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In this episode of the O’Reilly Data Show, I spoke with Danny Bickson, co-founder and VP at Dato, and the principal organizer of the Data Science Summit (full disclosure: I’m a member of the conference organizing committee). Among machine learning students and practitioners, recommender systems have become somewhat of a canonical use case and application. One of the early and popular building blocks was GraphLab’s collaborative filtering toolkit, a library originally written and maintained by Bickson. He has continued to keep tabs on the latest developments in recommenders and continues to help organize workshops on related topics throughout the world.

Building and Deploying Large-Scale Machine Learning Applications

In this session of the Super Data Science Podcast, I chat with machine learning expert Hadelin de Ponteves about his work at Google, Canal+ and what career implications may come from the rapid growth of the Data Science field.

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/2

The Super Data Science Podcast: Big Data | Analytics Careers | Mentors | Success

SDS 002 : Machine Learning, Recommender Systems and The Future of Data with Hadelin de Ponteves

In this session of the Super Data Science Podcast, I chat with Up and Rising Tableau Expert Megan Putney. You will know about how Megan started with Tableau through online learning, learn about know about Ad Hoc Analytics and gain some powerful Tableau insights.

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/12

SDS 012 : Online Learning, Tableau Insights and Ad Hoc Analytics with Megan Putney

In this episode of the Data Show, I spoke with Parvez Ahammad, who leads the data science and machine learning efforts at Instart Logic. He has applied machine learning in a variety of domains, most recently to computational neuroscience and security. Along the way, he has assembled and managed teams of data scientists and has had to grapple with issues like explainability and interpretability, ethics, insufficient amount of labeled data, and adversaries who target machine learning models. As more companies deploy machine learning models into products, it’s important to remember there are many other factors that come into play aside from raw performance metrics.

Building Machine Learning Solutions That Can Withstand Adversarial Attacks

In this episode of the SuperDataScience Podcast, I chat with Kaggle Grandmaster Eu Jin Lok. You will be able to know how to forecast year-ahead hospital stays using an ensemble of algorithms, discover feature extraction in a credit scoring model, discuss his great competition experiences and be able to get ideas on how to be involved in a Kaggle competition.

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/45

SDS 045: Exclusive Interview with the Legendary in Kaggle Competitions Eu Jin Lok

In this episode of the SuperDataScience Podcast, I chat with the Deep Learning Expert Hadelin de Ponteves. You will be able to have a look at the 6 supervised and unsupervised deep learning models, learn the idea to the question: why deep learning instead of machine learning, and discover TensorFlow and PyTorch as the two major tools in Deep Learning.

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/47

SDS 047: An Expert Overview of the Deep Learning Models, Supervised and Unsupervised

In this episode of the SuperDataScience Podcast, I chat with the Chief Data Officer at Ziff, Ben Taylor. You will discuss about the future of AI & what the world of future could look like, learn about the different approaches to Deep Learning revolution, and also get to know the consequences of the oncoming AI developments.

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/85

SDS 085: The AI Revolution – What the Future Will Look Like

What changes in life are you starting to work on in this new year?

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/122

SDS 122: Who Moved My Cheese?

In this episode of the SuperDataScience Podcast, I chat with the Artificial Intelligence Entrepreneur, the one and only, Hadelin de Ponteves. You will know why learning Blockchain makes perfect sense in this generation right now, learn the no. 1 reason why Blockchain is so disruptive, and listen to valuable insights on real life and innovative applications of Blockchain technology. 

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/139

SDS 139: The Rise of Blockchain: A Disruptive Super-Technology Much More Than Bitcoin

In this episode of the SuperDataScience Podcast, I chat with the Senior Consultant of Data Science at b.telligent, Dr. Andreas Hopfgartner. You will discuss the "Internet of Things", Sensor Data, and their integration into our daily lives; you will also know the different skills, techniques and the future of some of the tools used in Data Science; and also learn a systematic and structured approach to breaking into a Data Science career. 

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/143

SDS 143: Why Sensors and the Internet of Things are Becoming A Critical Part of Data Science

In this episode of the SuperDataScience Podcast, I chat with Serial Entrepreneur, Josey Parks. You will learn how a brick and mortar entrepreneur is leveraging data to build a business empire, know how Josey is training his salesmen as data analysts and get valuable tips on how to spread the power of data in the contractor industry. 

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/145

SDS 145: How to Use Data Science In Offline Business

In this episode of the SuperDataScience Podcast, I chat with independent turnaround consultant, Vitaly Dolgov. You'll talk about a scheduling system that just gets so many things done, know how to block out your time in your calendar and then committing to it, and also learn the power of routines by removing unnecessary decision making.

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/147

SDS 147: How to Live a More Fulfilling Life - Time & Energy Management

What would possibly be your attitude towards self-driving cars?

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/148

SDS 148: The Trolley Problem

In this episode of the SuperDataScience Podcast, I chat with the Associate Director of Data Science for Merck and Co., You will learn about Data Science Leadership and how to serve your team, discuss about the rapidly evolving world of AI startups, and talk about the ethical implications of Artificial Intelligence with its rapid integration in the society. 

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/149

SDS 149: Data Science Tips for Startups to Large Companies

In this episode of the SuperDataScience Podcast, I chat with the founder of Magnetic Memory Method, Anthony Metivier. You will discuss about the 7 magnetic modes to easily memorize stuffs, learn how to find your own memory palace and navigating through it, and know how to use memory techniques in your day to day life. 

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/153

SDS 153: Tips to Improve your Memory

In this episode of the SuperDataScience Podcast, I chat with the aspiring data scientist, Mike Taveirne. You will discuss the five stages of data science process for starters, get valuable tips for people who want to learn and transition to data science, and know how to apply your data science knowledge to your hobbies and interests.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/159

SDS 159: From Developer to Data Scientist

In this episode of the SuperDataScience Podcast, I chat with the Founder and Chief Technology Officer of Kylie.AI, Sinan Ozdemir. You will discuss Feature Engineering and why is it vital in interpreting and analyzing data models; you will also talk about Automated Customer Care Services and its importance in the future of enterprises, and get insights on why humans should ensure that AI is ethically responsible when serving humanity.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/161

SDS 161: Using AI to Automate Communication

In this episode of the SuperDataScience Podcast, I chat with Data Science recruiter, Matt Corey. You will talk about Matt's role as a Data Science recruiter, get interesting tips and insights about what recruiters look for in finding candidates for a data science position, and you will also know what are the things to expect from a recruiter and how intricate is the role of a good recruiter in Data Science. 

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/179

SDS 179: How a Data Science Recruiter Thinks

In this episode of the SuperDataScience Podcast, I chat with Founder and managing partner at velocitygroup.io, Tim Lafferty. You will discuss about Tim's insights from his consulting experience in the space of Data Science, talk about the 3 main aspects of the life cycle of a successful data project, and also know the 10 things that a degree won't teach you.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/181

SDS 181: 10 Tips from a Data Science Consultant

In this episode of the SuperDataScience Podcast, I chat with the Epic Life Coach, Carl Massy. This episode is a total pause from the Data Science world as talks about the secret to happiness. You will know what led Carl to follow his passion in helping people find inner happiness, learn how to establish daily rituals to have a solid foundation, and get the 3 valuable tips on how to change your state of mind.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/197

SDS 197: How to be Happy and Successful

In this episode of the Data Show, I spoke with Andrew Burt, chief privacy officer and legal engineer at Immuta, a company building data management tools tuned for data science. Burt and cybersecurity pioneer Daniel Geer recently released a must-read white paper (“Flat Light”) that provides a great framework for how to think about information security in the age of big data and AI. They list important changes to the information landscape and offer suggestions on how to alleviate some of the new risks introduced by the rise of machine learning and AI.

We discussed their new white paper, cybersecurity (Burt was previously a special advisor at the FBI), and an exciting new Strata Data tutorial that Burt will be co-teaching in March.

How Machine Learning Impacts Information Security

Three generals are voting on whether to attack or retreat from their siege of a castle. One of the generals is corrupt and two of them are not. What happens when the corrupted general sends different answers to the other two generals?

A Byzantine fault is "a condition of a computer system, particularly distributed computing systems, where components may fail and there is imperfect information on whether a component has failed. The term takes its name from an allegory, the "Byzantine Generals' Problem", developed to describe this condition, where actors must agree on a concerted strategy to avoid catastrophic system failure, but some of the actors are unreliable."

The Byzantine Generals' Problem and associated issues in maintaining reliable distributed computing networks is illuminating for both AI alignment and modern networks we interact with like Youtube, Facebook, or Google. By exploring this space, we are shown the limits of reliable distributed computing, the safety concerns and threats in this space, and the tradeoffs we will have to make for varying degrees of efficiency or safety.

The Byzantine Generals' Problem, Poisoning, and Distributed Machine Learning with El Mahdi El Mahmdi is the ninth podcast in the AI Alignment Podcast series, hosted by Lucas Perry. El Mahdi pioneered Byzantine resilient machine learning devising a series of provably safe algorithms he recently presented at NeurIPS and ICML. Interested in theoretical biology, his work also includes the analysis of error propagation and networks applied to both neural and biomolecular networks. This particular episode was recorded at the Beneficial AGI 2019 conference in Puerto Rico. We hope that you will join in the conversations by following us or subscribing to our podcasts on Youtube, SoundCloud, iTunes, Google Play, Stitcher, or your preferred podcast site/application. You can find all the AI Alignment Podcasts here.

If you're interested in exploring the interdisciplinary nature of AI alignment, we suggest you take a look here at a preliminary landscape which begins to map this space.

Topics discussed in this episode include:

The Byzantine Generals' Problem
What this has to do with artificial intelligence and machine learning
Everyday situations where this is important
How systems and models are to update in the context of asynchrony
Why it's hard to do Byzantine resilient distributed ML.
Why this is important for long-term AI alignment
An overview of Adversarial Machine Learning and where Byzantine-resilient Machine Learning stands on the map is available in this (9min) video . A specific focus on Byzantine Fault Tolerant Machine Learning is available here (~7min)

In particular, El Mahdi argues in the first interview (and in the podcast) that technical AI safety is not only relevant for long term concerns, but is crucial in current pressing issues such as social media poisoning of public debates and misinformation propagation, both of which fall into Poisoning-resilience. Another example he likes to use is social media addiction, that could be seen as a case of (non) Safely Interruptible learning. This value misalignment is already an issue with the primitive forms of AIs that optimize our world today as they maximize our watch-time all over the internet.

The latter (Safe Interruptibility) is another technical AI safety question El Mahdi works on, in the context of Reinforcement Learning. This line of research was initially dismissed as "science fiction", in this interview (5min), El Mahdi explains why it is a realistic question that arises naturally in reinforcement learning

El Mahdi's work on Byzantine-resilient Machine Learning and other relevant topics is available on
his Google scholar profile.

The Byzantine Generals' Problem, Poisoning, and Distributed Machine Learning with El Mahdi El Mhamdi

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast.

As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact.

Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy.

We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

SDS 161: Using AI to Automate Communication

Super Data Science: ML & AI Podcast with Jon Krohn