About this Show
Data Science at Home is a podcast about machine learning, artificial intelligence and algorithms.
The show is hosted by Dr. Francesco Gadaleta on solo episodes and interviews with some of the most influential figures in the field
Technology, AI, machine learning and algorithms. Come join the discussion on Discord! https://discord.gg/4UNKGf3
15 hours ago
15 hours ago
In this episode of Data Science at Home, weāre diving deep into the powerful strategies that top AI companies, like OpenAI, use to scale their systems to handle millions of requests every minute! From stateless services and caching to the secrets of async processing, discover 8 essential strategies to make your AI and machine learning systems unstoppable. Whether you're working with traditional ML models or large LLMs, these techniques will transform your infrastructure. Hit play to learn how the pros do it and apply it to your own projects!
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LISTEN / SUBSCRIBE TO THE PODCAST
YouTube: https://www.youtube.com/@DataScienceatHome
Apple Podcasts: https://podcasts.apple.com/us/podcast/data-science-at-home/id1069871378
Podbean Podcasts: https://datascienceathome.podbean.com/
Player Fm: https://player.fm/series/data-science-at-home-2600992
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Chapters
00:00 Intro
00:34 Scalability Strategies
01:08 Stateless Services
02:47 Horizontal Scaling
04:51 Load Balancing
06:14 Auto Scaling
07:41 Caching
09:27 Database Replication
11:07 Database Sharding
12:54 Async Processing
14:50 Infographics
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RESOURCES & LINKS
Data Science at home: https://datascienceathome.com
Amethix Technologies: https://amethix.com
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CONNECT WITH US!
Instagram: https://www.instagram.com/datascienceathome/
Twitter: @datascienceathome
Facebook: https://www.facebook.com/datascienceAH
LinkedIn: https://www.linkedin.com/company/data-science-at-home-podcast
Discord Channel: https://discord.gg/4UNKGf3
NEW TO DATA SCIENCE AT HOME?
Welcome! Data Science at Home explores the latest in AI, data science, and machine learning. Whether youāre a data professional, tech enthusiast, or just curious about the field, our podcast delivers insights, interviews, and discussions. Learn more at https://datascienceathome.com
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SEND US MAIL!
We love hearing from you! Send us mail at:Ā hello@datascienceathome.com
Monday Nov 25, 2024
Monday Nov 25, 2024
Monday Nov 25, 2024
In this episode of Data Science at Home, host Francesco Gadaleta dives deep into the evolving world of AI-generated content detection with experts Souradip Chakraborty, Ph.D. grad student at the University of Maryland, and Amrit Singh Bedi, CS faculty at the University of Central Florida.Ā
Together, they explore the growing importance of distinguishing human-written from AI-generated text, discussing real-world examples from social media to news. How reliable are current detection tools like DetectGPT? What are the ethical and technical challenges ahead as AI continues to advance? And is the balance between innovation and regulation tipping in the right direction?Ā
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Tune in for insights on the future of AI text detection and the broader implications for media, academia, and policy.
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ChaptersĀ
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00:00 - IntroĀ
00:23 - Guests: Souradip Chakraborty and Amrit Singh BediĀ
01:25 - Distinguish Text Generation By AIĀ
04:33 - Research on Safety and Alignment of Generative ModelĀ
06:01 - Tools to Detect Generated AI TextĀ Ā
11:28 - Water Marking
18:27 - Challenges in Detecting Large Documents Generated by AIĀ
23:34 - Number of TokensĀ
26:22 - Adversarial Attack
29:01 - True Positive and False Positive of DetectorsĀ
31:01 - Limit of TechnologiesĀ
41:01 - Future of AI Detection TechniquesĀ
46:04 - Closing Thought
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Subscribe to our new YouTube channel https://www.youtube.com/@DataScienceatHome
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Wednesday Nov 20, 2024
Wednesday Nov 20, 2024
Wednesday Nov 20, 2024
Welcome to Data Science at Home, where we donāt just drink the AI Kool-Aid. Today, weāre dissecting Sam Altmanās āAI manifestoāāa magical journey where, apparently, AI will fix everything from climate change to your grandma's back pain. Superintelligence is ājust a few thousand days away,ā right? Sure, Sam, and my catās about to become a calculus tutor.
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In this episode, Iāll break down the bold (and often bizarre) claims in Altmanās grand speech for the Intelligence Age. Iāll give you the real scoop on whatās realistic, whatās nonsense, and why some tech billionaires just canāt resist overselling. Think AIās all-knowing, all-powerful future is just around the corner? Letās see if we can spot the fairy dust.
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Strap in, grab some popcorn, and get ready to see past the hype!
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Chapters
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00:00 - Intro
00:18 - CEO of Baidu Statement on AI Bubble
03:47 - News On Sam Altman Open AI
06:43 - Online Manifesto "The Intelleigent Age"
13:14 - Deep Learning
16:26 - AI gets Better With Scale
17:45 - Conclusion On Manifesto
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Still have popcorns?Ā Get some laughs at https://ia.samaltman.com/Ā
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#AIRealTalk #NoHypeZone #InvestorBaitAlert
Wednesday Nov 13, 2024
Wednesday Nov 13, 2024
Wednesday Nov 13, 2024
In this episode of Data Science at Home, we dive into the hidden costs of AIās rapid growth ā specifically, its massive energy consumption. With tools like ChatGPT reaching 200 million weekly active users, the environmental impact of AI is becoming impossible to ignore. Each query, every training session, and every breakthrough come with a price in kilowatt-hours, raising questions about AIās sustainability.
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Join us, as we uncovers the staggering figures behind AI's energy demands and explores practical solutions for the future. From efficiency-focused algorithms and specialized hardware to decentralized learning, this episode examines how we can balance AIās advancements with our planet's limits. Discover what steps we can take to harness the power of AI responsibly!
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Check our new YouTube channel at https://www.youtube.com/@DataScienceatHome
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Chapters
00:00 - Intro
01:25 - Findings on Summary Statics
05:15 - Energy Required To Querry On GPT
07:20 - Energy Efficiency In BlockChain
10:41 - Efficicy Focused Algorithm
14:02 - Hardware Optimization
17:31 - Decentralized Learning
18:38 - Edge Computing with Local Inference
19:46 - Distributed Architectures
21:46 - Outro
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#AIandEnergy #AIEnergyConsumption #SustainableAI #AIandEnvironment #DataScience #EfficientAI #DecentralizedLearning #GreenTech #EnergyEfficiency #MachineLearning #FutureOfAI #EcoFriendlyAI #FrancescoFrag #DataScienceAtHome #ResponsibleAI #EnvironmentalImpact
Wednesday Nov 06, 2024
Wednesday Nov 06, 2024
Wednesday Nov 06, 2024
Subscribe to our new channel https://www.youtube.com/@DataScienceatHome
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In this episode of Data Science at Home, we confront a tragic story highlighting the ethical and emotional complexities of AI technology. A U.S. teenager recently took his own life after developing a deep emotional attachment to an AI chatbot emulating a character from Game of Thrones. This devastating event has sparked urgent discussions on the mental health risks, ethical responsibilities, and potential regulations surrounding AI chatbots, especially as they become increasingly lifelike.
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šļø Topics Covered:
AI & Emotional Attachment: How hyper-realistic AI chatbots can foster intense emotional bonds with users, especially vulnerable groups like adolescents.
Mental Health Risks: The potential for AI to unintentionally contribute to mental health issues, and the challenges of diagnosing such impacts. Ethical & Legal Accountability: How companies like Character AI are being held accountable and the ethical questions raised by emotionally persuasive AI.
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šØ Analogies Explored:
From VR to CGI and deepfakes, we discuss how hyper-realism in AI parallels other immersive technologies and why its emotional impact can be particularly disorienting and even harmful.
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š ļø Possible Mitigations:
We cover potential solutions like age verification, content monitoring, transparency in AI design, and ethical audits that could mitigate some of the risks involved with hyper-realistic AI interactions. š Key Takeaways: As AI becomes more realistic, it brings both immense potential and serious responsibility. Join us as we dive into the ethical landscape of AIāanalyzing how we can ensure this technology enriches human lives without crossing lines that could harm us emotionally and psychologically. Stay curious, stay critical, and make sure to subscribe for more no-nonsense tech talk!
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Chapters
00:00 - Intro
02:21 - Emotions In Artificial Intelligence
04:00 - Unregulated Influence and Misleading Interaction
06:32 - Overwhelming Realism In AI
10:54 - Virtual Reality
13:25 - Hyper-Realistic CGI Movies
15:38 - Deep Fake Technology
18:11 - Regulations To Mitigate AI Risks
22:50 - Conclusion
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#AI#ArtificialIntelligence#MentalHealth#AIEthics#podcast#AIRegulation#EmotionalAI#HyperRealisticAI#TechTalk#AIChatbots#Deepfakes#VirtualReality#TechEthics#DataScience#AIDiscussion #StayCuriousStayCritical
Monday Oct 28, 2024
Monday Oct 28, 2024
Monday Oct 28, 2024
Ever feel like VC advice is all over the place? Thatās because it is. In this episode, I expose the madness behind the money and how to navigate their confusing advice!
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Watch the video at https://youtu.be/IBrPFyRMG1Q
Subscribe to our new Youtube channel https://www.youtube.com/@DataScienceatHomeĀ
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00:00 - Introduction
00:16 - The Wild World of VC Advice
02:01 - Grow Fast vs. Grow Slow
05:00 - Listen to Customers or Innovate Ahead
09:51 - Raise Big or Stay Lean?
11:32 - Sell Your Vision in Minutes?
14:20 - The Real VC Secret: Focus on Your Team and Vision
17:03 - Outro
Monday Oct 21, 2024
Monday Oct 21, 2024
Monday Oct 21, 2024
Can AI really out-compress PNG and FLAC? š¤ 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. š§ š„
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: āļø How LLMs leverage probabilistic patterns for compression š Why compression efficiency doesnāt equal general intelligence š The practical (and ridiculous) challenges of using AI for compression š” Can AI actually BREAK Shannonās limitāor is it just an illusion?
If you love AI, algorithms, or just enjoy some good old myth-busting, this oneās for you. Don't forget to hit subscribe for more no-nonsense takes on AI, and join the conversation on Discord!
Letās decode the truth together. Join the discussion on the new Discord channel of the podcast https://discord.gg/4UNKGf3
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Don't forget to subscribe to our new YouTube channelĀ
https://www.youtube.com/@DataScienceatHome
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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/
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Saturday Oct 12, 2024
Saturday Oct 12, 2024
Saturday Oct 12, 2024
Are AI giants really building trustworthy systems? A groundbreaking transparency report by Stanford, MIT, and Princeton says no. In this episode, we expose the shocking lack of transparency in AI development and how it impacts bias, safety, and trust in the technology. Weāll break down Gary Marcusās demands for more openness and what consumers should know about the AI products shaping their lives.
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Check our new YouTube channel https://www.youtube.com/@DataScienceatHome and Subscribe!Ā
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Cool links
https://mitpress.mit.edu/9780262551069/taming-silicon-valley/
http://garymarcus.com/index.html
Tuesday Oct 08, 2024
Tuesday Oct 08, 2024
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 reflectāhow 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!
Tuesday Oct 01, 2024
Tuesday Oct 01, 2024
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!
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š 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! š)
Data Science at Home is the top-10 best data science podcasts on Apple Podcasts, Spotify, Stitcher, Podbean and many more aggregators.
We reach our audience on a weekly basis via 30-minute episodes enriched with blog posts and show notes. Our episodes reach a highly targeted audience across a wide demographics and globally distributed.
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Data Science at Home is a podcast about machine learning, artificial intelligence and algorithms.
The show is hosted by Dr. Francesco Gadaleta on solo episodes and interviews with some of the most influential figures in the field