Ai X Podcast Newsletter

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Episode 43: Deep Learning for Financial Trading with Sofien Kaabar

In this episode, Sofien Kaabar will discuss the role of deep learning and machine learning for finance, through the lens of his recent book Deep Learning for Finance. You’ll explore a whole range of topics including machine learning for finance, featuring engineering, time series prediction strategies, challenges such as backtesting, overfitting, and non-stationary data, and much more!

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Episode 42: Deciphering Data Architectures with James Serra

In this episode, James Serra, author of “Deciphering Data Architectures: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh” joins us to discuss his book and dive into the current state and possible future of data architectures. 

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Episode 41: Deep Reinforcement Learning in the Real World with Anna Goldie

In this episode, you’ll explore the field of deep reinforcement learning and the ways it influences the real world with Anna Goldie, Senior Staff Research Scientist at Google DeepMind. During this wide-ranging discussion, you’ll learn about her contributions to the field of reinforcement learning, and how we can leverage reinforcement learning effectively for real world applications going forward. 


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Episode 40: Open Table Formats Reshaping the Data Industry: A Deep Dive with Ryan Blue

Explore how open table formats are in the process of transforming the data industry. Take a deep dive into the unprecedented change presented by enabling data warehouses to share storage and the way it will help shape the future with Ryan Blue, Co-creator of Apache Iceberg.


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Episode 39: Navigating the Ethical Landscape of Generative AI with Michelle Yi

In this interview on navigating the ethical concerns of generative AI, Michelle Yi, technology leader and board member at Women in Data, will explore the causes, effects, and possible solutions for several of the concerns. In particular, she will focus on the impact of lack of explainability, legal and regulatory challenges, and how we move forward with this new technology responsibly.


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Episode 38: You’re Probably Overthinking It. Demystifying Data with Allen Downey

In this episode, Allen Downey, PhD, experienced instructor, expert in Data Science and Bayesian Statistics, and author of the book “Probably Overthinking It,” will take you on an exploration of surprising statistical phenomena and how they’re related to real-life common mistakes like the base rate fallacy, length-biased sampling, and Simpson’s paradox.


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Episode 37: No-Code & Low-Code AI: The New Era of Inclusive Tech Development with Gwendolyn Stripling

In this episode of ODSC’s Ai X Podcast, join Gwendolyn D. Stripling, PhD, AI/ML Content Developer at Google Cloud and author of Low-Code AI, to discuss the importance and impact of low-code and no-code AI on the industry. In this wide-ranging interview, they’ll explore how low-code and no-code can make AI more inclusive, how businesses can effectively implement AI solutions, and real-world examples of low-code AI in practice. 


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Episode 36: Guiding the Narrative: Shaping the Accuracy of LLM-Generated Content with Outlines by Remi Louf & Dan Gerlanc

In this episode of ODSC’s Ai X Podcast, you’ll explore guided outputs for Large Language Models. Casual users of LLMs expect the responses they receive to be clear, understandable answers or engaging dialogue, which is achievable without special guidance. If you want to use an LLM through an Application Programming Interface (API), you will need to guide the outputs. Without proper guidance, the LLM might return information in a format that’s incompatible or requires significant reformatting, making it less efficient or even unusable for the intended purpose.


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Episode 35: Large Language Models: Strategies and Best Practices with Sinan Ozdemir

In this episode, hear from Sinan Ozdemir, author of the Quick Start Guide to Large Language Models: Strategies and Best Practices for Using ChatGPT and Other LLMs. This wide-ranging discussion will take you through Sinan’s inspiration and motivations for writing this book on LLMs, as well as common questions and challenges that arise when working with LLMs. Finally, Sinan shares his take on what the future of LLMs might look like.


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Episode 34: The Modern Data Science Development Toolkit with Greg Michaelson

In this engaging discussion on the modern data science development toolkit, Greg Michaelson takes you through the tools, skills, and techniques that will help you improve your end-to-end development process.  


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Episode 33: Troubleshooting Large Language Models 

Join Amber Roberts for a wide-ranging discussion on the challenges and possible solutions for troubleshooting unstructured data, in their upcoming interview, Troubleshooting Large Language Models. Examine recent research on ways to measure and benchmark LLM models, and insights gained from various testing approaches.


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Episode 32: Exploring AI Innovation in Singapore and Beyond 

Join the Director of AI Innovation and AI trailblazer, Laurence Liew, on a fascinating journey into the heart of AI innovation in Singapore and beyond, and an exploration of his insights, experiences, and the exciting future he envisions for AI in the region.


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Episode 31: Acing the Data Science Interview  

The fields of data science and artificial intelligence are dynamic ones, with needs changing constantly. In this interview, we’ll speak with Nick Singh, Author of “Ace the Data Science Interview,” about what people can do in 2024 to stand out in a competitive job market and how to ace the interview aspect.


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Episode 30: Data Storytelling

Data doesn’t have to feel like a different language. Data storytelling can help effectively communicate data insights in a compelling, understandable manner. Learn how in this episode of the Ai X Podcast with Dominic Bohan.


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Episode 29: Catastrophic AI risks

Explore the main sources of catastrophic AI risks with Dan Hendrycks PhD, Executive Director of the Center for AI Safety, in this interview. Dan will address the four categories of catastrophic AI risks: malicious use, AI race, organizational risks, and rogue AIs.


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Episode 28: Past, Present, and Future of Large Language Models

Hear Thomas Scialom, the researcher behind renowned Generative AI projects like Llama 2, BLOOM, Toolformer, and Galactica, for an hour long discussion on the past, present, and future of LLMs. Over the course of an hour, you’ll explore recent developments and take a deep dive into future research trends in LLMs.


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Episode 27: The Ethics of Digital Minds 

Join Nick Bostorm, founding director and head of the Future of Humanity Institute at Oxford University and NYT bestselling author of Superintelligence, for a discussion on the ethics of digital minds. Over the course of an hour, you’ll explore the implications of a future where AI develops into morally considerable beings and the challenges that this presents.


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Episode 21: AI Enabled Drug Discovery 

In this Lightning Interview from ODSC and Ai+ Training, Daphne Koller, CEO and Founder of insitro, will share her knowledge about and expertise in machine learning-drive drug discovery. She’ll discuss the challenges faced, recent advances, and what she believes is the future of this technology and it’s role in the healthcare and Pharma industries.


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Check Out More Interviews

April 4, 2023 – Unleashing the Power of Collaborative AI: Federated Learning with Azure Machine Learning and NVIDIA Flare

Speakers:

  • Andreas Kopp, Sr. Cloud Solution Architect AI&Data Science, Microsoft
  • Harmke Alkemade, Cloud Solution Architect AI&Data Science, Microsoft

Learn more & register here

April 12, 2023 – Introduction to Time Series Analysis and Forecasting

Speakers:

  • Stuart Kozola, Director of Product Marketing at dotData | experienced Data Scientist | Member of SIAM and IAQF

Learn more & register here

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