Data Science at Home

Can AI really out-compress PNG and FLAC? 🤔 Or is it just another overhyped tech myth? In this episode of Data Science at Home, Frag dives deep into the wild claims that Large Language Models (LLMs) like Chinchilla 70B are beating traditional lossless compression algorithms. 🧠💥 But before you toss out your FLAC collection, let's break down Shannon's Source Coding Theorem and why entropy sets the ultimate limit on lossless compression. We explore: ⚙️ How LLMs leverage probabilistic patterns for compression 📉 Why compression efficiency doesn’t equal general intelligence 🚀 The practical (and ridiculous) challenges of using AI for compression 💡 Can AI actually BREAK Shannon’s limit—or is it just an illusion? If you love AI, algorithms, or just enjoy some good old myth-busting, this one’s for you. Don't forget to hit subscribe for more no-nonsense takes on AI, and join the conversation on Discord! Let’s decode the truth together. Join the discussion on the new Discord channel of the podcast https://discord.gg/4UNKGf3   Don't forget to subscribe to our new YouTube channel  https://www.youtube.com/@DataScienceatHome     References Have you met Shannon? https://datascienceathome.com/have-you-met-shannon-conversation-with-jimmy-soni-and-rob-goodman-about-one-of-the-greatest-minds-in-history/    

Are AI giants really trustworthy? A new report reveals shocking transparency issues in AI development, raising concerns about bias and safety. The discussion highlights Gary Marcus's call for openness, urging consumers to be aware of the implications behind the AI products they use. The focus is on the crucial need for accountability and ethical practices in this rapidly evolving technology.

We're revisiting one of our most popular episodes from last year, where renowned financial expert Chris Skinner explores the future of money. In this fascinating discussion, Skinner dives deep into cryptocurrencies, digital currencies, AI, and even the metaverse. He touches on government regulations, the role of tech in finance, and what these innovations mean for humanity. Now, one year later, we encourage you to listen again and reflect—how much has changed? Are Chris Skinner's predictions still holding up, or has the financial landscape evolved in unexpected ways? Tune in and find out!

In this episode, join me and the Kaggle Grand Master, Konrad Banachewicz, for a hilarious journey into the zany world of data science trends. From algorithm acrobatics to AI, creativity, Hollywood movies, and music, we just can't get enough. It's the typical episode with a dose of nerdy comedy you didn't know you needed. Buckle up, it's a data disco, and we're breaking down the binary!   Sponsors Intrepid AI is an AI assisted all-in-one platform for robotics teams. Build robotics applications in minutes, not months. Learn what the new year holds for ransomware as a service, Active Directory, artificial intelligence and more when you download the 2024 Arctic Wolf Labs Predictions Report today at arcticwolf.com/datascience   🔗 Links Mentioned in the Episode: Generative AI for time series: TimeGPT Documentation Lag-llama: GitHub (Note: The benchmark results on this one are pretty horrible) Open source LLM: Olmo Blog Post Quantization for LLM: Hugging Face Guide And finally, don't miss Konrad's Substack for more nerdy goodness! (If you're there already, be there again! 😄)

Join Mike, a software executive and passionate game developer, as he shares his insights on the fusion of AI and game development. The trio dives into how AI can revolutionize design, enhance player experiences, and streamline production cycles. They discuss real-world applications like GameGPT and the delicate balance between automation and human creativity. Mike highlights the importance of a robust understanding of game design while encouraging developers to embrace AI as a supportive tool in their creative journey.

Dive into the intriguing world of Large Language Models and their surprisingly creative tendency to hallucinate. Explore the challenges of training these models, focusing on the delicate balance between creativity and factual accuracy. Discover a groundbreaking approach from Lamini AI aimed at reducing these inaccuracies while addressing the environmental impact of model training. Can LLMs really evolve beyond fabrication? Tune in for insights into AI's complex relationship with truth!

Gary Marcus, a leading voice in artificial intelligence and advocate for responsible AI, discusses the current generative AI landscape. He addresses the skepticism surrounding the hype and questions whether the AI investment bubble is set to burst. The conversation touches on OpenAI's precarious position amid leadership changes and competition, and the ethical implications of evolving business strategies. Marcus calls for stronger regulations to safeguard user privacy as the tech industry faces potential correction.

In this insightful episode, we dive deep into the pressing issue of data privacy, where 86% of U.S. consumers express growing concerns and 40% don't trust companies to handle their data ethically. Join us as we chat with the Vice President of Engineering at MetaRouter, a cutting-edge platform enabling enterprises to regain control over their customer data. We explore how MetaRouter empowers businesses to manage data in a 1st-party context, ensuring ethical, compliant handling while navigating the complexities of privacy regulations.   Sponsors Intrepid AI (https://intrepid.ai) is an AI assisted all-in-one platform for robotics teams. Build robotics applications in minutes, not months   References https://www.metarouter.io/post/mastering-data-governance-why-governance-at-the-point-of-collection-is-a-must-have  https://hubs.ly/Q02HwJly0  https://www.metarouter.io/post/why-privacy-sandbox-is-a-good-paradigm-shift-for-consumers 

Join David Marom, Head of Panoply Business, as he discusses the benefits of all-in-one data platforms. Topics include tech stack consolidation, improving data accuracy, enhancing data governance, and success stories from organizations using Panoply. Learn about the cost-cutting advantages of transitioning to efficient solutions and streamlining data collection and analysis processes with Panoply.

Learn about the inner workings of GPUs and how they handle complex computations, from gaming graphics to scientific simulations. Explore the differences between CPU and GPU architectures, including instruction execution, caches, ALUs, cores, and GPU features like threads, blocks, and resource allocation.