AI in Education: From Micro-Courses to Rigorous Training Programs - ML 162

In this week's episode, Michael and Ben sit down with Artem Koren, Chief Product Officer at Sembly AI, to explore the future of AI integration in the workplace. We'll delve into Sembly AI's mission to accelerate team efficiency through powerful AI tools—imagine an Iron Man suit for your daily tasks. From proactive AI assisting with time-consuming tasks to ethical considerations in data privacy, this episode covers the cutting-edge developments and challenges in AI implementation.They also discuss the evolving landscape of workplace automation, the intricacies of data collection, and the balance between privacy and productivity. They also highlight Sembly's latest advancements like Semblian 2.0, a breakthrough in digital twin technology that promises to redefine meeting productivity. Join them for an in-depth conversation on AI's transformative potential, the ethical responsibilities it entails, and the practical impacts on the project. LinksSemblian 2.0SocialsLinkedIn: Artem KorenBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

10 Loka 202459min

In today's episode, Michael is joined by Hikari Senju the Founder and CEO at Omneky. He starts by discussing how he built Omneky, an AI-Driven Marketing Platform. They dive into Hikari's approach to working with customers on brand strategy and content. They also talk about the increasing importance of brands in a digital, AI-driven world. Additionally, they tackle Hikari's perspective on how generative AI will impact the advertising industry. Tune in on how ML is Reshaping The Advertising Industry.SocialsLinkedIn: Hikari SenjuBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

3 Loka 20241h 1min

Today, Ben and Michael dive into a compelling discussion on the intricate dance between challenges, feedback, mentorship, and growth in the field of software development. In this episode, Michael shares their journey of overcoming the pains of independent problem-solving before receiving effective guidance. As we explore their experiences with Ben, they uncover the vital importance of openness to feedback and the profound value of peer review in refining solutions.They delve into technical aspects, including Python's Pytest framework for unit tests and the delicate balance between complexity and simplicity in testing for maintainability and readability. Additionally, they touch on Michael's hands-on learning curve, tackling unfamiliar concepts such as RAG, embeddings, LLMs, and Git development, all while managing significant time constraints and social commitments.Moreover, Ben shares his mentorship philosophy, likening it to military training—pushing mentees to their limits without prior warning to foster resilience and self-improvement. They also discuss the importance of documentation, bug bashes, and the fine art of balancing integration and unit tests to ensure robust and thorough software.Join them as they explore the journey from initial struggle to increased autonomy and confidence, using real-world examples of testing gaps, code complexities, and the powerful impact of daily feedback. Whether you're a seasoned developer or just starting your tech career, this episode is packed with valuable insights to enhance your learning and development process. So, stay tuned and dive right in!Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

26 Syys 20241h 6min

Michael Berk dives deep into the adventures of AI and machine learning with our special guest, Richmond Alake, a staff developer advocate at MongoDB. Richmond's journey from web development to AI was driven by a quest for excitement and new challenges. In this episode, he shares how he transitioned into the AI field, his passion for using writing as a learning tool, and the importance of continuous learning in evolving tech landscapes.They explore the intricacies of building and evaluating Retrieval-Augmented Generation (RAG) systems, the benefits of MongoDB's versatile database functionalities, and the pressing challenges in machine learning data collection and evaluation. Richmond also gives us a peek into MongoDB's advanced solutions for AI application development and how strategic data chunking can impact efficiency.Whether you're a budding AI enthusiast or an experienced developer looking to expand your horizons, this episode is packed with practical advice, career insights, and the latest trends in AI and machine learning. Stay tuned as we uncover how to navigate the complexity of RAG pipelines and the evolving landscape of generative AI. Let's get started!SocialsLinkedIn: Richmond AlakeBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

19 Syys 20241h 3min

Today, we have a special guest Abi Aryan, an accomplished founder of Abide AI and a seasoned expert in machine learning. Joining us are your hosts, Michael Berk and Ben Wilson, who bring a wealth of experience from Databricks.In this episode, Ben shares his journey navigating the intricacies of deep learning and the surprising effectiveness of simpler solutions over complex algorithms. Abi lends her insights to the balancing act between innovation and practicality in tech adoption, influenced by career stability and venture capital demands. They also explore Abi's passion for recommender systems and audio speech synthesis, and the potential these fields hold for e-commerce and inclusivity.Abi also gives us a glimpse into her research methodology, her approach to autonomous agents, and the challenges she faced with bias and imposter syndrome. As they dissect consulting strategies, experiment design, and the art of fostering a collaborative environment, this episode is packed with valuable lessons for any tech enthusiast.So, get ready to tune in, take notes, and be inspired by the fascinating stories and insights from our expert guest and hosts.SocialsAbi AryanLinkedIn: Abi AryanBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

12 Syys 20241h 7min

Today, host Michael Berk and Ben Wilson dive deep into the multifaceted world of software engineering and data science with their insightful guest, Sandy Ryza a lead engineer from Dagster Labs. In this episode, they explore a range of intriguing topics, from the impact of the broken windows theory on code quality to the delicate balance of maintaining backward compatibility in evolving software projects. Sandy talks about the challenges and learnings in transitioning from data science back to software engineering, including dependency management and designing for diverse use cases. They touch on the importance of clear naming conventions, tooling, and infrastructure enforcement to maintain high code quality. Plus, they discuss the intricate process of selecting and managing Python libraries, the satisfaction of refactoring old code, and the necessity of balancing new feature development with stability.Michael and Ben will guide us through these essential discussions, emphasizing the significance of user-centric API design and the benefits of open source software. They also get practical advice on navigating API changes and managing dependencies effectively, with real-world examples from Dagster, Spark Time Series, and the libraries Numba and Pydantic.Join them for an episode packed with valuable insights and strategies for becoming a top-end developer! Don’t forget to follow Sandy on Twitter and check out Dagster.io for more information on his work.SocialsLinkedIn: Sandy RyzaBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

29 Elo 202459min

In today's episode, Ben and Michael dive deep into the intricacies of software development, innovation, and team dynamics. This episode explores the critical balance between building in-house tools versus leveraging open-source solutions, with real-world examples from Databricks.They discuss the creation and eventual abandonment of a benchmarking tool for warehouses and discuss the importance of evaluating user demand, effort, and impact before committing to development. They emphasize the role of empathy, constructive feedback, and team collaboration in driving successful projects. They share strategies to influence behavior within organizations, the significance of a blame-free culture, and the art of leading difficult conversations with stakeholders.From detailed discussions on customer feedback loops to practical advice on automating mundane tasks, this episode is packed with insights that will help you navigate the complex landscape of software development. So sit back, relax, and join us for a thoughtful and engaging conversation on how to turn challenges into opportunities for growth and innovation.SocialsLinkedIn: Michael berkLinkedIn: Benjamin WilsonBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

22 Elo 20241h 5min