Super Data Science: ML & AI Podcast with Jon Krohn Conversations (Audio)

Super Data Science: ML & AI Podcast with Jon Krohn

AI Conversations: Hosted by Dr. Jon Krohn

Listen to Dr. Jon Krohn’s compelling interviews with the leading experts in data science, artificial intelligence, and machine learning.

Series Description

Discover the world of data science, machine learning, and AI through insightful conversations on the Super Data Science Podcast. Dr. Jon Krohn explores the latest industry trends, career advice, and the real-world impact of data-driven technologies.

Whether you’re a data science newbie, a seasoned professional, or simply fascinated by the power of AI, this podcast is for you. Jon interviews many of the biggest names in the field, explores cutting-edge techniques, and uncovers the practical applications of data analysis, predictive modeling, and machine learning. Get ready to transform your career and change the world with data!

Related Learning

Book: Deep Learning Illustrated: A Visual, Interactive Guide to Artificial Intelligence

Video: Deep Learning with TensorFlow, Keras, and PyTorch

Video: The Essential Machine Learning Foundations: Math, Probability, Statistics, and Computer Science (Video Collection)

Live Training by Jon Krohn

Playlist: Jon Krohn’s AI Catalyst Playlist

Roseanne Liu: Deep Learning Classics and Trends

Dr. Rosanne Liu, Research Scientist at Google DeepMind and co-founder of the ML Collective, shares her journey and the mission to democratize AI research. She explains her pioneering work on intrinsic dimensions in deep learning and the advantages of curiosity-driven research. Jon and Dr. Liu also explore the complexities of understanding powerful AI models, the specifics of character-aware text encoding, and the significant impact of diversity, equity, and inclusion in the ML community. With publications in NeurIPS, ICLR, ICML, and Science, Dr. Liu offers her expertise and vision for the future of machine learning.

You will learn:

• How the ML Collective came about
• The concept of a failure CV
• ML Collective research topics
• How Dr. Liu’s work on the “intrinsic dimension” of deep learning models inspired the now-standard LoRA approach to fine-tuning LLMs
• The pros and cons of curiosity-driven vs. goal-driven ML research
• Discussion on Dr. Liu’s research and papers
• Character-aware vs. character-blind text encoding
• The positive impacts of diversity, equity, and inclusion in the ML community

Sol Rashidi: Ensuring Successful Enterprise AI Deployments

In this episode, Jon Krohn welcomes Sol Rashidi, a seasoned executive and author, to explore successful enterprise AI and pressing AI issues in the corporate world. They discuss the frequent turnover in C-suite roles, particularly among Chief Data Officers, and reveal which AI projects have the highest chance of success. Sol also demystifies the patent process and its importance across different industries. Join us for an episode filled with practical advice and expert insights into managing AI in complex corporate environments.

You will learn:

• How CDOs and related roles have such high turnover because
• The importance of building relationships in AI projects
• How Sol’s book “The AI Survival Guide” came about
• How high-criticality, low-complexity AI projects are the ones with the highest probability of success
• How Enterprise data security issues can be resolved with technologies like Protopia’s stained-glass data-masking solution
• Why having great data engineers is essential
• The value of patents

Bernard Marr: Generative AI in Practice

Bernard Marr, a world-renowned futurist and leading voice in technology, breaks down the power of generative AI and its transformative potential. As the author of ’Generative AI in Practice: 100+ Amazing Ways Generative Artificial Intelligence is Changing Business and Society,’ he explains how this technology is revolutionizing industries, enhancing daily life, and solving pressing global issues. From the entertainment industry to medical settings, learn how a future led by Generative AI will impact you.

You will learn:

• How Generative AI will transform industries
• The evolution of Generative AI
• How will Generative AI impact daily life
• The ethical challenges of AI
• How corporations can harness Generative AI for collaboration
• Industries that will be impacted by Generative AI
• How Sora-like Generative AI systems will create highly immersive entertainment
• How Generative AI could unlock 99% of business data

Jason Warner: A Code Specialized LLM will Realize AGI

Jason Warner, CEO of poolside, discusses the advantages of code-specialized LLMs over generalized models such as GPT-4, highlighting their significant value to the coding community. He also predicts a paradigm shift to an "AI-led, developer-assisted" approach, driven by the potential of specialized LLMs to accelerate the development of AGI through their training on complex, multi-step logic code.

You will learn:

• Complex ideas about AI’s future in coding
• Poolside’s unique approach to high-quality code and a training set refined for relevance and impact
• The broader context of software development, promising a significant leap in how AI aids in coding

Kirill Eremenko: Technical Intro to Transformers and LLMs

Attention and transformers in LLMs, the five stages of data processing, and a brand-new Large Language Models A-Z course: Kirill Eremenko joins host Jon Krohn to explore what goes into well-crafted LLMs, how to scale them, and how to succeed as a data scientist in this new age of generative AI.

• You will learn:
• Supply and demand in AI recruitment
• Kirill’s new course on LLMs, “Large Language Models (LLMs), Transformers & GPT A-Z”
• The learning difficulty in understanding LLMs
• The basics of LLMs
• The five building blocks of transformer architecture
  1. Input embedding
  2. Positional encoding
  3. Attention mechanism
  4. Feedforward neural network
  5. Linear transformation and softmax
• Inference vs training time
• Why transformers are so powerful

Professor Joey Gonzalez: Vicuña, Gorilla, Chatbot Arena and Socially Beneficial LLMs

Joey Gonzalez speaks with Jon Krohn about LLM models and platforms, how Berkeley students leveraged the Llama LLM with data from ShareGPT to produce Vicuña, smart ways to evaluate and rank LLM models, and the prospects for AI and open-source options in the near future.

You will learn:

• Vicuña: How the revolutionary LLM came to be
• Chatbot Arena: The leading LLM leaderboard
• Trusting LLM results
• Gorilla: The open-source ChatGPT plugin alternative
• About LMSYS and long context windows
• Open- vs closed-source LLMs: Which is better?
• Aqueduct
• Founding GraphLab
• How AI will positively impact society in the coming decades

Professor Raluca Ada Popa: Generative A.I. without the Privacy Risks

Confidential computing, securely using generative AI APIs, and the ongoing debate of open-source versus closed-source AI development are top topics of discussion this week as we welcome Dr. Raluca Ada Popa, renowned computer scientist, entrepreneur, and President of Opaque Systems, to the podcast. Together with Jon Krohn, she talks about the benefits and complexities of operating compute pipelines across multiple cloud providers.

You will learn:

• What is a confidential computing platform?
• How to get started with confidential computing
• The challenges of confidential computing and LLMs
• How to safeguard your data while using commercial LLMs like GPT-4
• Open-source vs closed-source
• Raluca’s PreVail cybersecurity company
• Combining entrepreneurship and academic career
• DARE Program

Carly Taylor: Machine Learning for Video Games

Have you ever considered how machine learning affects your gaming experience? If you’re like us, you probably have! That’s why we’re excited to welcome Activision’s Carly Taylor to the SuperDataScience podcast and dive into machine learning for video games. As the Lead ML Engineer for the iconic Call of Duty, Carly uses ML to detect and minimize disruptive behavior in the game, and this week she’s here to shed light on the importance of low-latency, the future of gaming, her thoughts on the metaverse, and so much more.

You will learn:

• The relationship between data science and cyber security
• The importance of low-latency for an optimal gaming experience
• The future of gaming
• Carly’s thoughts on the Metaverse
• Carly’s favorite operating systems, software packages, and keyboards
• How to transition from a quantitative academic background into data science
• Why Carly’s called the “Rebel Data Scientist”
• How to file a patent

Matt Harrison: Effective Pandas

In this episode, Matt Harrison joins us to reveal his best Pandas tips, tricks and best practices to help you get the most out of the Python data analysis library.

• You will learn:
• Pros and cons of self-publishing and working with a publisher
• Matt’s six tips for using Pandas
• The best way for corporate teams to level up their skills
• How to learn anything effectively
• Matt’s tricks for staying motivated
• Matt’s recommendations for using Git and the Unix command line
• Matt’s recommended software libraries for working with tabular data

Wes McKinney: Open-Source Analytical Computing (pandas, Apache Arrow)

In this episode we take a technical deep dive into the creation of the pandas library, the content of Wes’s books, what Apache Arrow is, Wes’s favorite tools, and more!

You will learn:

• History of pandas
• The trends of R and Python
• Python for Data Analysis
• pandas updates and community
• Apache Arrow
• Voltron Data
• Origin of Wes’s project names
• Wes’s favorite tools

Pieter Abbeel: Deep Reinforcement Learning for Robotics

Professor Pieter Abbeel is Director of the Berkeley Robot Learning Lab and Co-Director of the Berkeley Artificial Intelligence (BAIR) Lab. Abbeel’s research strives to build ever more intelligent systems, with main emphasis on deep reinforcement learning, meta-learning. His lab also investigates how AI could advance other science and engineering disciplines. In this episode, Jon and Pieter got into some interesting conversations. They covered his most recent research in machine learning, his productivity tips, top learning resources for AI, his podcast, skills you need to succeed, and more!

You will learn:

• How does Pieter do it all?
• Pieter’s exciting areas of research
• Research application at Covariant
• Getting into AI robotics
• Traits of good AI robotics apprentices
• Valuable skills
• What Pieter hopes to look back on

Noam Brown: A.I. For Crushing Humans at Poker and Board Games

Noam Brown is a Research Scientist at Meta AI working on multi-agent artificial intelligence and computational game theory. Noam co-created Libratus and Pluribus, the first AIs to defeat top humans in two-player no-limit poker and multiplayer no-limit poker, respectively. In this episode, Noam joins Jon to discuss the absolute cutting-edge of A.I. capabilities today. Noam sheds light on his award-winning no-limit poker-playing algorithms, and the real-world implications of his game-playing AI breakthroughs.

You will learn:

• What Meta A.I. is and how it fits into Meta, the company
• Noam’s award-winning no-limit poker-playing algorithms, Libratus and Pluribus algorithms
• What game theory is and how does Noam integrate it into his models?
• The real-world implications of Noam’s game-playing A.I. breakthroughs
• Why Noam elected to become a researcher at a big tech firm instead of in academia
• The main barriers to getting AI game theory techniques beyond games to self-driving cars
• Recommendations for people who want to break into poker AI

Dr. Amira Abbas: Quantum Machine Learning

In our episode, Dr. Amira Abbas, Quantum Computing Researcher at the University of Amsterdam, provides a detailed look into the world of qubits, the essential stages of Quantum ML, and the intriguing possibilities of Quantum Support Vector Machines. She also shares crucial ML specific tools for those eager to venture into the crossroads of quantum computing and machine learning. Join host Jon Krohn in his discussion with Dr. Abbas as she unravels the world of quantum machine learning in a way that is both deep and accessible.

You will learn:

• Quantum computing vs classical computing
• What is quantum entanglement
• What is a qubit
• The best problems for quantum ML
• Three distinct steps in quantum ML and its potential
• Quantum neural networks
• What Amira’s working on
• How to get started in quantum ML
• Amira’s recommended ML tools for quantum computing

Gaël Varoquaux: scikit-learn’s Past, Present and Future, with scikit-learn co-founder Dr. Gaël Varoquaux

In this episode, scikit-learn co-founder Gaël Varoquaux sits down with Jon Krohn live at the historic Sorbonne in Paris, where they delve deep into the evolution of scikit-learn. From its origins as a memory-efficient Python implementation of support vector machines to its present-day status as a pivotal resource in machine learning, Gaël paints a vivid picture of its remarkable growth.

You will learn:

• The early beginnings and growth of scikit-learn
• Development principles of scikit-learn
• How to apply scikit-learn to your ML problem
• Resource-efficiency and scikit-learn development
• How to contribute to an open-source project like scikit-learn yourself
• The future of scikit-learn
• Gaël on the social-impact data projects in his Soda lab
• Why domain expertise and statistical rigor are more important than ever

Piotr Grudzień: How to Integrate Generative A.I. Into Your Business

Founder of Quickchat AI Piotr Grudzień believes the key to any successful AI platform is to ensure it can be tailored to a company’s specific needs. In the case of Quickchat, this means helping clients generate realistic and satisfying conversations that help their customer base find what they need quickly. The details matter to Piotr, as he explains to host Jon Krohn that he and his team see Quickchat’s platform as the “Photoshop of conversational AI,” delivering to consumers a comprehensive package where anyone can become an expert in conversation, design and testing.

You will learn:

• About Quickchat AI and how it works
• How to successfully set up a conversational AI
• What “temperature” is in the context of AI
• How the LLM landscape has changed in recent years
• The future of generative AI
• The advantages of an AI accelerator

Cole Nussbaumer Knaflic: How to Speak so You Blow Listeners’ Minds

Explore the art of persuasive communication with Cole Nussbaumer Knaflic, the author of "Storytelling with You." Cole shares invaluable insights into creating presentations that not only inform but also profoundly engage the audience. For anyone aiming to leave a lasting impression, this episode is a goldmine of strategies and tips.

You will learn:

• How to become a confident communicator
• How to get rid of filler words
• How facts alone can’t make a strong impact
• Cole’s overview of her book Storytelling with You
• How to craft an effective presentation
• Common mistakes in virtual presentations
• Cole’s virtual presentation setup
• Cole’s next book Daphne Draws Data

Rudina Seseri: The Best AI Startup Opportunities

At Glasswing Ventures, Rudina Seseri wants to be able to answer the question: What has Glasswing Ventures done for the company beyond capital investment? She speaks to Jon Krohn about the importance of an AI startup knowing its market fit, what type of AI companies have a great chance of success, and more.

You will learn:

• Potential interest areas for Series A AI venture capitalists
• How Glasswing’s AI Palette helps AI startups
• How data driven the venture capital industry is
• Advice for adopting services from AI providers
• Model collapse: Causes and concerns
• Glasswing’s checklist for AI startups

Dr. Sebastian Raschka: Open-Source LLM Libraries and Techniques

Jon Krohn sits down with Sebastian Raschka to discuss his latest book, Machine Learning Q and AI, the open-source libraries developed by Lightning AI, how to exploit the greatest opportunities for LLM development, and what’s on the horizon for LLMs.

You will learn:

• All about Machine Learning Q and AI
• Sebastian Raschka’s role as Staff Research Engineer at Lightning AI
• PyTorch Lightning’s and Lightning Fabric’s capabilities
• Large language models: Opportunities and challenges
• DoRA vs LoRA
• How to be a successful AI educator

Kirill Eremenko: Gradient Boosting: XGBoost, LightGBM and CatBoost

In this highly technical episode designed for intermediate to advanced practitioners, Kirill Eremenko, founder of SuperDataScience and online educator, joins host Jon Krohn to walk listeners through why decision trees and random forests are fruitful for businesses, and he offers hands-on walkthroughs for the three leading gradient-boosting algorithms today: XGBoost, LightGBM, and CatBoost.

You will learn:

• All about decision trees
• All about ensemble models
• All about AdaBoost
• All about gradient boosting
• Gradient boosting for classification problems
• Advantages of XGBoost
• LightGBM
• CatBoost

Aleksa Gordić: What will humans do when machines are vastly more intelligent?

Expect significant changes to the future of education: Aleksa Gordić speaks to Jon Krohn about his strategies for self-directed learning, the traits that help people succeed in moving from big tech to entrepreneurship, and the social impact of artificial superintelligence. Aleksa is an ex Google DeepMind / Microsoft ML engineer and a founder & CEO of Runa AI that builds LLMs for the lower resource languages with the belief that no language should be left behind. As a side gig he is an educator who built a community of over 160,000 people in the AI space.

You will learn:

• How to motivate yourself to become a tech entrepreneur
• Aleksa’s checklist for the perfect CTO
• Potential sustainable solutions for LLMs
• The next major developments in AI and tech
• How hobbies have a knock-on effect for a person’s career
• How and why formal education needs to change

Dr. Luis Serrano: Math, Quantum ML and Language Embeddings

In this episode, host Jon Krohn is joined by Dr. Luis Serrano of the Serrano Academy, an expert in making Math and Quantum Machine Learning accessible. They discuss simplifying complex A.I. topics, Cohere’s innovative use of embeddings, and the future of Quantum ML.

You will learn:

How math and AI can be made easy to understand
• The three major categories of learners
• Why embeddings are the most important component of LLMs
• How semantic search differs from a traditional keyword search
• The most exciting emerging application areas for AI
• The promising application areas for Quantum Machine Learning

Dr. Jason Yosinski: ML for Wind-Powered Energy Generation

Dr. Jason Yosinski and Jon Krohn explore the impact of machine learning on wind energy, focusing on how it enhances wind turbine efficiency and grid reliability. As CEO of Windscape AI, Dr. Yosinski unveils the latest ML advancements revolutionizing renewable energy practices. Their discussion delivers essential insights for both industry specialists and environmentally conscious audiences.

You will learn:

• Enhancing predictability in wind energy with ML
• Data utilization from wind turbines by energy providers
• Jason’s journey into wind energy
• Landing the right startup idea
• Visualizing neural networks with the Deep Vis Toolbox
• Extreme event forecasting at Uber vs. nowcasting at Windscape AI
• Discoveries from Loss Change Allocation research
• Engaging with Jason’s ML Collective
• Traits of successful AI entrepreneurs

Jon Krohn is Co-Founder and Chief Data Scientist at the machine learning company Nebula. He authored the book Deep Learning Illustrated, an instant #1 bestseller that was translated into seven languages. He is also the host of SuperDataScience, the data science industry’s most listened-to podcast. Jon is renowned for his compelling lectures, which he offers at leading universities and conferences, as well as via his award-winning YouTube channel. He holds a PhD from Oxford and has been publishing on machine learning in prominent academic journals since 2010.

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