February 3, 2026
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Training neural networks faster usually involves the usage of powerful GPUs. In this episode I explain an interesting method from a group of researchers from Google Brain, who can train neural networks faster...
February 3, 2026
Some of the most powerful NLP models like BERT and GPT-2 have one thing in common: they all use the transformer architecture. Such architecture is built on top of another important concept already known to the community: self-attention.In this episode I ...
February 3, 2026
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 […]
February 3, 2026
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 […]
February 3, 2026
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 […]
December 23, 2025
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 […]
November 26, 2025
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 […]
November 12, 2025
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 […]
October 30, 2025
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 […]
October 23, 2025
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 […]



