Navigating Build vs. Buy Decisions in Emerging AI Technologies - ML 180

Adventures in Machine Learning

#Tech #Careers #Business #Machine Learning #Artificial Intelligence #Data Analysis #Data Science #Podcasting Education #Ben Wilson, Michael Berk #Ben Wilsons #Michael Berk

27:28

Chris Nowinski is a former football player at Harvard University and professional wrestler with WWE, World Wrestling Entertainment. After enduring a career-ending head injury, Chris has dedicated his professional life to serving patients and families affected by brain trauma, particularly Chronic traumatic encephalopathy, or CTE, a progressive neurodegenerative disease that develops after repeated head injuries. Jay and Chris discuss the state of head injuries in American athletics, the difference between advocating for head safety at youth and professional levels, Chris’ newest research, and much more. Episode Chapters (00:00) Intro (00:50) changes in the culture around concussions in the past two decades (02:39) padded helmet technology (03:55) concussion reporting in the NFL (10:35) Chris’ career path and concussion history (14:52) connecting with activists who haven’t themselves suffered a traumatic brain injury (17:42) SHAAKE - a new sign to identify concussions (20:53) Unions can help players advocate for safety policies (23:10) final thoughts and goodbye For video episodes, watch on www.youtube.com/@therudermanfamilyfoundation Stay in touch: X: @JayRuderman | @RudermanFdn LinkedIn: Jay Ruderman | Ruderman Family Foundation Instagram: All About Change Podcast | Ruderman Family Foundation To learn more about the podcast, visit https://allaboutchangepodcast.com/…

for ca. et år siden 31:58

MP3•Episode hjem

In today's episode, we dive into the critical decision-making process of building versus buying technology solutions, especially when it comes to agentic logic-based frameworks. With the industry still in its early stages, I recommend waiting for managed solutions to mature, while Ben suggests the educational value of simple project builds. They discuss the importance of understanding the technology thoroughly before diving into business-focused decisions, using tools like customer user journeys (CUJs) to evaluate scalability, cost-efficiency, and maintainability. They also highlight some initial challenges and missteps in project management and the necessity for pre-evaluation by tech teams.
For non-technical teams engaged in technical projects, they provide structured guidance on navigating these unknowns efficiently. Additionally, they emphasize the value of research spikes and incremental development to manage risk and learn from user behavior. Finally, they explore the promising yet evolving landscape of generative AI and its potential high ROI with Retrieval-Augmented Generation (RAG).
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208 episoder

Adventures in Machine Learning

Navigating Build vs. Buy Decisions in Emerging AI Technologies - ML 180

Adventures in Machine Learning

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published for ca. et år siden

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MP3•Episode hjem

Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

208 episoder

#Tech #Careers #Business #Machine Learning #Artificial Intelligence #Data Analysis #Data Science #Podcasting Education #Ben Wilson, Michael Berk #Ben Wilsons #Michael Berk

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1
Integrating Business Needs and Technical Skills in Effective Model Serving Deployments - ML 184 51:26

for 21 dage siden51:26

51:26

Welcome back to another episode of Adventures in Machine Learning, where hosts Michael Berk and Ben Wilson delve into the intricate process of implementing model serving solutions. In this episode, they explore a detailed case study focused on enhancing search functionality with a particular emphasis on a hot dog recipe search engine. The discussion takes you through the entire development loop, beginning with understanding product requirements and success criteria, moving through prototyping and tool selection, and culminating in team collaboration and stakeholder engagement. Michael and Ben share their insights on optimizing for quick signal in design, leveraging existing tools, and ensuring service stability. If you're eager to learn about effective development strategies in machine learning projects, this episode is packed with valuable lessons and behind-the-scenes engineering perspectives. Join us as we navigate the challenges and triumphs of building impactful search solutions. Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…

1
Navigating Common Pitfalls in Data Science: Lessons from Pierpaolo Hipolito - ML 183 55:08

for 6 weeks siden55:08

55:08

Welcome to another insightful episode of Top End Devs, where we delve into the fascinating world of machine learning and data science. In this episode, host Charles Max Wood is joined by special guest Pierpaolo Hipolito, a data scientist at the SAS Institute in the UK. Together, they explore the intriguing paradoxes of data science, discussing how these paradoxes can impact the accuracy of machine learning models and providing insights on how to mitigate them. Pierpaolo shares his expertise on causal reasoning in machine learning, drawing from his master's research and contributions to Towards Data Science and other notable publications. He elaborates on the complexities of data modeling during the early stages of the COVID-19 pandemic, highlighting the use of simulation and synthetic data to address data sparsity. Throughout the conversation, the focus remains on the importance of understanding the underlying system being modeled, the role of feature engineering, and strategies for avoiding common pitfalls in data science. Whether you are a seasoned data scientist or just starting out, this episode offers valuable perspectives on enhancing the reliability and interpretability of your machine learning models. Tune in for a deep dive into the paradoxes of data science, practical advice on feature interaction, and the importance of accurate data representation in achieving meaningful insights. Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…

1
Cows, Camels, and the Human Brain - ML 182 42:06

for 8 weeks siden42:06

42:06

What do cows and camels have to do with the human brain? The latest developments in machine learning, of course! In this episode, Michael and Ben dive into a new white paper from Facebook AI researchers that reveals a LOT about the future of modeling. They discuss “cows and camels”, the question of predictive vs causal modeling, and how algorithms are getting scary good at emulating the human brain these days. In This Episode Why Facebook’s new research is VERY exciting for AI learning and causality (but what does it have to do with cows and camels?) The answer to “Is predictive or causal modeling more accurate?” (and why it’s not the best question to ask) Not sure if you need machine learning or just plain data modeling? Michael lays it out for you What algorithms are learning about human behavior to accurately emulate the human brain in 2022 and beyond Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…

1
A/B Testing with ML ft. Michael Berk - ML 181 45:41

for 9 weeks siden45:41

45:41

Michael Berk joins the adventure to discuss how he uses Machine Learning within the context of A/B testing features within applications and how to know when you have a viable test option for your setup. Links How to Find Weaknesses in your Machine Learning Models LinkedIn: Michael Berk Michael Berk - Medium Picks Ben- David Thorne Books Charles- Shadow Hunter Michael- Stuart Russell Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…

1
Navigating Build vs. Buy Decisions in Emerging AI Technologies - ML 180 31:58

for 10 weeks siden31:58

31:58

In today's episode, we dive into the critical decision-making process of building versus buying technology solutions, especially when it comes to agentic logic-based frameworks. With the industry still in its early stages, I recommend waiting for managed solutions to mature, while Ben suggests the educational value of simple project builds. They discuss the importance of understanding the technology thoroughly before diving into business-focused decisions, using tools like customer user journeys (CUJs) to evaluate scalability, cost-efficiency, and maintainability. They also highlight some initial challenges and missteps in project management and the necessity for pre-evaluation by tech teams. For non-technical teams engaged in technical projects, they provide structured guidance on navigating these unknowns efficiently. Additionally, they emphasize the value of research spikes and incremental development to manage risk and learn from user behavior. Finally, they explore the promising yet evolving landscape of generative AI and its potential high ROI with Retrieval-Augmented Generation (RAG). Socials Linkedin: Ben Wilson LinkedIn: Michael Berk Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…

1
Artificial Intelligence as a Service with Peter Elger and Eóin Shanaghy - ML 179 54:55

for 11 weeks siden54:55

54:55

Peter Elger and Eóin Shanaghy join Charles Max Wood to dive into what Artificial Intelligence and Machine Learning related services are available for people to use. Peter and Eóin are experts in AWS and explain what is provided in its services, but easily extrapolate to other clouds. If you're trying to implement Artificial Intelligence algorithms, you may want to use or modify an algorithm already built and provided to you. Links fourTheorem Twitter: Eóin Shanaghy Twitter: Peter Elger Picks Charles- The Eye of the World: Book One of The Wheel of Time by Robert Jordan Charles - Changemakers With Jamie Atkinson Charles- Podcast Domination Show by Luis Diaz Charles- Buzzcast Charles- Podcast Talent Coach Eóin- IKEA | IDÅSEN Desk sit/stand, black/dark gray63x31 1/2 " Eóin- Kinesis | Freestyle2 Split- Adjustable Keyboard for PC Peter- The Wolfram Physics Project Peter- PBS Space Time Peter- Youtube Channel | 3Blue1Brown Peter- Cracking the Code Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…

1
Combating Burnout in Machine Learning: Strategies for Balance and Collaboration - ML 178 1:12:04

for 12 weeks siden1:12:04

1:12:04

In this episode, Ben and Michael explore burnout, particularly in machine learning and data science. They highlight that burnout stems from exhaustion, cynicism, and inefficiency and can be caused by repetitive tasks, overwhelming workloads, or being in the wrong role. They also tackle strategies to combat burnout, including collaborating with others, mentoring, shifting focus between tasks, and hiring more people to distribute the workload. A key takeaway is the importance of knowledge sharing and not hoarding tasks for job security, as this can lead to burnout and inefficiency. They also discuss managing burnout and its components, particularly exhaustion, cynicism, and inefficiency, through personal experiences. Finally, they talk about how burnout can lead to inefficiency and physical manifestations, like a lack of motivation to engage in activities outside of work. Socials LinkedIn: Ben Wilson LinkedIn: Michael Berk Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…

1
The Nature of the World and AI with Rishal Hurbans - ML 177 40:36

for 12 weeks siden40:36

40:36

Rishal Hurbans is the author of Grokking Artificial Intelligence Algorithms. He walks us through how to learn different Machine Learning algorithms. He also then walks us through the different types of algorithms based on different natural systems and processes. Links Kaggle: Your Machine Learning and Data Science Community Rishal Hurbans Inktober Book giveaway link Picks Chuck- Hero with a thousand faces by Joseph Campbell Chuck- Masterbuilt smoker Rishal-Learn something new everyday Rishal- Building a StoryBrand by Donald Miller Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…

1
Crafting Data Solutions: Shrinking Pie and Leveraging Insights for Optimal Data Learning - ML 176 55:43

for 14 weeks siden55:43

55:43

In today’s episode, Michael and Ben are joined by industry expert Barzan Mozafari, the CEO and co-founder at Keebo. He delves deep into the evolving landscape of data learning and cloud optimization. They explore how understanding data distribution can lead to early detection of anomalies and how optimizing data workflows can result in significant cost savings and unintended business growth. Barzan sheds light on leveraging existing cloud technologies and the role of automated tools in enhancing system interactions, while Ben talks about the intricacies of platform migration and tech debt. They dig into the challenges and strategies for optimizing complex data pipelines, the economic pressures faced by data teams, and insights into innovation stemming from academic research. The conversation also covers the importance of maintaining customer trust without compromising data security and the iterative nature of both academic and industrial approaches to problem-solving. Join them as they navigate the intersection of technical debt, AI-driven optimization, and the dynamic collaboration between researchers and engineers, all aimed at driving continuous improvement and innovation in the world of data. So, gear up for an episode packed with insights on shrinking pie data learning, cloud costs, automated optimization tools, and much more. Let’s dive right in! Socials LinkedIn: Barzan Mozafari Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…

1
Challenges and Solutions in Managing Code Security for ML Developers - ML 175 51:46

for 15 weeks siden51:46

51:46

Today, join Michael and Ben as they delve into crucial topics surrounding code security and the safe execution of machine learning models. This episode focuses on preventing accidental key leaks in notebooks, creating secure environments for code execution, and the pros and cons of various isolation methods like VMs, containers, and micro VMs. They explore the challenges of evaluating and executing generated code, highlighting the risks of running arbitrary Python code and the importance of secure evaluation processes. Ben shares his experiences and best practices, emphasizing human evaluation and secure virtual environments to mitigate risks. The episode also includes an in-depth discussion on developing new projects with a focus on proper engineering procedures, and the sophisticated efforts behind Databricks' Genie service and MLflow's RunLLM. Finally, Ben and Michael explore the potential of fine-tuning machine learning models, creating high-quality datasets, and the complexities of managing code execution with AI. Tune in for all this and more as we navigate the secure pathways to responsible and effective machine learning development. Socials LinkedIn: Michael Berk LinkedIn: Ben Wilson Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…

1
Innovative Security Solutions for Developers - ML 174 58:26

for 16 weeks siden58:26

58:26

They delve into the journeys and insights of distinguished leaders in the development world. In today's episode, Michael engages with Brian Vallelunga, the visionary CEO of Doppler. Brian shares his compelling journey from early tech innovations to leading multiple startups and eventually founding Doppler, a centralized cloud secret management tool. Brian emphasizes the importance of making security tools enticing for developers, comparing it to making vegetables taste like candy, to boost productivity. His team’s strategy revolves around seamless integration into developers’ workflows, featuring a VS Code extension and automatic syncing akin to Dropbox, enhancing efficiency and ease of use. They explore Doppler's competitive edge and how it partners with major cloud resource managers, making two-click integrations effortless. Brian also discusses their customer-centric development approach and the release of enterprise features like two-person approval and config inheritance, designed for complex organizational needs. Brian's entrepreneurial journey is marked by significant pivots driven by frustration and market demand, rather than strategic planning alone. He shares candid thoughts on the impact of founders and success, cautioning against the allure of celebrity status and emphasizing team contributions. Join them as they dive into insightful discussions on building developer-friendly security tools, the nuances of secret management, and Brian's perspectives on startup growth and innovation. Discover how Doppler is revolutionizing secret management, one integration at a time. Socials LinkedIn: Brian Vallelunga Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…

1
Peer Review and Career Development - ML 173 1:08:09

for 17 weeks siden1:08:09

1:08:09

In today's episode, Michael and Ben discuss peer review, specifically Michael's experiences. Michael explains his unconventional path, starting with advanced math as a child, then struggling with a math-heavy computer science program in college. He pivoted to environmental studies, focusing on side projects and extracurriculars. These projects led to his first job, and later to a role at a boxing streaming service (2B) with a rigorous peer review process. Ben asks about the importance of the peer review process, and Michael highlights its value in catching errors and ensuring code quality, especially when working under pressure. Moreover, Ben discusses the learning experience at different career stages, noting that junior developers learn from senior developers' code and feedback. Ben discusses the differences in peer review for different types of code changes. They discuss the importance of thorough review for critical code changes and many more! Socials LinkedIn: Ben Wilson LinkedIn: Michael Berk Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…

1
Navigating Expertise Gaps - ML 172 1:16:15

for 18 weeks siden1:16:15

1:16:15

In today's episode, Ben and Michael discuss how to handle situations involving individuals lacking expertise in machine learning projects. They explore scenarios where a team lacks expertise, considering approaches for consultants or team members. They discuss various personality types encountered in such situations, including those overly suspicious or resistant to change. Moreover, they discuss how to convince a boss that a proposed project is a bad idea, suggesting a structured approach with clear estimates, risk assessment, and alternative solutions. They emphasize the importance of honesty, transparency, and presenting options with clear pros and cons. The discussion then returns to the Gen AI time-series case study, suggesting a presentation of multiple options, including established algorithms and the Gen AI approach, to facilitate a data-driven decision. Finally, the episode addresses the scenario of a teammate being untrained about a system they built, suggesting a combination of direct but constructive feedback and a collaborative approach to identify the root cause of the issue. Socials LinkedIn Ben Wilson LinkedIn Michael Berk Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…

1
The Influence of Gen AI on Personalized Education and Curiosity - ML 171 1:08:19

for 19 weeks siden1:08:19

1:08:19

In this episode, Michael and Ben dive deep into the intersection of education and technology with their insightful guest, Daniel Hiterer. Michael, a data engineering and machine learning expert, and Ben, an integrator of Gen AI tools, navigate through Danny's unique perspective on the impact of nurturing educational environments. Currently working at Cornell’s Studio entrepreneurship program, Danny brings a multidisciplinary background, combining history and instructional technology, and shares his vision for the future of learning. This episode explores the transformative power of nurture in education, the evolving role of Gen AI in fostering curiosity, and the challenges and opportunities in integrating AI into the learning process. Danny provides thought-provoking insights on emotional access points, curiosity-driven learning, and the delicate balance between educational goals and productivity tools. Listen in as they discuss personalized education, the promise of AI-assisted learning, and the future trajectory of superintelligence in education. Plus, hear personal anecdotes from Ben and Michael about their own learning journeys and the evolving landscape of curiosity and knowledge. Socials LinkedIn: Daniel Hiterer Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…

1
The Role of Open Source in Modern Development Practices - ML 170 1:02:12

for 20 weeks siden1:02:12