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.

Sponsors

This episode is brought to you by Statistical Horizons 

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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Website https://datascienceathome.com

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CEO is obsolete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 

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.

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

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.

Sponsors

This episode is brought to you by Statistical Horizons 

VortexNet uses actual whirlpools to build neural networks. Seriously.

Sponsors

This episode is brought to you by Statistical Horizons 

References

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

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:

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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