The power of Data is undeniable. And unharnessed - it’s nothing but chaos. Making data your ally. Using it to lead with confidence and clarity. Host Jess Carter is solving problems in real-time to reveal what’s possible. Helping communities and people thrive. This is Data Driven Leadership, a show brought to you by Resultant.
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内容由Charles M Wood提供。所有播客内容(包括剧集、图形和播客描述)均由 Charles M Wood 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal。
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Young and Profiting with Hala Taha (Entrepreneurship, Sales, Marketing)


Too many entrepreneurs get stuck on the business treadmill, hustling nonstop, unable to scale, and unknowingly stalling their growth. That’s where Dave Ramsey began. After crashing into $3 million in debt, he rebuilt from scratch, turning a small radio program into a national show with millions of listeners. With over three decades of experience in entrepreneurship, business growth, and content creation, he knows what it takes to build a lasting business. In this episode, Dave reveals the six drivers of long-term success, the five key stages of startup growth, and how he balances life as an entrepreneur and a content creator. In this episode, Hala and Dave will discuss: (00:00) Introduction (00:23) The Core Principles of Financial Freedom (05:42) Adapting to Change as a Content Creator (09:22) Balancing Content Creation and Entrepreneurship (12:34) How to Create a Clear Path in Business (15:19) The Truth About Starting a Business Today (18:22) The Six Drivers of Business Success (26:20) Shifting From Tactical to Strategic Thinking (29:44) The Five Stages of Business Growth (41:10) Leading with Care, Clarity, and Accountability (47:10) Identifying the Right Leadership Skills (48:35) Starting a Media Business as an Entrepreneur Dave Ramsey is a personal finance expert, radio personality, bestselling author, and the founder and CEO of Ramsey Solutions. Over the past three decades, he has built a legacy of helping millions achieve financial freedom. As the host of The Ramsey Show , Dave reaches more than 18 million listeners each week. He is the author of eight national bestselling books. His latest, Build a Business You Love , helps entrepreneurs navigate growth and overcome challenges at every stage. Sponsored By: Shopify - Sign up for a one-dollar-per-month trial period at youngandprofiting.co/shopify OpenPhone: Streamline and scale your customer communications with OpenPhone. Get 20% off your first 6 months at openphone.com/profiting Airbnb - Find yourself a co-host at airbnb.com/host Indeed - Get a $75 sponsored job credit at indeed.com/profiting RobinHood - Receive your 3% boost on annual IRA contributions, sign up at robinhood.com/gold Factor - Get 50% off your first box plus free shipping at factormeals.com/factorpodcast Rakuten - Save while shopping at rakuten.com Microsoft Teams - Stop paying for tools. Get everything you need, for free at aka.ms/profiting LinkedIn Marketing Solutions - Get a $100 credit on your next campaign at linkedin.com/profiting Resources Mentioned: Dave’s Book, Build a Business You Love: bit.ly/BuildaBusinessYouLove Dave’s Website: ramseysolutions.com Active Deals - youngandprofiting.com/deals Key YAP Links Reviews - ratethispodcast.com/yap Youtube - youtube.com/c/YoungandProfiting LinkedIn - linkedin.com/in/htaha/ Instagram - instagram.com/yapwithhala/ Social + Podcast Services: yapmedia.com Transcripts - youngandprofiting.com/episodes-new Entrepreneurship, Entrepreneurship Podcast, Business, Business Podcast, Self Improvement, Self-Improvement, Personal Development, Starting a Business, Strategy, Investing, Sales, Selling, Psychology, Productivity, Entrepreneurs, AI, Artificial Intelligence, Technology, Marketing, Negotiation, Money, Finance, Side Hustle, Mental Health, Career, Leadership, Mindset, Health, Growth Mindset, Side Hustle, Passive Income, Online Business, Solopreneur, Networking.…
Peer Review and Career Development - ML 173
Manage episode 449604391 series 2977446
内容由Charles M Wood提供。所有播客内容(包括剧集、图形和播客描述)均由 Charles M Wood 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal。
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
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
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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
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
209集单集
Manage episode 449604391 series 2977446
内容由Charles M Wood提供。所有播客内容(包括剧集、图形和播客描述)均由 Charles M Wood 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal。
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
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
…
continue reading
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
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
209集单集
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Adventures in Machine Learning

In this episode, we dive deep into the evolving landscape of digital marketing and brand storytelling. We explore how the intersection of authenticity, community, and technology is reshaping how brands connect with people—and why it's no longer just about the product, but about the experience. We talk about how we've shifted our focus from performance-only metrics to a more holistic approach, blending creativity with strategy. There's a big emphasis on human-first marketing—building trust, showing up consistently, and leading with values that resonate. We also reflect on the role of content creators and influencers in today’s market, and how brands can partner more meaningfully instead of just transacting for reach. It’s about collaboration, not commodification. Key takeaways: Authenticity wins. Audiences can tell when it’s forced. Content isn't king—connection is. Brand loyalty is built through trust, not just a strong call to action. It’s time to ditch the funnel mindset and embrace more circular, relationship-driven marketing. Data is powerful, but gut instinct and creativity still matter—a lot. Whether you’re a marketer, entrepreneur, or creator, there’s something in here for you. Let’s keep pushing the industry forward—together. Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

1 Integrating Business Needs and Technical Skills in Effective Model Serving Deployments - ML 184 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 .…
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Adventures in Machine Learning

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 .…
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Adventures in Machine Learning

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 .…
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Adventures in Machine Learning

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 .…
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Adventures in Machine Learning

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 .…
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Adventures in Machine Learning

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 .…
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Adventures in Machine Learning

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 .…
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Adventures in Machine Learning

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 .…
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Adventures in Machine Learning

1 Crafting Data Solutions: Shrinking Pie and Leveraging Insights for Optimal Data Learning - ML 176 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 .…
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Adventures in Machine Learning

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 .…
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Adventures in Machine Learning

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 .…
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Adventures in Machine Learning

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 .…
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Adventures in Machine Learning

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 .…
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Adventures in Machine Learning

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 .…
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Adventures in Machine Learning

1 Redefining Data Science Roles: Beyond Technical Skills and Traditional Job Descriptions - ML 155 57:43
In today's episode, Michael Berk and Ben Wilson dive deep into the intricacies of technical interviews for machine learning roles. They discuss the importance of assessing candidates' genuine knowledge of traditional and deep learning models and the value of being candid about one's expertise. They explore how technical skills, particularly in applied machine learning, are evaluated with a focus on their impact on business outcomes. Michael and Ben also address the common misalignments between job descriptions and the actual skills required, stressing the need for problem-solving capabilities and critical thinking over memorized knowledge. Additionally, they delve into the roles within data science—analysts, applied ML specialists, and researchers—highlighting the importance of fitting the right skills to the right job. They also touch on the evolving expectations and frustrations with the current hiring process, offering insights on how it can be improved. Stay tuned as they unpack these topics and more, including valuable tips for showcasing your skills effectively on resumes, and the significance of asking insightful questions during interviews. Whether you’re an aspiring data scientist or a seasoned professional, this episode is packed with practical advice and industry insights you won’t want to miss! Socials LinkedIn: Ben Wilson LinkedIn: Michael Berk Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

Michael Berk and Ben Wilson from Databricks are joined by Brooke Wenig, who has a fascinating background in distributed machine learning. Today’s conversation dives deep into the intersection of AI, environmental science, and career transitions. They explore how individuals like Michael transformed their careers from environmental science to AI, leveraging existing expertise in innovative ways. Ben shares insights on leaping from non-technical roles to data science by embracing automation with Python and machine learning. We tackle the critical shift in roles, the balance between education and hands-on experience, and the growing disparity between academia and industry. Brooke brings valuable perspectives on project scoping, from aligning success criteria to ensuring real-world value. The discussion revolves around augmenting existing roles with AI, common pitfalls, and transitioning proofs of concept to production. They also explore the practical applications of language models, the debate over open versus closed source models, and the future of AI in various industries. With a focus on collaboration, the traits of top data scientists, and the implications of integrating AI into non-tech fields, this episode is packed with insights and tips for anyone looking to navigate the exciting world of AI and machine learning. Join them as they delve into these topics and more, discussing the evolving landscape of AI and how it's shaping careers and industries alike. Socials LinkedIn: Brooke Wenig Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

1 AI in Security: Revolutionizing Defense and Outsmarting Attackers in the Digital Era - ML 153 1:17:50
Michael Berk and Ben Wilson join cybersecurity expert Daniel Miessler to delve into the cutting-edge world of AI and cybersecurity. They discuss the evolving tactics of attackers, from specialized targeting to AI-driven data collection. The episode tackles dynamic risk assessment, the arms race between attackers and defenders, and the role of open-source models in security. They explore AI's potential to monitor, defend, and even augment human efforts against security threats, touching on both the opportunities and ethical challenges. They also examine AI's role in protecting against social media scams and phishing attacks, envisioning a future where AI acts as our digital guardian. Whether you're in cybersecurity, development, or simply curious about AI's impact on security, this episode is packed with valuable insights. Stay tuned for a fascinating discussion! Socials LinkedIn: Daniel Miessler Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

Fernando Lopez is an AI Engineer at Google. They delve deep into the realms of machine learning, documentation challenges in open-source projects, and the transition from startup environments to tech giants like Google. They share their candid experiences with impostor syndrome, practical tips for continuous learning, and the nuances of scaling solutions in the dynamic tech landscape. Explore the nuances of software development, the complex interplay of learning strategies, and the realities of navigating large-scale organizations. Join them as the industry experts unravel the intricacies of prototyping, scaling challenges, and the value of hands-on experience in shaping successful tech careers. Get ready to immerse yourself in a wealth of knowledge and thought-provoking insights that underscore the essence of growth and innovation in the tech realm. Socials LinkedIn: Fernando Lopez Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

Deeksha Goyal is the Senior Machine Learning Engineer at Lyft and Michael Sun is the Staff Software Engineer at Lyft. They delve into the intricacies of machine learning and data-driven technology. In this episode, they explore the challenges and innovations in deploying models into production, particularly focusing on the real-world implications of ETA (Estimated Time of Arrival) modeling at Lyft. They share valuable insights, from the complexities of A/B testing and long-term impact assessment, to the dynamic nature of handling real-time data and addressing unpredictability in route predictions. Join them as they journey through the world of model deployment, bug identification, and career development within the fast-paced environment of Lyft's data-driven infrastructure. Sponsors Chuck's Resume Template Developer Book Club Become a Top 1% Dev with a Top End Devs Membership Socials LinkedIn: Deeksha Goyal LinkedIn: Michael Sun Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

Matt Van Itallie is the Founder & CEO at Sema. This episode covers a wide range of topics, from the impact of AI and machine learning on software development and educational systems, to the importance of code reviews and career advice in the tech industry. Matt Van Italy shares his diverse experiences in law, consulting, public schools, and the tech sector, emphasizing the value of using data to drive improvements. The conversation also touches on the use of GenAI tools in development and the need for organizations to embrace new technology to stay competitive. They also explore issues such as defense spending, career transitions, and the significance of investing in education and human capital. Sponsors Chuck's Resume Template Developer Book Club Become a Top 1% Dev with a Top End Devs Membership Socials LinkedIn: Matt Van Itallie Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

Terry Rodriguez is the Co-Founder at Remyx AI. They discuss the challenges and opportunities in deploying and updating AI models for robotics, exploring the potential applications across various industries, and delving into the complexities of conducting experiments and controlling for interaction effects. You'll also hear from industry experts who have worked on recommender algorithms and enhancing content recommendations through experimental workflows and hypothesis testing. Get ready for an insightful and dynamic conversation about the latest developments in the ML landscape! Sponsors Chuck's Resume Template Developer Book Club Become a Top 1% Dev with a Top End Devs Membership Socials LinkedIn: Terry Rodriguez Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

Lukas Geiger is a Deep Learning Scientist, open-source developer, and an astroparticle physicist. He shares his experience using machine learning to analyze cosmic ray particles and detect secondary particles. We explore the challenges and opportunities of open source as a business model, the potential of models for edge computing, and the importance of understanding open-source code. Join us as we delve into the intersection of physics, machine learning, and the intricate world of software development. Sponsors Chuck's Resume Template Developer Book Club Become a Top 1% Dev with a Top End Devs Membership Socials LinkedIn: Lukas Geiger Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

1 Data Platform Innovation: Navigating Challenges and Building a Unified Experience - ML 147 1:06:25
Nick Schrock is the Founder of Dagster Labs. He is also the Creator of Dagster and the Co-creator of GraphQL. They delve into the world of data engineering, software development, and ML orchestration. In today's episode, they explore the challenges and intricacies of standardizing data movement, handling data access in various systems, and migrating data across different platforms. They share insights on the importance of building a system that spans multiple data platforms, the decision-making process behind tool development, and the impact of lineage in managing and migrating data. Join them as they uncover the complexities of open-source projects, API evolution, and the future of data engineering. Sponsors Chuck's Resume Template Developer Book Club Become a Top 1% Dev with a Top End Devs Membership Socials LinkedIn: Nick Schrock Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

Ben and Michael dive into the dynamic relationship between engineers and scientists in the realms of software engineering and physical science. They explore the differences and similarities between these roles, sharing valuable insights on the research and testing processes, the importance of thorough research, the value of teamwork, and the challenges of transitioning between engineering and science. With analogies, real-world examples, and expert perspectives, they shed light on the intricacies of these roles and the considerations for hiring scientists and engineers based on company size and market effects. Tune in for a thought-provoking discussion on finding the optimal path between efficiency and innovation in the world of technology and research! Sponsors Chuck's Resume Template Developer Book Club Become a Top 1% Dev with a Top End Devs Membership Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

Michael and Ben dive into the critical role of design in software development processes. They emphasize the value of clear and understandable code, the importance of thorough design for complex projects, and the need for comprehensive documentation and peer reviews. The conversation also delves into the challenges of handling complex code, the significance of prototype research, and the distinction between design decisions and implementation details. Through real-world examples, they illustrate the impact of rushed processes on project outcomes and the responsibility of tech leads in analyzing and deleting unused code. Join them as they explore how process and organizational culture contribute to successful outcomes in tech companies and why companies invest in skilled individuals who can work efficiently within established processes. Sponsors Chuck's Resume Template Developer Book Club Become a Top 1% Dev with a Top End Devs Membership Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

Michael and Ben share their insights on being called in to fix issues in production systems at the last minute. They stress the importance of asking questions to understand the context and navigate the political landscape, and caution against providing half-baked solutions. They also discuss the significance of understanding project goals, documenting decision-making processes, and providing guidance to the team to avoid building unnecessary and difficult-to-maintain systems. Stay tuned as they share their experiences and valuable advice for navigating complex projects and delivering meaningful solutions. Sponsors Chuck's Resume Template Developer Book Club Become a Top 1% Dev with a Top End Devs Membership Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

Ben and Michael dive into the world of machine learning operations (MLOps) and discuss the complexities of building a computer vision pipeline to detect fishing boats at ports. They unpack the intricacies of MLOps basics and the challenges of implementing an effective computer vision model for traffic optimization and data collection at ports. From discussing the importance of exploratory data analysis (EDA) and data cleaning for image classification to the intricacies of continuous integration and deployment, this episode provides invaluable insights into the practical application of machine learning in real-world scenarios.Sponsors Chuck's Resume Template Developer Book Club Become a Top 1% Dev with a Top End Devs Membership Advertising Inquiries: https://redcircle.com/brands Privacy & Opt-Out: https://redcircle.com/privacy Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

Ben and Michael dive into the complex world of decision-making, transparency, and truth-seeking in professional settings. They share their insights on challenging decisions, navigating organizational hierarchies, and the importance of evidence-based arguments. From the intricacies of software development to the dynamics of leadership, they discuss the challenges and strategies for making informed decisions and seeking truth within organizations. Whether you're a tech lead, director, or aspiring leader, this episode offers valuable perspectives on humility, empathy, and effective communication in the fast-paced world of technology. Sponsors Chuck's Resume Template Developer Book Club starting Become a Top 1% Dev with a Top End Devs Membership Advertising Inquiries: https://redcircle.com/brands Privacy & Opt-Out: https://redcircle.com/privacy Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

Davis King is the perception engineer at Aurora. They talk about Dlib, which makes real-world machine learning and data analysis applications. They delve into the complexities of CUDA extensions, software layering, and the critical role of accurate data in machine learning. Join them as they dissect the challenges and importance of creating well-structured software with clear APIs, the intricacies of real-time systems, and the impact of language choice on code complexity and maintenance. Sponsors Chuck's Resume Template Developer Book Club starting Become a Top 1% Dev with a Top End Devs Membership Links Dlib.net Socials LinkedIn: Davis King Advertising Inquiries: https://redcircle.com/brands Privacy & Opt-Out: https://redcircle.com/privacy Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

Today, they dive deep into the fascinating intersection of open-source development and machine learning. Michael and Ben are joined by distinguished guest, Görkem Erkan, CTO and seasoned engineer at Jozu. Görkem shares his illustrious career journey from Nokia to Red Hat, his contributions to the Eclipse Foundation, and his current focus on MLOps. They explore his passion for open-source projects, the cultural and communication impacts on software design, and the unique challenges posed by integrating open-source frameworks with proprietary systems. Ben provides critical insights on the complexities of managing scalable backend services and the hurdles in translating SaaS offerings to open-source platforms. Tune in to learn about the innovative practices at Jozu, the role of open communication in team success, and the nuanced debate on maintaining separate proprietary and open-source codebases. This episode is packed with valuable lessons for developers, tech leaders, and anyone interested in the future of machine learning and open-source development. Socials LinkedIn: Görkem Ercan Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

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. Links Semblian 2.0 Socials LinkedIn: Artem Koren Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

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. Socials LinkedIn: Hikari Senju Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

1 Learning, Testing, and Mentorship: Building Autonomy and Confidence in Python Development - ML 167 1:06:39
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 .…
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Adventures in Machine Learning

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! Socials LinkedIn: Richmond Alake Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

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. Socials Abi Aryan LinkedIn: Abi Aryan Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

1 Maintaining Backward Compatibility in Software Projects: Strategies from Industry Experts - ML 164 59:52
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. Socials LinkedIn: Sandy Ryza Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

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. Socials LinkedIn: Michael berk LinkedIn: Benjamin Wilson Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

In today's episode, Ben and Michael dive deep into the intersection of education, AI, and innovative instructional design. Luis Garcia who is the President of PETE, delves into automating instructional design, content development, and assessments, shedding light on the evolving educational landscape and the pivotal role of evaluation and learning. Ben shares invaluable insights on leveraging chat GPT and generative AI to streamline documentation creation and evaluate knowledge, drastically cutting down processing times. Together, Luis and Ben discuss the positive reception and transformative potential of AI-driven micro-courses, text-to-speech features, and customized training tools in education. They also touch on the intense training involved in fields like nuclear reactor operation and the need for effective onboarding processes. Michael contributes by emphasizing empathy and strategic pacing in international business projects, while also summarizing instructional strategies and organizational tips for rapid learning and growth. Join them as they explore the crucial role of innovative AI technologies and personalized learning tools in reshaping education and business training, featuring insights from top industry professionals and thought leaders. And don't miss the chance to learn more about Pete and Collectiva. Get ready for a compelling discussion about enhancing learning outcomes and the future of education with AI! Socials LinkedIn: Luis E. Garcia Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

In today's episode, our hosts Michael, Ben, and special guest Keith Goode delve deep into the transformative role of AI and machine learning in modern HR practices. They tackle a range of topics, starting with the innovative use of AI to streamline surveying and sentiment analysis in employee evaluations. They explore the exciting potential of AI models in technical data collection, particularly for interviews, and discuss how these models can assess candidates' sentiment and confidence levels, providing valuable insights into their fit for specific roles. They also hear about the emerging trends discussed at the recent Databricks Data and AI Summit, where generative AI for resume screening took center stage. They debate the challenges and opportunities of leveraging AI to reduce information overload in analytics, particularly within the complex hiring process. They emphasize the importance of explainable AI models, consulting scalability, and the perennial issue of data cleansing in HR. Additionally, the episode touches on the critical aspects of diversity and inclusion in the workplace, the influence of new legislation on workforce diversity modeling, and how companies can configure HR systems to suit their unique needs. They share insights into using advanced tools like XGBoost for predictive modeling, highlight the significance of face-to-face interactions in interview processes, and caution against over-reliance on automated resume screening. Join them as they navigate these thought-provoking discussions and more, shedding light on the intersection of AI, machine learning, and human resources. Socials LinkedIn: Keith Goode Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

In today's episode, they delve deep into the intertwining worlds of technology, security, and innovation with Aaron Painter, CEO at Nametag. Aaron kicks things off by underlining the cultural facets in hiring, emphasizing the virtues of being good listeners, intellectually curious, kind, and respectful while achieving tangible results. We also explore the collaborative spirit in group product planning and the pivotal role of diverse perspectives. From there, Ben takes us into the fascinating—and somewhat unnerving—advancements in deep fakes, particularly in image generation, and their implications for security and entertainment. This discussion also touches on the complexities of preventing deep fake attacks and the critical role of technology in mitigating these threats. Michael weighs in on how physical devices and user verification limit fraudulent deep fake activities, while Aaron offers invaluable advice on latching onto growing fields like AI for future-proofing your career. We also delve into a riveting recount of Ben’s early data science days, offering a glimpse into the tech evolution from Hadoop to cloud computing. Our conversation spans intriguing analogies, from the oil industry to AI, and examines the crucial shift toward cloud technologies, underpinned by end-use cases and consumer demands. We discuss the pressing need for secure identity verification in the digital age, exploring multifactor authentication and the delicate balance between security and user experience. Additionally, the episode covers Microsoft’s impact on global economies, with Aaron sharing heartfelt insights from his illustrious career. Join them as they navigate these compelling topics and more, offering a wealth of knowledge for developers, tech enthusiasts, and anyone keen on the future of technology. Tune in and prepare to elevate your understanding as we unfold the latest in machine learning, AI, and technological innovation. Socials LinkedIn: Aaron Painter Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

In today’s episode, they dive into the intricate world of MLOps with Brad Micklea, a seasoned expert with extensive experience in software infrastructure and leadership roles at Eclipse Shay, Red Hat, AWS, and Jozu. Brad shares his journey of founding Jozu, an MLOps company that stands out with its commitment to open standards such as the OCI standard for packaging AI projects. Alongside Jozu, they explore KitOps, an innovative open-source project that simplifies version control and collaboration for AI teams. Join them as they discuss the challenges in integrating AI models into production, the importance of monitoring API usage, and the critical role of automated rollback systems in maintaining operational excellence. They also touch on the cultural differences in operational approaches between giants like AWS and Red Hat and hear first-hand experiences on the significance of transparency, trust, and efficient risk management in both startups and established companies. Whether you're a DevOps professional, MLOps practitioner, or data scientist transitioning to production, this episode is packed with valuable insights and practical advice to help you navigate the complexities of AI project management. Tune in to discover how Brad and his team are tackling these challenges head-on and learn how to set up your projects for success from the ground up! Socials LinkedIn: Brad Micklea Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

In today's episode, they dive deep into the evolving landscape of software development. Join us as Kirk, the CTO and founder at Graphlit, shares his journey from traditional software at Microsoft to pioneering perception ML for drone-based aerial intelligence. They explore the paradigm shift from object-oriented to functional programming, the crucial role of software architecture, and the challenges of maintaining consistent design and documentation in growing teams. They also get insights into Databricks' approach to user-friendly API design and the importance of learning management systems in knowledge distillation. Listen in as our speakers discuss the strategic decisions in scaling products, the nuances of open-source contributions, and the value of automation in modern development. Whether you're navigating a startup or a large enterprise, this episode is packed with expert advice on building robust, scalable systems and the dynamic decision-making needed to thrive in today's tech environment. Tune in and elevate your development game! Socials LinkedIn: Kirk Marple Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

In today's episode, Michael and Ben alongside our guest Alex Levin dive deep into the evolving landscape of AI development and its broader implications on business and society. You'll hear Ben emphasize reducing the cost and time of AI development by leveraging open-source models, while Alex draws parallels between the AI industry and flat-screen TVs, advocating for AI as a public good. The conversation traverses through the importance of compelling AI services, revenue-generating strategies, and the disruption AI brings—both in job creation and efficiency improvement. From personal anecdotes in semiconductor fabs to the pitfalls of the YC funding model, we explore various facets of success in the tech world. Alex brings a unique perspective from his background in psychology and entrepreneurship, touching on the importance of market timing, embracing uncertainty, and the significant role of mentorship. Whether you're a startup enthusiast or a seasoned tech veteran, this episode will provide invaluable insights on navigating the complexities of AI development, operational challenges for founders, and the essential balance between innovation and business strategy. So tune in, and let's get started on this journey through the cutting edge of technology with our insightful guests on Top End Devs! Socials LinkedIn: Alex Levin alexrlevin.com Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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Adventures in Machine Learning

In today's episode, Michael and Ben dissect the process of building maintainable and impactful products, emphasizing the crucial balance between innovation and simplicity. They explore personal and group learning curves, the value of collaboration, and the indispensable role of peer review in creating robust solutions. They'll also touch upon the nuanced perspectives of working at top tech companies like Google and Databricks, examining how timing and project involvement can shape a developer's skillset and career trajectory. From the importance of understanding one's career goals to the powerful impact of a company's culture on code quality, they aim to uncover the multifaceted aspects of professional growth in tech. Join they as they delve into stories of overengineered solutions, the necessity of constructive feedback, and the collaborative efforts that define truly great products. Whether you're aspiring to join the elite 1% of developers, or simply looking to understand the dynamics of a high-functioning team, this episode is packed with insights and practical advice. So, tune in and let's explore the path to greatness together! Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support .…
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