Data Driven: the podcast where we explore the emerging field of Data Science. We bring the best minds in Data, Software Engineering, Machine Learning, and Artificial Intelligence right to you every Tuesday.
The field of data science mashes up the worlds of statistics, database architecture and software engineering. Data Scientist has been labelled by the Harvard Business Review, as "the sexiest job of the 21st century." A quick search of job search sites reveal that this field is in high demand.
In a world where Data is the new Oil, Data Science the new Refineries, consider this Car Talk for the Data Age. Every week we bring the best minds in this emerging field straight to you. Our goal is to educate and inspire our listeners so that they can be prepared to thrive in a Data Driven world.
*Data Point* Data Collection on Vacation
In this data point episode of "Data Driven," hosts BAILeY and Frank La Vigne discuss Frank's recent vacation in Hilton Head, South Carolina, where he noticed a unique data collection device called Metro Count. Frank explores the purpose of these sensors, which are placed on the ground and can differentiate between pedestrians, bikes, and vehicles. He speculates on the data that can be collected and how it could be used, including potential insights on bike trail usage or monitoring unauthorized vehicles like e-scooters or hoverboards. Frank highlights the ubiquity of data and expresses his fascination with how it can be found even while on vacation.
Adam Ross Nelson on Getting Started in a Data Science Career
Join hosts Andy Leonard, BAILeY, and Frank La Vigne as they dive into the world of data science in the podcast 'Data Driven.'
In this episode, they interview guest Adam Ross Nelson on the topic of getting started in a data science career. Discover how data science can contribute to a company's revenue and bottom line, even in non-profit organizations. Learn about real-life use cases of data science, such as predicting the best ask in fundraising, and the importance of specific suggestions during interviews.
Get valuable insights on transitioning into a data science career and the evolving perception of data. Don't miss out on engaging discussions, expert advice, and practical tips. Tune in to 'Data Driven' for all things data science!
Piero Molino on the Impact of Declarative ML
Welcome back to another episode of Data Driven! In today's episode, we have a special guest joining our hosts Andy Leonard, BAILeY, and Frank La Vigne. We are thrilled to have Piero Molino, an expert in declarative ML, sharing his insights with us.
We'll be diving into the world of generative AI and exploring the two types of companies when it comes to adoption. Piero highlights the advantages and limitations of using APIs for quick solutions, shedding light on why owning the entire stack and platform is the next phase for companies.
Speaker BioPiero Molino, a renowned researcher and engineer, has made significant contributions to the field of artificial intelligence. He previously worked at Uber as one of the founding members of the Uber AI organization, where he spent four years conducting research and developing applications. During his time at Uber, Molino created Ludwig, an open source project that has become a foundational technology for many companies, including his own. Ludwig is recognized as one of the first machine learning systems that offer clarity and transparency. Molino's innovation and expertise have positioned him as a leading figure in the advancement of AI technologies.
Show Notes[00:01:07] Ageing well thanks to healthy lifestyle changes.
[00:05:52] Declarative configuration for creating AI pipelines.
[00:10:14] Built tool to streamline machine learning projects, shortened development time from a year to a week.
[00:13:14] Deploying machine learning models should be easier.
[00:19:42] Declarative ML: Trendy or in need of explanation?
[00:23:40] Shortcut solutions may work, but lack knowledge. Building custom data models can be costly. Differentiation and progress with new product, Bradybase.
[00:27:16] Customizable, automated solution between build and buy.
[00:30:40] Larger organizations have a spectrum of machine learning applications, with some being more impactful than others. Evaluating the feasibility of smaller applications can be costly. Having a tool to test applications quickly would be beneficial. Uber had a similar experience with self-driving cars being the highest priority.
[00:35:08] First-time CEO experiences changing priorities and challenges.
[00:37:47] New breed of generative eye tools; interactive applications; computer graphics and machine learning; improved animation in sports.
[00:41:04] Difficulty connecting transportation dots, still unresolved.
[00:44:12] Audible super premium account for book recommendations. Eye-opening books on goals and time.
[00:47:35] Encourage checking out predibus. Thanks for listening.
Lauren Maffeo on Data Governance from the Ground Up
In this episode of Data Driven, Frank and Andy Leonard are joined by guest speaker Lauren Maffeo to discuss data governance from the ground up. The conversation revolves around the importance of data governance in relation to generative AI, copyright infringement, and protecting consumer rights.
They explore topics such as the need for proactive cybersecurity measures, the challenges faced by startups in implementing data governance, and the cultural transformation required for successful implementation.
Overall, it is a thought-provoking discussion that provides insights into the complexities and potential solutions related to data governance in today's data-driven world.
Moments00:05:49 Civic Tech serves the public through technology.
00:07:50 Data governance: a holistic, cultural business strategy.
00:12:25 Data as tangible asset, managing as product.
00:14:38 Implementing data governance: start small, connect to business.
00:20:34 Data growth, lack of management, legislative progress. Clear framework for data quality needed.
00:25:14 Startups prioritize innovation for survival. Large industries restrict innovation due to regulation. Motivations and context are key in governance.
00:28:54 Data governance and copyright infringement in generative AI. The future of consumer rights and cybersecurity.
00:33:44 Encourage caution with sharing proprietary information
00:36:36 Bias in AI and data governance intertwined. Risk reduction, troubleshooting. Not all intent is negative. Challenges in data work solvable. Nonprofits and cybersecurity models for governance.
00:40:38 Encouraging shift in conversation about data governance.
00:44:34 Data found me, sparked interest in AI.
00:49:20 Technology saves time, allowing for more productivity.
00:54:03 Adopting foster pets: fun without long-term responsibility.
00:55:57 Connect on LinkedIn, visit Pragprov.com, feedback welcome.
Lauren Tickner on Strategies for Building a Personal Brand
On this episode of Data Driven, BAILeY and Frank La Vigne welcome special guest Lauren Tickner to discuss strategies for maximizing time and success in the digital age.
Lauren shares her insights on motivation, dealing with online haters, and the power of automation in business. The conversation delves into the importance of understanding risks and rewards, breaking free from traditional career paths, and the benefits of working in startups or entrepreneurial businesses. Lauren also provides valuable tips on social media content creation, utilizing storytelling and personalization to engage readers.
Additionally, she introduces the PASTA framework for creating compelling social media posts and shares her approach to tracking and optimizing the client journey.
Moments[00:01:16] The podcast uses a British voiceover actor to differentiate from East Coast accents. An AI voice named Bailey was later used, which can now be animated.
[00:06:19] Successful asset manager quits job to pursue fitness career using social media. Simplifies life and focuses on selling premium packages. Finds success with minimal monthly sales.
[00:08:05] The speaker discusses their upbringing in New York and the pressure to work in the financial industry. They admire the listener's decision to break free from that path and simplify things. They also comment on the listener's sense of humor and social media presence.
[00:13:00] To simplify social media content creation: automate posting to multiple platforms, identify 5 topics to focus on, add personal storytelling to engage readers, and include a call to action to prompt specific actions.
[00:19:41] The text discusses creating and sharing content for three different audience groups based on their familiarity with the author. It suggests using different types of content for each group, such as introducing oneself to new audiences, showcasing expertise to familiar audiences, and offering opportunities to become clients. The author also talks about segmenting content into top, middle, and bottom of the funnel, and using different calls to action to gauge audience interest.
[00:24:09] Data shows that clients who watch 2 case studies before joining stay longer. We track client journey and added quick welcome call within 4 hours of joining for positive experience. Pooled calendar allows immediate availability for calls.
[00:27:46] The author explains their approach to managing their business, aiming for a smaller internal company and owning multiple businesses rather than having a large team and many clients.
[00:31:58] We should focus on the potential benefits, not just the downsides. Make realistic lists of what could go right and wrong. Replace "time" with "life" to make better decisions. Consider leaving high-paid jobs for startups or entrepreneurial businesses. Showcase the value you can bring to companies.
[00:34:17] The speaker finds the content interesting and praises the concept, emphasizing the key takeaway. They inquire about finding more information.
Steve Orrin on the Importance of Hardware in AI Development
On this episode of Data Driven, our hosts Andy Leonard, BAILeY, and Frank La Vigne are joined by guest Steven Orrin, an expert in software and hardware innovation at Intel.
The episode dives into the crucial role that hardware plays in AI development, from data curation to training and inferencing. Steve emphasizes the importance of hardware optimization for specific workloads to achieve powerful and timely training. They also explore the impact of hardware on inferencing, particularly in real-time applications like autonomous driving. Intel, as Steve explains, is providing a diverse set of hardware architectures, including CPUs, AI accelerators, and edge AI chips, to address various AI workloads.
In addition to discussing hardware, the conversation touches on several other interesting topics. Steve dives into the concept of collapsing data related to planes or vehicles into a single integer level or bit, highlighting the value of data but also cautioning against excessive data collection. They also touch on the future of edge computing, the challenges of achieving high performance and energy efficiency, the advantages of a diverse team, and Intel's commitment to collaboration and open source.
Overall, this episode provides valuable insights into the importance of hardware in AI development and offers a fascinating glimpse into Intel's approach to providing hardware solutions for different AI workloads. Join us on this episode of Data Driven to learn more about the role of hardware in AI and Intel's contributions to the field.
Fun and informative
This show is an example of my favorite way to learn. Which is to make it fun. Do yourself a favor and give it a listen if you have any interest in data science or AI
Data Guys super entertaining
Frank and Andy are hugely entertaining and informative. The “layoff” show is one of my favorites!
Utopia for data nerds! 💥
Frank, Andy, and their highly knowledgeable guests are making data fun again! The wide variety of topics they cover and the engaging way in which they deliver them had me hooked from my very first listen. They’re also personable and funny, which is always a plus in data science. Thanks for putting out such a great show guys - keep up the amazing work! 🙏