook/385562to listen full audiobooks.
Title: Les Misérables: Penguin Classics
Author: Victor Hugo
Narrator: John Owen-Jones, Adeel Akhtar, Adrian Scarborough, Natalie Simpson, Emma Fielding
Format: Unabridged Audiobook
Length: 65 hours 41 minutes
Release date: April 23, 2020
Ratings: Ratings of Book: 5 of Total 8
Ratings of Narrator: 5 of Total 3
Genres: LGBTQ+
Publisher's Summary:
Brought to you by Penguin. This Penguin Classic is performed by an ensemble cast which includes the BAFTA award-winning actor Adeel Akhtar (Killing Eve; The Night Manager; Les Miserables), Adrian Scarborough (Gavin and Stacey; The King's Speech), Natalie Simpson (Outlander; Les Miserables), Emma Fielding (Unforgotten; Les M...
2020-04-235h 41
Papo Com Helal7 - HUGO KERTH: uma conversa sobre arte, criação, teatro e fotografiaNo encontro de hoje, o ator e professor de canto Hugo Kerth (@hugokerth), faz uma análise da sua carreira em relação a arte, teatro e criação, revelando fatos importantes e trazendo conselhos para os artistas dessa nova geração. Gravado em seu estúdio, a conversa também revela um pouco dos bastidores do primeiro ensaio fotográfico externo que o Hugo fez, comigo, em 2018. Aperta o play!
2020-03-2244 min
IBM thinkLeadersPromoting AI literacy w/ Hugo Bowne-Anderson of DataCampHow can we better promote AI literacy? What skills are commonly lacking in organizations? Are new people entering the field considering bias in AI?
In this episode of IBM thinkLeaders podcast, we are joined by guest Hugo Bowne-Anderson (Data Scientist at DataCamp) to discuss how we can better promote AI and digital skills. We talk to Hugo about the skills that people often overlook, how to build out successful teams, and how new people interested in AI can overcome hesitations.
Connect with us @IBMthinkLeaders (#thinkLeaders) & our guest at:
@hugobowne
@DataCamp
2020-03-1914 min