HockeyStick Show

Hosted by Miko Pawlikowski

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Aug 2024

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About the show

Explore the moments leading to exponential growth in technology, business, science and more.

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20 recent

August 26, 202419 min

Mastering MLOps - Maria Vechtomova - HockeyStick #20

Mastering MLOps with Maria: Insights and Future Trends Join us for an in-depth conversation with Maria, a leading expert in MLOps, as she shares her journey and insights into the world of machine learning operations. Maria discusses the common misconceptions about MLOps, the integration of DevOps practices, and the tools and frameworks that have shaped her career. Discover her unique approach to MLOps, the challenges faced by data science teams, and the evolution of the field. Maria also introduces her new course on MLOps with Databricks, aimed at helping practitioners deepen their skills. Don't miss this episode for valuable advice and a peek into the future of MLOps! 0:00 Intro 0:31 Marvel and Lego: A Personal Touch 1:12 Journey into MLOps 02:09 The Evolution of MLOps 04:38 Challenges and Best Practices in MLOps 06:38 MLOps vs. DevOps 08:10 LLM Monitoring and Prompt Engineering 10:02 Advice for MLOps Practitioners 13:15 Marvelous MLOps: The Blog and Course 17:53 Final Thoughts and Career Advice 19:21 Conclusion and Farewell

August 12, 202450 min

Hacking Life & AI - Harpreet Sahota - HS#19

Harpreet Sahota on Becoming a Hacker in Residence & AI Innovation: Chat with Miko Pawlikowski Join Miko Pawlikowski on HockeyStick as he interviews Harpreet Sahota, Voxel51's Hacker in Residence and a prominent figure in the AI community. Harpreet shares his journey from studying math and stats to becoming a biostatistician and data scientist, eventually taking on his current role. They discuss what it means to be a Hacker in Residence, the importance of Voxel51's open-source library in the AI industry, and Harpreet's upcoming book on Practical Retrieval Augmentation Generation. Harpreet also delves into his experiences with LinkedIn courses, his extensive podcasting history, and advice for aspiring AI professionals. Tune in to learn about the intricate balance of responsibilities in Harpreet's role, from creating educational content to exploring novel AI applications. 00:00 Meet Harpreet Sahota: Hacker in Residence 01:25 Role and Responsibilities at Voxel51 04:59 Journey to Becoming a Hacker in Residence 10:44 Challenges and Rewards of the Role 15:07 Writing a Book on Retrieval Augmented Generation 23:12 Creating LinkedIn Learning Courses 28:17 Balancing Work and Family Life 28:42 Recording Courses from Home 28:56 Choosing Not to Be On-Screen 29:23 Writing and Newsletters 31:07 Industry Events and Conferences 35:00 Traveling for Work 36:10 The Harpreet Podcast 41:59 Future Plans and Building a Dream House 44:25 Final Thoughts and Reflections 45:33 Advice for Aspiring Professionals

August 5, 202451 min

Simplifying Algorithms - Vadim Smolyakov - HS#18

Simplifying Algorithms with Vadim Smolyakov! Get Vadim's book 45% OFF with code hockeystick24 here: https://mng.bz/4J5Q Join Miko Pawlikowski on HockeyStick as he discusses machine learning algorithms with Vadim Smolyakov, author of 'Machine Learning Algorithms in Depth.' They explore Vadim's experiences at MIT CSAIL, his work at Microsoft, and key machine learning concepts like Bayesian nonparametrics, decision trees, and Markov chain Monte Carlo methods. Vadim also shares insights on his book, the challenges in implementing ML algorithms, and predictions about the future of AI. This episode is perfect for intermediate learners and those new to machine learning. 0:00 Guest Introduction: Vadim Smolyakov 00:48 MIT CSAIL Experience 01:28 Bayesian Inference and Non-Parametrics 02:30 Vadim's Work at Microsoft 03:14 The Origin of Vadim's Book 06:41 Target Audience for the Book 08:04 Explaining Bayesian Algorithms 15:57 Supervised vs Unsupervised Learning 19:22 Decision Trees and Random Forests 24:42 Challenges in Implementing ML Algorithms 31:32 Top Machine Learning Algorithms 45:27 Future of AI and ML 50:31 Conclusion and Farewell

July 29, 202438 min

From Windsurfing to AI Meetups - Matt Carey - HS#17

Matt Carey's AI Journey: From Windsurfing to London’s AI Meetups Join Miko Pawlikowski on HockeyStick as he chats with Matt Carey, an AI engineer at StackOne, AWS Community Builder, organizer of AI Demo Days, and OpenUK AI Advisory Board member. In this episode, Matt shares his unique path from competitive windsurfing to AI engineering, the challenges of transitioning from outdoor sports to indoor coding, and his passion for building a strong AI community in London. They delve into the vibrant AI scene in London, the importance of open-source advocacy, and the exciting innovations happening in Web AI and browser-based LLMs. Matt provides insights into his work with StackOne and offers advice for aspiring AI engineers and startup enthusiasts. 0:00 Introduction to the Episode 0:39 Matt Carey's Windsurfing Journey 1:58 Transition from Windsurfing to AI 4:34 AI Scene in London 5:21 AI Demo Days and Meetups 10:42 AWS Community Builder Experience 14:58 OpenUK AI Advisory Board 18:02 Exciting Innovations in the London Startup Scene 25:51 Navigating Funding and Incubators in London 26:30 Influential Figures and Cool Projects to Follow 28:56 The Role of AI Engineers at StackOne 33:09 The Fun and Chaos of Tech Twitter

July 22, 202448 min

Quantum Computing in Action - Johan Vos - HS#16

Exploring Quantum Computing with Johan Vos! Get Johan's book 45% OFF with code hockeystick24 here: https://mng.bz/v8da Join Miko Pawlikowski on HockeyStick as he delves into the fascinating world of quantum computing with Johan Vos, author of "Quantum Computing in Action" and co-founder of Gluon. Discover what makes quantum computing special, its implications for future technology, potential impacts on security, and how to future-proof your career in a quantum-driven world. Johan explains complex concepts like superposition and entanglement in simple terms and discusses real-world applications and the future of quantum hardware. Don't miss this comprehensive guide to understanding the next big leap in computing! 0:00 What Makes Quantum Computing Special? 1:49 Quantum Computing vs Classical Computing 4:17 Real-World Applications of Quantum Computing 6:25 Understanding Qubits and Superposition 10:02 Quantum Entanglement Explained 13:54 Quantum Computing Hardware and Simulators 26:06 Programming Quantum Computers 42:38 Future of Quantum Computing 48:00 Conclusion and Final Thoughts

July 15, 202441 min

Software Engineering Managers - Akanksha Gupta - HS#15

Think Like a Software Engineering Manager - insights with Akanksha Gupta Get her book 45% OFF with code hockeystick24 here: https://mng.bz/v8va Join Miko Pawlikowski on this episode of HockeyStick as he delves into the world of software engineering management with Akanksha Gupta, author of "Think Like a Software Engineering Manager". Explore Akanksha's journey from software engineer to engineering manager and gather valuable insights on making the transition, thriving in the role, and avoiding common pitfalls. Learn about essential skills such as delegation, career discussions, and maintaining team morale, along with practical strategies for hiring, managing attrition, and personal growth. 0:00 Intro 0:24 Meet Akanksha Gupta: Author and Engineering Manager 1:09 The Journey from Engineer to Manager 1:34 Writing the Book: Inspiration and Challenges 4:31 Deciding to Transition: Promotion vs. Lateral Move 9:09 Navigating the People Aspect of Management 15:19 Key Traits of a Good Engineering Manager 34:52 Continuous Learning and Self-Growth 40:00 Final Advice for Aspiring Engineering Managers

July 13, 20241 hr 4 min

Robo Advisors - Rob Reider & Alex Michalka - HS#14

Exploring Robo Advisors with Python Experts: Rob Reider & Alex Michalka Get their book 45% OFF with code hockeystick24 here: https://mng.bz/ngjd Join Miko Pawlikowski on this episode of HockeyStick as he dives into the world of robo advisors with industry heavyweights Rob Reider and Alex Michalka, authors of "Build a Robo Advisor with Python from Scratch". Discover their fascinating career paths from hedge funds to robo advising, the intricacies of Python programming for finance, and the evolution of financial planning and optimization techniques. Gain insights into asset allocation, tax-loss harvesting, Monte Carlo simulations, reinforcement learning, and the future of robo advising. An essential watch for anyone interested in the intersection of finance and technology! 0:00 Introduction to Robo Advisors 0:50 Rob Reider's Career Journey 01:40 Quantopian and the Love for Python 04:19 The Birth of a Book Collaboration 05:11 Alex's Journey and Weather Derivatives 08:08 Understanding Hedge Funds vs. Robo Advisors 11:13 The Rise of Robo Advisors 17:30 Tax Efficiency and Asset Allocation 24:51 Target Audience and Book Insights 28:21 Monte Carlo Simulations Explained 31:15 Monte Carlo Simulations Explained 32:01 Applications of Monte Carlo Simulations 33:34 Introduction to AI and Reinforcement Learning 35:25 Reinforcement Learning in Finance 39:38 The Power of Python in Finance 42:23 Challenges in Measuring Returns 1:01:35 Conclusion and Final Thoughts

June 21, 20241 hr 1 min

LLMOps, Large Language Models in Production - HS#13

Understanding LLMOps: Differentiating from MLOps with Abi Aryan Join Miko Pawlikowski on this episode of HockeyStick as he interviews Abi Aryan, a leading expert and author on Large Language Model Operations (LLMOps), to distinguish it from Machine Learning Operations (MLOps) and Machine Learning Engineering (MLE). Abi delves into the challenges and unique requirements of managing generative models in production, discusses the evolution and future of LLMOps, and shares insights into her upcoming book, 'LLMOps: Managing Large Language Models in Production.' Gain understanding on safety, scalability, robustness, and the lifecycle of LLMs, and learn practical steps to effectively deploy and monitor these advanced models. 00:00 Introduction 1:11 Generative vs. Discriminative Models 1:58 Challenges in LLMOps 2:12 The Shift to Task-Agnostic Software 2:50 Fine-Tuning and Prompt Engineering 4:37 The Origin of LLMOps 13:20 Safety, Scalability, and Robustness in LLMOps 29:40 Dynamic Model Adaptation 30:37 Challenges of Static Models 31:42 Improving Model Performance 32:20 Introducing a New Framework 34:06 Lifecycle of an LLM in Production 35:29 Data Engineering and Evaluation 37:06 Orchestration and Security 47:51 Future Predictions and Concerns 48:46 Impact on Jobs and Society 55:06 Risks and Ethical Considerations 59:11 Industry Trends and Monopolies 01:00:52 Conclusion and Contact Information

June 17, 202443 min

AI-Assisted Testing - HS#12

AI Impact on Software Testing: Expert Insights with Mark Winteringham Get Mark's book 20% OFF with code hockeystick24 here: https://mng.bz/oeWD In this episode of Hockey Stick, host Miko Pawlikowski welcomes Mark Winteringham, author of 'AI Assisted Testing,' to discuss the impact of generative AI on software testing. They explore the efficacy of AI in writing tests, the future of software testing jobs, and the diverse roles within the testing profession. Mark provides his insights and experiences from 15 years in the industry, shares the concept of exploratory testing, and discusses the practical applications and limitations of AI tools in the testing landscape. Key takeaways include the importance of empathy, critical thinking, and collaboration in testing, as well as how to effectively use AI tools for specific tasks. Tune in for an in-depth conversation on the evolving world of software testing. 00:00 Introduction to AI in Software Testing 00:17 Meet Mark Winteringham: A Journey into Software Testing 00:46 The Role and Daily Life of a Software Tester 14:01 Exploring the Impact of AI on Software Testing 17:35 Generative AI: Opportunities and Challenges 20:53 Practical Use Cases for AI in Testing 39:14 The Future of AI in Software Testing 42:02 Conclusion and Final Thoughts

June 10, 202453 min

HockeyStick #11 - MLOps essentials

The Essentials of MLOps: With Eric Riddoch Join Miko Pawlikowski as he dives into the world of MLOps with Eric Riddoch, a machine learning platform engineer and MLOps practitioner. In this episode, they discuss the differences between MLOps, DevOps, and platform engineering, tools and practices in MLOps, as well as Eric's journey into the field from studying applied math to becoming an MLOps expert. They explore automated workflows, experiment tracking, model serving, and monitoring, while considering the evolving landscape of MLOps and the challenges of integrating various tools. Tune in for an in-depth look at the technical and non-technical aspects of MLOps, and learn why this field is critical and exciting. 00:00 Introduction to MLOps 01:20 Eric Riddoch's Journey into MLOps 08:12 The Emergence of MLOps 10:23 Comparing MLOps and DevOps 10:53 Challenges in MLOps 21:15 Tools and MLOps Maturity 25:57 Building an ML Platform with Orchestrators 26:35 Experiment Tracking and Model Performance 27:08 ML Flow and Alternatives 29:18 Serving Models with BentoML 31:49 Challenges with SageMaker and GPU Quotas 32:54 Monitoring Tools and Their Limitations 36:48 The PyTorch vs TensorFlow Debate 42:41 Challenges in MLOps Roles and Leadership 50:42 Advice for Aspiring MLOps Engineers