HockeyStick Show Miko Pawlikowski

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

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

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

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

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

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