Data Science at Home

Right now, millions of people are simultaneously chatting with a system that remembers nothing, knows nothing, and resets after every message. The engineering keeping that illusion alive is actually the impressive part.

 

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NEW TO DATA SCIENCE AT HOME? Welcome! Data Science at Home explores the latest in AI, data science, and machine learning. Whether you’re 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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The brutal truth about why Silicon Valley is blowing billions on glorified autocomplete while pretending it's the next iPhone.

We're diving deep into the AI investment circus where VCs who can't code are funding companies that barely understand their own technology. From blockchain déjà vu to the "ChatGPT wrapper" economy—this episode will make you question every AI valuation you've ever seen.

Fair warning: We're naming names and calling out the hype. Don't listen if you work at a "revolutionary AI startup" that's just OpenAI's API with a pretty interface.

 

#AIBubble #VentureCapital #TechReality #StartupBullshit

VortexNet uses actual whirlpools to build neural networks. Seriously.
By borrowing equations from fluid dynamics, this new architecture might solve deep learning's toughest problems—from vanishing gradients to long-range dependencies.
Today we explain how vortex shedding, the Strouhal number, and turbulent flows might change everything in AI.

 

Sponsors

This episode is brought to you by Statistical Horizons 
At Statistical Horizons, you can stay ahead with expert-led livestream seminars that make data analytics and AI methods practical and accessible.
Join thousands of researchers and professionals who’ve advanced their careers with Statistical Horizons.
Get $200 off any seminar with code DATA25 at https://statisticalhorizons.com

 

 

References

https://samim.io/p/2025-01-18-vortextnet/

Also on YouTube

 

Two AI experts who actually love the technology explain why chasing AGI might be the worst thing for AI's future—and why the current hype cycle could kill the field we're trying to save. Want to dive deeper? Head to datascienceathome.com for detailed show notes, code examples, and exclusive deep-dives into the papers we discuss.

 

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References

CEO is obsolete

AI is the new blockchain

Dr Eliseo Ferrante NYU

https://nyuad.nyu.edu/en/academics/divisions/science/faculty/eliseo-ferrante.html

Mark Brocato built Mockaroo—the tool that taught millions of developers how to fake data. Now, as Head of Engineering at Tonic.ai, he's building the AI agent that's making his own creation obsolete. In this episode, we explore why static test data can't survive the AI era, what it means to "negotiate" datasets with an agent instead of scripting them, and whether we're heading toward a future where sandbox environments vanish entirely. From the hidden failures of legacy mocks to the security implications of agent-driven synthesis, Mark reveals what happens when data generation becomes a conversation—not a pipeline.

 

Sponsors

 

Tonic.ai Synthetic data solutions for software and AI development. Accelerate engineering velocity and ensure compliance with AI-powered data synthesis

 

This episode is brought to you by Statistical Horizons 
At Statistical Horizons, you can stay ahead with expert-led livestream seminars that make data analytics and AI methods practical and accessible.
Join thousands of researchers and professionals who’ve advanced their careers with Statistical Horizons.
Get $200 off any seminar with code DATA25 at https://statisticalhorizons.com