Data Science at Home

Your Favorite AI Startup is Probably Bullshit (Ep. 298) [RB]

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
 

Why AI Researchers Are Suddenly Obsessed With Whirlpools (Ep. 297) [RB]

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/
 

AGI: The Dream We Should Never Reach (Ep. 296)

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CEO is obsolete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
 
 

When Data Stops Being Code and Starts Being Conversation (Ep. 297)

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
 

Your AI Strategy is Burning Money: Here's How to Fix It (Ep.295)

Most companies don't have an AI problem. They have a decision-making problem. Matt Lea, founder of Schematical and CloudWarGames, has spent nearly 20 years helping tech leaders ship smarter.
In this conversation, he breaks down when AI actually makes sense, where AWS costs spiral out of control, and why your "cool demo" keeps dying before launch. If you're tired of AI hype and ready for straight answers, hit play. Join the conversation! Our Discord community is full of ML engineers, researchers, and AI enthusiasts discussing papers, sharing projects, and helping each other level up. Whether you're debugging your first neural net or training your tenth transformer, there's a place for you. 
 
 
Newsletter https://datascienceathome.substack.com/subscribe
Website https://datascienceathome.com
 
References
http://schematical.com
https://cloudwargames.com
https://schematical.com/posts/we-need-ai_20241028
 

From Tokens to Vectors: The Efficiency Hack That Could Save AI (Ep. 294)

LLMs generate text painfully slow, one low-info token at a time. Researchers just figured out how to compress 4 tokens into smart vectors & cut costs by 44%—with full code & proofs! Meanwhile OpenAI drops product ads, not papers. We explore CALM & why open science matters. 🔥📊
 
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
 

Why AI Researchers Are Suddenly Obsessed With Whirlpools (Ep. 293)

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/
 

The Scientists Growing Living Computers in Swiss Labs (Ep. 292)

Fred Jordan, Co-CEO of FinalSpark, takes us inside the radical world of biological computing, where real neurons extracted from human tissue are being trained to solve problems that would require 10 megawatts in silicon. We explore the life support systems keeping these "wetware" processors alive, the ethical quandaries of computation performed by living cells, and why the messiness of biology might be exactly what AI needs next. From training cycles and reproducibility challenges to the surprising behaviors these neural networks display, Jordan paints a picture of 2030 where your devices might be powered by something closer to a brain than a chip.
 
Sponsors
 
This episode is proudly sponsored by Amethix Technologies. At the intersection of ethics and engineering, Amethix creates AI systems that don’t just function—they adapt, learn, and serve. With a focus on dual-use innovation, Amethix is shaping a future where intelligent machines extend human capability, not replace it. Discover more at https://amethix.com This episode is brought to you by Intrepid AI. From drones to satellites, Intrepid AI gives engineers and defense innovators the tools to prototype, simulate, and deploy autonomous systems with confidence. Whether it's in the sky, on the ground, or in orbit—if it's intelligent and mobile, Intrepid helps you build it. Learn more at intrepid.ai
 
References
Website: finalspark.com
Discord account:   / discord  
Newsletter: https://finalspark.com/#newsletter
 
Topics: Biological computing • Neural engineering • Energy-efficient AI • Wetware vs hardware • The future of computation

When AI Hears Thunder But Misses the Fear (Ep. 291)

Sanjoy Chowdhury reveals AI's hidden weakness: while systems can see objects and hear sounds perfectly, they can't reason across senses like humans do. His research at University of Maryland College Park, including the Meerkat model and AVTrustBench, exposes why AI recognizes worried faces and thunder separately but fails to connect them—and what this means for self-driving cars and medical AI.
 
Sponsors
This episode is proudly sponsored by Amethix Technologies. At the intersection of ethics and engineering, Amethix creates AI systems that don’t just function—they adapt, learn, and serve. With a focus on dual-use innovation, Amethix is shaping a future where intelligent machines extend human capability, not replace it. Discover more at https://amethix.com
 
This episode is brought to you by Intrepid AI. From drones to satellites, Intrepid AI gives engineers and defense innovators the tools to prototype, simulate, and deploy autonomous systems with confidence. Whether it's in the sky, on the ground, or in orbit—if it's intelligent and mobile, Intrepid helps you build it. Learn more at intrepid.ai
 
Resources:
The first audio-visual LLM with fine-grained understanding: Meerkat: Audio-Visual Large Language Model for Grounding in Space and Time (Accepted at ECCV 2024)
Benchmark for evaluating the robustness to adversarial attacks, compositional reasoning: AVTrustBench: Assessing and Enhancing Reliability and Robustness in Audio-Visual LLMs (Accepted at ICCV 2025)
First audio-visual reasoning evaluation benchmark and test time reasoning distillation pipeline AURELIA: Test-time Reasoning Distillation in Audio-Visual LLMs Accepted at ICCV 2025
For a detailed list of Sanjoy's work, please visit his webpage: https://schowdhury671.github.io/

Why VCs Are Funding $100M Remote Control Toys (Ep. 290)

This episode exposes the uncomfortable truth: most defense tech startups are just software engineers cosplaying as military innovators, creating fragmented solutions that Pentagon doesn't need. Not now, at least.
 
References
War On The Rocks: https://warontherocks.com/2025/08/ukraine-isnt-the-model-for-winning-the-innovation-war/
LinkedIn: https://www.linkedin.com/in/jonasrsinger/
Spotify: https://tr.ee/Omy_1X8k1U
Apple Podcast: https://podcasts.apple.com/us/podcast/defence-innovation-podcast/id1797131332
YouTube: https://youtube.com/@DefenceInnovationpodcast?si=cu2WlnVgL5XKnM0p
 
Sponsors
This episode is proudly sponsored by Amethix Technologies. At the intersection of ethics and engineering, Amethix creates AI systems that don’t just function—they adapt, learn, and serve. With a focus on dual-use innovation, Amethix is shaping a future where intelligent machines extend human capability, not replace it. Discover more at https://amethix.com
 
This episode is brought to you by Intrepid AI. From drones to satellites, Intrepid AI gives engineers and defense innovators the tools to prototype, simulate, and deploy autonomous systems with confidence. Whether it's in the sky, on the ground, or in orbit—if it's intelligent and mobile, Intrepid helps you build it. Learn more at intrepid.ai
 
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